In this episode, I explore the difference between productivity and agency: the ability to decide what should happen next, act with incomplete information, and take responsibility for the outcome.

We get into:

• Why AI compresses time, skill, capability, and organizational effort

• Why doing the wrong thing 10x faster is still waste

• How AI is narrowing some skill gaps and expanding what individuals can execute

• Why judgment and direction become more important as output gets easier

• The productivity trap of generating endless plausible, unnecessary work

• Why high agency also means knowing when to stop, kill a project, or ignore the trend

Generative AI and professional writing
ChatGPT reduced completion time by 40% and increased output quality by 18% in an MIT study of professional writing tasks.

Generative AI in customer support
AI assistance increased productivity by 14% overall and by 34% among novice and lower-skilled workers.

AI task-completion horizon
METR research finds that the length of software tasks frontier AI agents can complete with 50% reliability has historically doubled roughly every seven months.

Personal initiative and agency
A randomized trial in Togo found personal initiative training increased small-business profits by 30%, versus a statistically insignificant 11% from traditional business training.

00:00 Why agency matters more when execution gets cheaper
01:49 What agency actually means
03:08 The four kinds of AI compression
04:50 The expanding AI task horizon
05:56 Productivity vs. agency
07:02 The AI productivity trap
07:55 Can agency be trained?
09:21 Restraint as a form of agency
10:20 End

“Productivity improves the speed of the vehicle. Agency chooses where the vehicle goes.”

“As AI makes action cheaper, restraint becomes more valuable too.”

Noy & Zhang — Experimental evidence on the productivity effects of generative AI (Science)

Brynjolfsson, Li & Raymond — Generative AI at Work (NBER)

METR — Task-Completion Time Horizons of Frontier AI Models

Campos et al. — Personal initiative training in Togo (Science/PubMed)

Brand Runner is for creative leaders and operators who want sharper thinking on creative productivity, creative operations, AI-enabled workflows, and the systems behind better marketing work.

Subscribe: https://brandrunner.substack.com/
LinkedIn: https://www.linkedin.com/in/fabien-hameline/
Work: https://fabienhameline.com/

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There’s a version of the creative process most people carry around in their heads. An idea arrives. You plan it out. You execute. Done.

That version is wrong.

The real process looks more like a loop. An idea germinates. You think about it for a while. Then you start planning — every step, every dependency, every thing that needs to happen before the thing can happen. Then you execute for a bit. Then something changes, or you learn something, or the idea itself shifts, and you’re back in the planning stage. This cycle repeats. Sometimes for days. Sometimes for years.

Every time you return to the planning stage, you spend something. Attention, cognitive energy, the mental capacity to hold complexity and make decisions about it. The problem is that this spending is invisible. There’s no transaction notification. You just slowly notice that the creative work feels harder, slower, more effortful than it should.

That’s a resource problem. And most people mistake it for something else entirely.

What flow state actually requires

Mihaly Csikszentmihalyi spent decades studying what he called flow — the state where creative work stops feeling like work and starts feeling like something closer to inevitability. His finding wasn’t mysterious: flow happens when challenge and skill are matched, feedback is immediate, and the goal is clear.

But there’s a condition underneath those conditions that gets less attention. Flow requires a mind that isn’t already occupied.

You can’t drop into deep creative work while part of your brain is still managing the unresolved decision from this morning, the task you moved for the third time this week, the email you haven’t answered that keeps surfacing. That background processing doesn’t stop just because you open a new document. It runs beneath the surface and taxes the same cognitive resource your creative work depends on.

Csikszentmihalyi described creative output as something that compounds. One hour of real flow makes the next session easier, because you’ve built something to return to. The inverse is also true. Interrupted, fragmented, cognitively taxed creative work compounds downward. The conditions deteriorate faster than the work accumulates.

Modern life is optimized to interrupt this. The interruption people usually blame — the phone notification, the Slack ping — is mostly a symptom. The root problem runs deeper.

The real enemy: cognitive residue

Gloria Mark at UC Irvine has spent years studying how people actually work. One of her findings is well known: it takes an average of about 23 minutes to return to a task after an interruption. That number gets cited as an argument for turning off notifications, which is fine but misses the point.

The deeper finding is about what she calls attention residue. When you leave one task for another — even voluntarily, even briefly — part of your working memory stays attached to the original task. You’re physically present at the new thing, but cognitively, you’re still partly somewhere else.

Scale that across a full day. Across a week of re-planning the same project, re-triaging the same task list, re-deciding the same priorities because they weren’t written anywhere trustworthy. The residue accumulates. By the time you sit down to do the work you actually care about, you’re already carrying weight you can’t see.

Daniel Kahneman’s framework makes this concrete. The kind of thinking that planning and deciding require — what he called System 2 — is slow, deliberate, and finite. Every time you re-decide something you already decided, you draw from the same reserve that creative work depends on. The tank isn’t bottomless.

This is what quietly kills creative output. Not laziness. Not lack of discipline. Cognitive residue — the accumulated cost of all the thinking your brain is doing that isn’t creating anything.

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Systems as protection, not productivity

Most people build systems to produce more. The productivity industry runs on this premise: better tools, better workflows, faster throughput.

That framing misses the real leverage.

A system you trust reduces the cognitive cost of operating. The decisions that were draining you — what to work on, in what order, what’s actually urgent, what you promised someone last week — get resolved before you sit down to create. The mental space you were spending on those decisions is now available for the work itself.

Think of it as environmental protection. A creative practice without systems is constantly exposed to the ambient demands of a busy life. Re-planning pulls you out. Re-deciding depletes you. Context-switching leaves residue. The work happens in whatever space is left over, which is usually not much.

Systems clear that. A trusted task list reviewed once a day removes the re-sorting tax. A morning ritual means you’ve decided what matters before the noise begins. A weekly recap keeps you from disappearing into execution without ever surfacing. Protected create time — even thirty minutes with no fixed agenda — is the slot where the compounding actually has room to happen.

The sophistication isn’t in the tools. It’s in understanding what you’re actually protecting.

What this looks like in practice

A task list organized by area — content, projects, admin, whatever the relevant categories are — removes the overhead of re-sorting. When everything lives in one undifferentiated list, every review requires re-triaging. Categorized lists mean your eye goes to the right place and the decision is already half made.

A morning review before the day begins means you’re deciding once, rather than reactively all day. You see what’s urgent, confirm your priorities, and start from intention instead of catching up to circumstances.

A weekly recap serves a different function. It’s accountability that exists outside your own head. You see what you finished, what you moved, what you’ve been circling without resolving. The view from above is different from the view inside the work, and most people only ever get the latter.

Daily create time matters because the compounding only happens if there’s continuity. A creative practice that only activates when conditions are perfect never activates at all. Thirty minutes of tinkering or brainstorming is enough to keep the thread alive between the sessions where real work happens.

The thing worth protecting

You don’t protect a creative practice by working harder or longer. The people who produce the most interesting work over time aren’t the ones who push through — they’re the ones who’ve learned to protect the conditions where their thinking can actually move.

Cognitive rest isn’t a luxury. An empty-enough mind isn’t a nice-to-have. These are the inputs. Everything else is downstream.

Systems don’t create the work. They create the silence the work needs.

Source

• Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. Harper & Row. — The compounding creative output argument and the conditions for flow.

• Mark, G., Gudith, D., & Klocke, U. (2008). The cost of interrupted work: More speed and stress. CHI ‘08 Proceedings. — The ~23 minutes finding and attention residue.

• Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux. — System 1 / System 2 and the finite nature of deliberate thinking.

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I rarely take handwritten notes in meetings anymore.

A few years ago that would have felt like a confession. The notebook was the badge of the serious operator. Sit down, open the page, write the date, capture the points, circle the action items, look attentive.

Now Granola AI captures the conversation and I stay in it. That tradeoff feels obvious to me now. In a good meeting my attention belongs on the person, the tension, the decision forming in the room. If I am looking down to preserve every useful sentence, I am partly absent from the thing I am trying to understand.

AI is very good at storage. Let it do the storing.

What still deserves the pen

That does not make handwriting obsolete. It sharpens the real question: what still deserves to be written by hand?

For me the answer keeps getting narrower. Cards, because a few words should feel like they came from a person and not a clean productivity system. Journaling. A flowchart, because some decisions need arrows, boxes, crossings-out, and a little ugliness before they become clear.

And one new category I have started building around: the judgment book.

What a judgment book is

Not a diary. Not a productivity notebook. Not a meeting log.

A judgment book is where I record meaningful decisions by hand. The point is not to capture what happened, because AI already does that better than I can. The point is to slow down long enough to understand what I chose, what I refused, and what would prove me wrong.

That distinction is the whole thing.

Retrieval is only half the job

Most knowledge systems are built for retrieval. Can I find this later, tag it, query it, connect it to six other notes in Obsidian?

Fair questions, and I ask them constantly. But retrieval is only half the job. The harder we optimize for it, the more we treat every passing thought like an asset before it has earned the status. Some thoughts need to stay messy for a while. Some decisions need to be argued with on paper before they become knowledge.

Mueller and Oppenheimer found that students who took notes by hand understood the material better than those who typed. The reason was simple: typists could transcribe fast enough to copy things down word for word, while the slower hand forced the writers to filter and rephrase as they went. The processing was the point. But the mechanism matches what I feel on the page. The slowness makes you decide what actually matters before you write it.

This is where the paper page still wins. A page has a physical honesty to it. You see the false starts. You see the sentence you crossed out. You remember where the idea lived: top left, after a bad night, pressed too hard into the paper because you were annoyed and pretending you were calm. Digital notes flatten all of that. They make everything searchable and, in the process, make everything equally clean.

Clean is useful once the thinking is done. It is not always useful while the thinking is happening.

The workshop and the library

So the system I want is simple. Paper is the workshop. Obsidian is the library. The judgment book lives in the workshop, and only the durable part ever moves to the shelf.

A decision page can hold the situation, the options, the reason I picked one path, the fear sitting underneath the choice, and the single condition that would make me change my mind. It is allowed to be imperfect. It can have arrows. It can contain a sentence that would embarrass me in a polished note. Later, one line graduates into the digital system:

Chose X over Y because the operating reality was stronger than the title.

Kept the system smaller because the extra automation would have created a second job.

Chose paper for reflection, Obsidian for retrieval.

That is the part worth querying years from now. The rest stays in the notebook, where it belongs.

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Judgment stayed expensive

This matters more than it used to, because AI has changed the division of labor. Machines capture, summarize, sort, and retrieve faster than any of us.

Good. Hand it over.

But judgment stayed expensive. Judgment is the part where you decide what matters, what to ignore, what to keep, what to cut, and what kind of operator you are slowly becoming through repeated choices.

That work benefits from friction. Useful friction. The kind that slows your hand just enough for your thinking to catch up. There’s some brain-imaging work that hints at why this might be more than a feeling. A Norwegian team recorded high-density EEG while people wrote by hand and typed the same words, and handwriting lit up far more elaborate connectivity across the regions tied to memory and encoding. Typing didn’t. The study has its critics, and it didn’t test learning directly, so I won’t oversell it. But the shape of it fits: the intricate hand movements seem to pull more of the brain into the act. A specific pen, a specific notebook, a quiet page. Small signals to the nervous system that this is not capture, this is deciding.

The real question is placement

Creative productivity keeps getting reduced to speed. Faster notes, faster summaries, faster drafts, faster publishing. Speed helps when the direction is clear. When the direction is unclear, speed just produces cleaner confusion.

So the real question is placement. Where do you remove friction, and where do you protect it?

Remove it from capture. Let the transcript hold the meeting. Keep it around judgment, and let the notebook hold the decision you refuse to outsource to the transcript.

Years from now I doubt I will care about having perfect meeting notes. I will care whether I can trace how my judgment changed, and whether the trail I left was honest enough to learn from.

The transcript will remember the room. The notebook is where I find out who I became in it.

References

Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: Advantages of longhand over laptop note taking. Psychological Science, 25(6), 1159–1168.

Van der Weel, F. R., & Van der Meer, A. L. H. (2024). Handwriting but not typewriting leads to widespread brain connectivity: A high-density EEG study with implications for the classroom. Frontiers in Psychology, 14, 1219945.

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You open a new chat. You paste the brief. You explain who the audience is, what the product does, the three things you never say, the one thing you always say, the tone, the offer, the proof. The model gives you something. It’s fine. It’s also generic. So you correct it. Then tomorrow you open a different tool and do the whole thing again from zero.

This is most people’s actual relationship with AI right now. Not a partnership. A series of cold introductions to a stranger who keeps forgetting your name.

We’ve decided to call the output the problem. It sounds generic, so the AI must be the issue. But the output is downstream. The real problem is that you keep handing a powerful tool almost nothing to work with, and then acting surprised when it gives you the average.

Adoption went vertical. Context didn’t.

The usage numbers are no longer interesting because they’re no longer in doubt. Around 87% of marketing teams now use generative AI in at least one recurring workflow, up from roughly half just two years earlier. In marketing specifically, AI moved from experiment to default faster than almost any tool in the category’s history.

So the tools are everywhere. The question worth asking is whether the work got better, and there the picture gets honest fast. About 86% of marketers report spending time editing AI-generated content. The time you save generating is quietly handed back in correction. People describe spending longer fixing tone than they’d have spent writing from scratch — which means the productivity story, for a lot of teams, partly cancels itself out.

That’s not a model problem. That’s a context problem.

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Why the average is the default

There’s a mechanical reason AI output drifts toward bland. These models are trained on something close to the average of the internet, so without specific direction, the average is exactly what they return. Left alone, they avoid the distinctive, the opinionated, the specific — the precise qualities that make anything worth reading. The safe phrasing is the most probable phrasing, and the most probable phrasing is what everyone else is also getting.

There’s a good test for this going around: could this paragraph appear on a competitor’s site, unchanged, and nobody would notice? If yes, it’s generic. Not because the AI failed, but because nothing in the prompt told it who you were.

And here’s the part most teams haven’t reconciled. Research suggests roughly 64% of successful marketers have documented brand voice guidelines — but only around 23% are actually feeding those guidelines to their AI tools. The playbook exists. It’s just sitting in a folder while you re-type a worse version of it into a chat window every morning.

Your brand already exists. Your AI just can’t read it.

Here’s the uncomfortable truth under all of this. Your brand context isn’t missing. It’s scattered.

It lives in an old deck, a half-finished positioning doc, three Slack threads, a sales call you half-remember, the website, and a surprising amount of it lives nowhere but your own head. Every one of those is real context. None of it is reachable by the tool you’re asking to sound like you.

Scattered context is, functionally, invisible context. When the model can’t find your approved language, it guesses. And guessing is exactly where voice drift starts.

This is the reframe worth holding onto: brand context isn’t documentation. It’s infrastructure. Documentation is something you write once and file. Infrastructure is the layer everything else runs on. When that layer is sharp, AI gets more useful. When it’s fuzzy, AI faithfully amplifies the fuzz.

Which leads to the line this whole essay is really about: AI didn’t remove the need for brand thinking. It exposed whether you ever did any. When positioning, proof, and voice are vague, AI doesn’t hide it. It scales it.

What I kept running into

I work in creative operations and brand production, which mostly means I’m responsible for output being consistent across a lot of surfaces and a lot of tools. And I kept hitting the same wall the numbers describe.

Every tool started cold. Cursor didn’t know what Claude knew. Claude didn’t know what I’d told ChatGPT last week. I was the integration layer — the human carrying context between systems that couldn’t hold it. That’s a bad use of a person, and it doesn’t scale past one.

So I built the thing I needed: a single structured source of truth my tools could read before they wrote anything. Not a prompt pack. Not a box of tricks. A brand memory layer.

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A note on the built-in tools — including Claude’s

If you use Claude, you’ve probably seen its brand-voice features — the plugins that discover your materials, generate guidelines, and enforce them as you write. They’re good at what they do, other tools are shipping their own versions, and none of this is a knock on them. But notice where they live: a native brand feature runs inside one tool’s ecosystem, set up per user, tied to a subscription. The moment you move to Cursor, or ChatGPT, or an automation, that context doesn’t travel with you — and on a team, those guidelines load per person, with no shared source everyone pulls from.

The fix isn’t to fight any of that. It’s to own a portable layer that works everywhere, including pointed straight at those features. You can hand a brand memory to Claude’s enforcement and get both, and the same layer still works in tools that have no brand feature at all. Build it once, own it as plain files, use it anywhere — that’s the whole bet, and it’s what I ended up building for myself.

What I built, and the part that’s still your job

The thing I made is the Agent-Ready Brand Kit — a markdown-based brand memory system. A structured folder you customize once, then point your tools at before they create, review, or adapt work. It helps you clarify the things AI keeps guessing at: your brand context, your positioning decisions, how the brand should and shouldn’t sound, reusable messaging patterns, output guidance for common formats.

It ships with starter, review, and repurposing prompts so you’re not facing a blank chat after setup — but the prompts support the system, they aren’t the product. It’s plain markdown on purpose: Cursor or GitHub for technical teams, Google Drive for everyone else (or anywhere your company saves safely its knowledge), Obsidian for solo operators. You own the files and carry them to whatever tool you adopt next. No platform owns your brain.

The shift is small to describe and large to live with. Before, you start from a vague prompt, the AI guesses, and you spend your time repairing the output. After, the AI starts from brand memory and you spend your time shaping instead of repairing. It won’t think for you, and it shouldn’t — it organizes your thinking so the tools get more useful.

That’s the line it draws: a starting point for people who care about the brand, not a finished campaign, not a shortcut around judgment. The teams that win the next stretch of this won’t be the ones with the best model (everyone has the same models now). They’ll be the ones who stopped re-explaining themselves every morning and gave their tools something solid to stand on.

If that sounds like a problem you have, the kit’s here. Build the context once, reuse it everywhere.

Sources

• Salesforce State of Marketing 2026 / AI marketing adoption data, via Digital Applied — ~87% of marketing teams using genAI in a recurring workflow; adoption trajectory

• Key Generative AI Statistics and Trends, Sequencr AI — 86% of marketers spend time editing AI-generated content

• How to Maintain Brand Consistency in AI-Generated Content, Averi — 64% have documented brand voice, only 23% feed it to AI tools

• AI Content That Doesn’t Sound Like AI, Averi — why models drift to generic; the competitor-swap test

• How do we maintain our unique brand voice when using AI?, Contentstack — AI trained on the average of the internet; brand consistency revenue impact

• How to ensure brand voice consistency with AI translation, Glean — scattered context as the origin of voice drift

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Creative productivity is not about doing more. It is about reducing the distance between a thought and its output.

That sounds obvious until you watch how most tools behave. They ask for more steps. More windows. More permissions. More tiny decisions at the exact moment your brain is trying to stay with an idea.

Sometimes the friction starts before the tool does. A thought begins to take shape. You make a typo. You hit delete, type more, delete again, correct the correction. By the time you climb out of that loop, the idea has cooled. It is still there, technically. But it is less precise and organic than it was ten seconds ago.

Ideas are fragile at the start.

Protect the loop

Before they become an essay, a brief, a chapter, or a strategy doc, they arrive as something messier. A half-formed sentence. A paragraph you say out loud. A shape without structure yet. That early moment is where the work is most alive and most easily lost.

This is where flow comes in.

Flow is not magic. Mihaly Csikszentmihalyi, who named it, described it as a tight loop between intention, action, and feedback — the thought appears, you move, the work responds, and self-consciousness drops away. You are not managing yourself. You are not managing the tool. You are inside the work.

The wider that loop gets, the more your attention leaks. You open the wrong app. You wait for a spinner. You correct the correction. You wonder whether the audio is being uploaded somewhere, whether your raw thinking is being stored, reviewed, or used to train a model. You start watching what you say.

Akira Kurosawa the famous film director put the writing version of this plainly:

That is flow. And when you lose it, the cost is not the two seconds of waiting. The cost is the break in state. Psychologist Sophie Leroy calls the residue that lingers when you switch tasks “attention residue” — part of your mind stays stuck on the thing you just left. Gloria Mark’s research on interruption points the same direction: getting back to real focus after a break is expensive, and we underestimate how expensive every time.

So the real tax is not friction. It is the broken loop.

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About dictation

For people who think out loud, dictation should be one of the cleanest creative tools we have. Speaking is faster than typing. It carries more energy. It catches the thought before it gets too polished, too polite, too dead.

But most cloud dictation comes with an invisible cost: your voice leaves your machine.

That is fine for some uses, and I am not going to pretend every cloud tool is sinister. There are more advanced products in this space — Wispr Flow, for one, has a nicer interface and is clearly further along. I am not trying to compete with those.

What I wanted was more personal: to see how much I could build myself, and to capture my thinking without sending it to someone else’s servers. Because for deep work — strategy notes, private drafts, client thinking, anything still half-formed — I do not want to negotiate with a privacy policy before I can capture a sentence. And I do not want the quiet question sitting at the back of my head: is this becoming training data?

Maybe it is not. Maybe there are settings. Maybe the policy is clean. Fine. But even the question is cognitive load. And cognitive load is exactly what a creative system should remove.

So I built something simpler. It is called Murmur.

What it is

Murmur is a small local dictation tool for the Mac. You hold a key, speak, release, and the cleaned-up text lands on your clipboard. Transcription runs locally through faster-whisper. Cleanup runs locally through a small Ollama model that strips filler and false starts without changing your meaning.

Nothing leaves the machine. No cloud. No subscription. No app ceremony.

Just:

Hold Right Option. Speak. Release. Paste.

That is the whole philosophy. Not every tool needs to become a platform. Not every workflow needs a dashboard.

Sometimes the best system is the one that protects the moment.

Why I built it

I am writing a book about creative operations — the invisible infrastructure that lets good work actually ship. Predictably, I kept running into the exact problem the book is about.

My best thinking does not always happen neatly at the keyboard. Sometimes it lands while I am talking through a problem at my desk. Sometimes it lands when I step away for a minute and the sentence finally arrives. Sometimes it lives in that middle space where the idea is clear enough to say but not yet ready to write.

By the time I sit down and force myself to type, I am often no longer capturing the thought. I am reconstructing the ghost of it. The energy has cooled. The sentence has become responsible.

Murmur is my bridge back to the live version. It is not trying to replace writing — writing is where taste, structure, and judgment happen. It protects the material before writing begins.

To be clear about its edges: Murmur is desktop-only, and it runs in the terminal. There is no menu bar icon, no onboarding flow. The terminal is where it tells you it is recording, transcribing, cleaning, done.

On day one that small feedback loop matters. After a week you stop looking at it. It is not the tool for catching a thought on a walk — that is a different product. It is for the desk, the home office, the kitchen-counter laptop, the moment when talking is still easier than typing.

A few decisions worth naming

The manual paste is deliberate. The obvious move was to auto-insert text into whatever app you are in. But that path gets messy fast — app focus, macOS permissions, accessibility edge cases, debugging across every place you might paste. So I chose the boring solution. Clipboard first, paste yourself. One extra keystroke, far less complexity. Subtract until it sings.

It is also intentionally hackable. Two knobs sit at the top of the file: one controls how the transcript gets cleaned, one controls the transcription model. You can preserve more roughness, strip more filler, match your own style, disable cleanup for raw transcription, or swap in a cloud API later if you decide you want it. It is not a locked product. It is a small workflow you can understand, change, and break without asking permission.

The models are not bundled. Murmur is the glue.

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The real point

Murmur is free, open source, and MIT licensed. But the script is not the point.

The point is that creative systems should protect flow, not interrupt it. Your best ideas do not always arrive when your fingers are ready. Sometimes the thought needs to be spoken before it can be written. Sometimes the only job of the tool is to catch the sentence before it disappears.

The tool does not need to impress you. It needs to get out of the way fast enough that the thought survives.

No cloud. No subscription. No training-data anxiety humming in the background while you are trying to think. Just speak, capture, paste, keep moving.

When the work matters, protect the loop.

The code lives here: github.com/metafabs/murmur

If you build on it, tune it to your own voice, or use it to catch an idea that would otherwise have vanished, I would like to hear about it.

How to install Murmur on Mac

If you have never touched GitHub, do not let that stop you.

This setup is just a series of copy-paste commands into Terminal.

You need:

• a Mac

• Homebrew

• Ollama

• Terminal

Terminal is already on your Mac. Press Cmd + Space, search for Terminal, then open it.

1. Get the code

Copy and paste this into Terminal:

cd ~
git clone https://github.com/metafabs/murmur.git
cd murmur

This downloads Murmur and opens the Murmur folder.

2. Install the audio library and Python

Copy and paste this:

brew install portaudio
brew install python@3.12

This installs two things:

• portaudio, which Murmur needs to hear your microphone

• Python 3.12, which Murmur will use as a stable Python version

This matters because your Mac can have several Python versions installed. Murmur should not depend on whatever Python your Mac happens to use by default.

3. Create Murmur’s private Python environment

Copy and paste this:

python3.12 -m venv .venv
.venv/bin/python -m pip install --upgrade pip
.venv/bin/python -m pip install -r requirements.txt

This creates a private Python setup inside the Murmur folder.

From now on, Murmur will use this private Python instead of the random default Python on your Mac.

That is why the command uses:

.venv/bin/python

Not:

python3

4. Install and launch Ollama

Copy and paste this:

brew install --cask ollama
open -a Ollama

This installs Ollama and opens it.

Important: leave Ollama open. Murmur needs Ollama running in the background.

5. Download the local cleanup model

Copy and paste this:

ollama pull llama3.1:8b

This downloads the local AI model Murmur uses to clean up your transcript.

It is a large download, so let it finish.

6. Run Murmur

Copy and paste this:

cd ~/murmur
.venv/bin/python murmur.py

On first launch, Murmur may download the transcription model.

macOS may also ask for permissions. Allow them.

Murmur needs:

• Microphone

• Input Monitoring

• Accessibility

You can find these here:

System Settings → Privacy & Security

After granting permissions, quit Terminal, open Terminal again, and run:

cd ~/murmur
.venv/bin/python murmur.py

7. Use Murmur

Hold Right Option, speak, then release.

Wait for the Terminal to confirm that the text is on your clipboard.

Then paste with:

Cmd + V

Press Esc to quit Murmur.

8. Launch Murmur with one word

Once Murmur works, copy and paste this:

echo 'alias murmur="cd ~/murmur && .venv/bin/python murmur.py"' >> ~/.zshrc
source ~/.zshrc

Now you can launch Murmur anytime by typing:

murmur

Feel free to share with someone who might benefit from this tool.

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References

• Mihaly Csikszentmihalyi, Flow: The Psychology of Optimal Experience (1990) — https://www.harpercollins.com/products/flow-mihaly-csikszentmihalyi

• Sophie Leroy, “Why is it so hard to do my work? The challenge of attention residue when switching between work tasks,” Organizational Behavior and Human Decision Processes (2009) — https://www.sciencedirect.com/science/article/abs/pii/S0749597809000399

• Gloria Mark, Attention Span (2023), and “The Cost of Interrupted Work” (CHI 2008) — https://ics.uci.edu/~gmark/Home_page/Research.html

• Akira Kurosawa, Something Like an Autobiography (1982) — quote on first drafts

• faster-whisper — https://github.com/SYSTRAN/faster-whisper

• Ollama — https://ollama.com

Other articles you might be interested in

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In this engaging interview, Farid Ismail shares his multifaceted artistic journey, explores the impact of AI on filmmaking and art, and discusses the future of creativity in the age of technology. Discover insights on how AI supports and challenges creators, the importance of maintaining human authenticity, and the evolving landscape of cinema and digital art.

To subscribe to the Substack here - https://brandrunner.substack.com/

Keywords

AI in filmmaking, digital art, artistic journey, creativity, future of cinema, AI ethics, artistic authenticity

Key topics

AI's impact on filmmaking and art

Maintaining authenticity in digital creation

Future prospects of cinema with AI

Guest name

Farid Ismail

Sound bites

"AI can create with smaller budgets."

"AI films can evoke real emotions."

"Over-reliance on AI can be dangerous."

Chapters

00:00 Introduction to Artistic Versatility

01:58 The Impact of AI on the Film Industry

04:03 AI as a Tool for Creativity

06:31 The Emotional Capacity of AI in Film

09:15 Licensing and Ethical Concerns with AI

12:03 The Role of AI in Creative Processes

17:14 The Future of Human Creativity in an AI World

18:34 Embracing AI in Filmmaking

21:13 The Impact of Technology on Creativity

22:21 Personal Projects and Artistic Expression

23:35 Collaboration and Professionalism in Filmmaking

Resources

The Coming Wave by Mustafa Suleyman - https://the-coming-wave.com/

ChatGPT by OpenAI - https://chat.openai.com/

Claude by Anthropic - https://www.anthropic.com/

Farid Ismail's links

Instagram - https://www.instagram.com/faridfilms/

https://www.linkedin.com/in/faridismail/

For the first two years, working with LLMs was a fight against the model.

Could it write coherently? Could it code? Could it reason through anything that wasn’t a quiz question? You’d ask for a draft and spend forty minutes correcting hallucinations, smoothing tone, restructuring logic the model couldn’t hold. The bottleneck was the machine.

That’s not the fight anymore.

Opus, GPT-5, Gemini Pro — they can all produce competent work now. Not perfect, but competent. The model is no longer the problem. Which means the bottleneck moved, and most people haven’t noticed yet.

The new question isn’t can the model do this?

It’s can the model do this the way I would?

That gap — between competent output and your output — is the actual frontier now. And it doesn’t get solved by bigger models.

A 10M token context window won’t make the LLM think like you. A reasoning upgrade won’t either. Better benchmarks won’t. Because the gap isn’t about capability. It’s about alignment to a specific person’s judgment, taste, and way of deciding.

That’s a structural problem, not a hardware one. And it’s the one nobody is really solving.

The cost of not solving it

Most people patch the gap with iteration. You ask, the model produces something off, you correct, it produces something closer, you correct again, and somewhere on the fourth or fifth pass you get something usable.

That loop is more expensive than it looks.

For you, every misaligned output costs attention. Not the work itself — the correction of the tool. You’re not thinking about the problem you came to solve. You’re thinking about how to re-explain yourself to a system that should already know. Stack that across a day and you’re cognitively depleted by lunch, not from doing the work, but from steering the machine toward something you could have written yourself in less time.

For the model, every iteration eats context. The window is finite. Each round of “no, more like this” burns tokens on alignment overhead — tokens that don’t come back. By the time the model is dialed in, you’ve spent half the context just getting it ready to work. The rest of the thread runs on what’s left.

So the cost of not closing the gap is paid twice. You think slower because you keep re-explaining. The model thinks shorter because alignment ate the window. And the outputs converge toward defaults anyway, because most people give up before reaching full alignment and ship whatever the model produced on round three.

That’s the real tax. Not the time. The cognitive load on both sides of the screen.

Why most skills miss it

The way LLMs are usually customized doesn’t help here.

Skills, custom GPTs, system prompts — they almost all optimize for the same thing: output. Write me a post in this tone. Do this analysis with these constraints. Format it like this. That works when you know exactly what you want and you just need the model to produce it.

But most real work isn’t like that.

Most real work involves deciding — between options, between framings, between what to keep and what to cut. And no skill in the standard library helps with that. They tell the model how to produce. They don’t tell the model how to judge.

That’s the layer that’s missing.

What I built instead

A few weeks ago I started building what I call Thinking OS. I am giving it for free soon.

Not a skill in the usual sense. A meta-skill — a skill about how to use skills. It doesn’t tell the model what to write. It tells the model how to route decisions — using the same lenses, values, and constraints I’d use myself.

I want to be precise about what that means. The OS is not deciding for me. It’s a decision router. It runs options through the closest possible approximation of how I’d think about them, so what surfaces is pre-aligned. But the call is still mine. Always. The system makes the iteration loop shorter; it doesn’t replace the person at the end of it.

A CLAUDE.md file is useful, but it’s not the same thing as a Thinking OS. CLAUDE.md gives Claude project memory: the rules, commands, structure, and preferences it should follow inside a specific codebase. A Thinking OS goes one layer deeper. It doesn’t just tell the model what the project is; it teaches the model how I make decisions, what I reject, what tradeoffs matter, and how to route work through my judgment before it reaches the screen. One is context. The other is alignment.

The frame underneath it is something I’ve been working with for a long time: the Five Rings of Marketing, used not as a marketing system but as five simultaneous lenses for any decision. Earth (foundations). Water (adaptation). Fire (impact). Wind (perspective). Void (vision). Run any option through those five lenses at once and the noise drops out fast.

The OS is LLM-agnostic. It works anywhere there’s a skill-like feature — Claude, ChatGPT, anything that’s coming next. And it’s not designed to do the work for me. It’s designed to filter the work before I see it, so what reaches me is already aligned.

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What changes when you use it

Iteration drops. Sharply.

Not because the model gets smarter. Because the noise gets caught earlier. Options I would have rejected anyway never make it to the screen. Tradeoffs I would have spotted are surfaced before I have to ask. The model proposes things I would have proposed myself — which means I’m not correcting, I’m choosing.

But there’s a layer the OS will never touch, and this matters: taste.

Taste is the felt sense that something is right in a way that can’t be fully justified. It shows up in the room and refuses to be reduced to a rule. No system encodes it. No prompt captures it. It’s the part of judgment that lives in lived experience — what I’ve made, what I’ve refused to make, what I’ve watched land and what I’ve watched die. The OS handles structure, lenses, and alignment. Taste is what I bring.

And this is where the loop gets interesting. Sometimes I’ll push back on a proposal the model made. I’ll say “I don’t think that’s right, here’s why” — and the model will respond “good catch, that’s actually more aligned with your core philosophy, I missed it.”

That’s not the system breaking. That’s the system working exactly as designed. The OS aligns the model to my judgment at high fidelity, but I’m still the one with the full context, the lived experience, the taste. When my correction lands and the model defers, the loop is functioning correctly — because the human is the source of truth the system was built around. The model isn’t competing with me. It’s collaborating at high fidelity, and accepting correction when my taste catches something the lenses didn’t.

That’s a different kind of working relationship with a machine. Not delegation. Not automation. Augmentation in the actual sense of the word.

The cognitive tax goes down on both sides. I stop re-explaining. The context window stops getting burned on alignment. The thread stays sharp longer because we’re not wasting tokens negotiating.

This is consistent with something cognitive psychologists have known for a long time: every time you have to make the same judgment call twice, you pay a decision cost. Roy Baumeister’s work on ego depletion — and Daniel Kahneman’s distinction between System 1 and System 2 thinking — both point to the same thing: deliberative judgment is metabolically expensive, and it’s the first thing to degrade as the day wears on. The point of a system is to convert what would otherwise be a fresh decision into something automatic. You stop spending energy on choices that are already settled.

That’s what Thinking OS does for the human-LLM loop. It moves judgment out of the iteration cycle and into the system layer. The decisions you’ve already made about how you think don’t get re-litigated every prompt. They’re just there.

I’ll have more to say about this soon. There’s a deeper layer underneath — about what these tools actually are in the longer arc of where AI is going, and why the interface we’re using right now (typing words into a box) is more primitive than it looks. That’s the next post.

For now: notice if the bottleneck has moved for you too.

If you’re still fighting the model, you’re working on yesterday’s problem. If you’re fighting alignment, you’re on the new one — and that one doesn’t get solved by waiting for a better model.

It gets solved by building the layer that’s missing.

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References

• Baumeister, R. F. (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology.

• Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.

This is Part 1 of a two-part essay. Part 2 will walk through how to build your own AI collaboration OS, step by step.

We Are Having the Wrong AI Conversation

The current conversation around AI is loud, fast, and oddly repetitive. Every week brings a new model, a new benchmark, a new round of excitement. We argue about which system is smarter, which one reasons better, and which one is worth switching to. Prompts circulate like folk recipes. People compare notes, chase marginal gains, and quietly abandon last month’s breakthrough for the next one.

Yet despite all this activity, something is missing. Very little of it compounds.

Most AI usage today is episodic. You open a chat, extract value, close it, and move on. The next session starts from scratch. Context is rebuilt imperfectly. Nuance is lost. Judgment resets. The tools get better, but the user does not.

That is not a model problem. It is a systems problem.

Intelligence without continuity does not accumulate. It produces bursts of usefulness that quickly decay. The result is a strange paradox. We have access to more intelligence than ever before, yet our thinking remains fragmented. We are faster, but not sharper. More productive, but not more grounded.

What I ended up building looks nothing like the AI products we are used to. It is not a tool. It is not a model. It is closer to an operating system for thinking, a persistent layer that sits above any individual AI system and makes collaboration continuous rather than episodic.

This essay is about why that shift matters now, and why it points toward a quieter, more consequential version of the Singularity than most people are paying attention to.

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Kurzweil, Revisited

Ray Kurzweil has spent decades arguing that humans and machines are on a collision course. In The Singularity Is Nearer, he refines his earlier thesis. The point is not spectacle or science fiction. It is trajectory. Computation gets cheaper. Models get better. Biological and non-biological intelligence move toward integration, not replacement.

Most reactions to Kurzweil fall into two camps. Either the future sounds implausible and exaggerated, or it sounds dystopian and frightening. Both reactions miss the more subtle insight.

The merger is already underway.

We already outsource memory, navigation, scheduling, and retrieval to machines. Our phones are not accessories. They are extensions of cognition. Cloud systems already act as persistent external memory. What we call tools are quietly becoming cognitive infrastructure.

Kurzweil’s real argument is not that implants or AGI will suddenly change what it means to think. It is that thinking itself is becoming distributed. Intelligence no longer lives in one place. It flows across systems.

From that perspective, what I’ve built with the Five Rings OS is not futuristic. It is almost primitive. A text-based, rule-driven thinking layer feels rudimentary compared to neural interfaces or embedded computation. But that is precisely why it matters.

It forces questions that become unavoidable as intelligence scales.

If machines are going to participate in our thinking, under what principles do they operate?

Whose judgment do they reflect?

What constraints shape their output?

The Singularity does not arrive as a moment. It arrives as a pattern of delegation. This system is an early attempt to shape that pattern deliberately.

The Real Failure Mode of AI

Most people believe AI fails because it lacks enough context. In practice, the opposite is usually true. AI fails because it is given too much context, and none of it is weighted.

Raw notes, half-formed thoughts, emotional reactions, contradictory instructions, historical baggage, all of it gets poured into the same input stream. The model has no way to tell what is foundational, what is provisional, and what should be ignored entirely.

When everything is included, nothing stands out. Signal collapses into noise.

This is where hallucinations emerge. Not because the model is broken, but because the human side never did the work of distillation. The system is asked to reason without a map.

The Five Rings OS begins from the opposite assumption. Before collaboration, there must be compression. Principles must be separated from examples. Heuristics must be made explicit. Constraints must be declared.

AI does not need more of you. It needs the right version of you.

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Why an Operating System, Not a Prompt Library

Prompts are transactional. They solve the problem in front of you. An operating system shapes behavior across time.

I did not want better answers in isolated moments. I wanted consistent reasoning. I wanted critique that behaved the same way every time. I wanted positioning to override engagement, and subtraction to be the default move.

That requires externalizing judgment. Not ideas, but the logic that evaluates ideas. Not content, but the standards that decide whether content is worth keeping.

This is why the repository is structured around rules rather than samples. Examples are useful, but they decay quickly. Principles last longer. Heuristics travel across contexts. Constraints protect taste.

What emerges is not automation. It is alignment.

It Was Never About GitHub

GitHub is visible, so people fixate on it. That misses the point.

This system does not depend on GitHub. You could host it locally. You could wire it into another toolchain. You could interface through Cursor or any environment that can load structured text.

GitHub is simply convenient. It offers versioned truth, diffable change, and cloud accessibility. It allows any model with the right connector to access the same thinking substrate.

What matters is not the platform. What matters is the act of externalizing how you think.

Principles. Heuristics. Voice. Critique rules. Operating modes.

GitHub is not the brain. It is the spine.

Collaboration, Not Delegation

Most AI workflows fall into delegation.

Do this for me. Improve this. Make it faster.

That path erodes skill and weakens judgment over time.

The alternative is collaboration. The machine does not decide what matters. It operates inside constraints you define. It helps express, explore, and test ideas without overruling the underlying values.

This is why critique in the system defaults to subtraction. Why positioning beats engagement. Why hooks can be bold, but substance must remain clean.

These are not stylistic preferences. They are encoded decisions.

Model-Agnostic by Design

Models will continue to change. And with all the AI power users I know, we all test and swap them. Interfaces will fragment. Pricing will fluctuate.

If your thinking system is tied to a single provider, you are building on sand.

By externalizing judgment, the system becomes portable. Models become interchangeable inference engines. The thinking layer remains stable.

The goal is not to trust AI more. It is to trust your system more. This is what the Earth ring is about.

Does This System Compound

Not in the way people usually mean.

The OS does not have autonomous memory. It does not evolve on its own. Compounding happens through deliberate refinement. You adjust principles. You sharpen heuristics. You remove noise.

The machine accelerates the application. The human retains authorship.

This balance matters. It keeps agency intact while still benefiting from scale.

A Different Kind of Second Brain

This is not a vault for ideas or a personal knowledge management system. It does not exist to remember everything.

It exists to think consistently.

In that sense, it functions as a second brain. Not because it stores thoughts, but because it enacts judgment. It brainstorms within your values. It critiques within your standards. It helps you reason without drifting.

The Quiet Singularity

Most people will experience the AI future as churn. New models, new tools, constant resets.

A smaller group will experience continuity. Their thinking will persist across systems. Their judgment will compound. Their collaboration with machines will feel less like prompting and more like extension.

The gap will not be loud. It will not announce itself. It will widen quietly.

Human judgment does not disappear. It gets encoded.

Sources and References

• Ray Kurzweil, The Singularity Is Nearer (2024)

• Ray Kurzweil, The Singularity Is Near (2005)

• Andy Clark, Supersizing the Mind

• Douglas Engelbart, Augmenting Human Intellect

• J.C.R. Licklider, Man-Computer Symbiosis

Part 2 will focus on how to build your own AI collaboration OS, adapted to how you think and work. Subscribe to get part 2.

Build your foundation. Sharpen your systems. Execute with precision. Brand Runner brings you creative productivity frameworks and brand strategy insights rooted in timeless principles. Subscribe for the dojo work nobody sees but everyone feels

If you spend your day on LinkedIn or X, you likely feel like the last person on Earth to automate your life. You see “vibe coding” demos, agents running entire departments, and “prompt engineers” claiming six-figure salaries. The noise is deafening. It creates a sense of panic—a feeling that the ship has already sailed and you’re standing on the dock with an empty suitcase.

But the data tells a different story. A quieter, much more interesting story.

According to the Microsoft AI Economy Institute’s 2025 Global AI Diffusion Report, global adoption of generative AI only reached 16.3% by the end of last year. In plain English:

84% of the planet has never even typed a prompt.

We aren’t in the “mass adoption” phase. We are still in the Perspective phase.

If you are reading this, you are not late. You are absurdly early. And in a world moving this fast, being early is the only moat that matters—provided you know how to act like it.

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Earth: Build the System, Not Just the Prompt

Most people view AI as a magic wand. They “try it once,” get a mediocre result, and join the 84% who walk away. They treat AI as a tactical tool rather than a foundational shift.

In the Five Rings framework, Earth represents your foundations: your positioning, your systems, and your discipline.

The 16% who are using AI today are mostly just “messing around”. They have no system. They prompt with chaos and receive chaos in return. But systems create freedom. The real advantage doesn’t come from having the best prompt; it comes from building the system that makes any AI output repeatable and high-quality.

Stop looking for the “perfect” model. Start building the internal infrastructure—the documentation, the data hygiene, and the decision-making rubrics—that allows AI to actually do the work. Tools don’t create advantage. Principles do.

Water: Buy Back Your Judgment

There is a massive psychological gap between “using” AI and “investing” in it.

As of early 2026, while hundreds of millions use free versions of tools like ChatGPT, only an estimated 1% of the global population actually pays for a subscription. OpenAI’s paid subscriber base for ChatGPT Plus and Enterprise tiers is roughly 35 to 60 million people worldwide.

Why does this matter? Because the 1% aren’t just paying for “faster” text. They are paying for judgment under speed.

This is the lens of Water. Adaptation requires flow. When you pay for high-tier models, you are removing the “cost of bad thinking” faster. You are training your own judgment by interacting with the sharpest edge of the technology. While the rest of the world is waiting for AI to become “perfect” and free, the 1% are using it to sharpen their own strategic intuition and make moves.

Don’t just use AI to save time. Use it to expand your capacity for high-stakes decision-making.

Fire: Strike While the Scrolls are Loading

Perhaps the most telling statistic is the “Developer’s Gap.”

The term “vibe coding”—building entire applications through natural language without touching the underlying code—became the ultimate flex in 2025. Yet, according to the Stack Overflow 2025 Developer Survey, nearly 72% of professional developers said vibe coding is not part of their professional work.

While the majority of the world’s technical talent is over-analyzing the “how” and worrying about “perfect architecture,” a tiny 0.1% of the population is simply shipping.

This is Fire🔥. A decisive strike.

In a shifting market, motion is not mastery, but principled speed is. If you are one of the few people actually building, testing, and shipping “vibe-coded” projects right now, you aren’t just a hobbyist. You are an outlier. You are striking while the “scrolls are still loading”—acting while the incumbents are still debating the ethics of the change.

Void: The Bottleneck is Alignment, Not Intelligence

We are living through a period of strategic compression. AI compresses time, but it does not compress effort.

The final lens, Void, is about mastery and vision. It’s about knowing what you stand for—and what you refuse to do.

The biggest mistake people make when they realize they are “early” is to try and do everything. They automate their email, their social media, their coding, and their creative work all at once. The result? Automation without clarity just scales noise. The bottleneck in a world of infinite intelligence isn’t the AI’s IQ. It’s your alignment.

If you don’t have a clear vision of what you are building, AI will just help you fail faster. Stillness is not inaction; it is strategic compression. Before you scale your output, scale your clarity. Subtract until it sings. Then sharpen.

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The Reality Check

The world is still standing on the sidelines.

• 84% are watching.

• 16% are playing.

• 1% are investing.

• 0.1% are building.

The “AI Revolution” hasn’t even hit its stride yet. The infrastructure is still being laid. The rules are still being written. If you feel like you’ve missed the boat, look at the numbers again.

You are early.

Stop performing for the algorithm. Stop chasing the latest “hack.” Build your foundation. Invest in your judgment. Strike with precision.

The future doesn’t belong to the loudest room. It belongs to the few who are actually doing the work while everyone else is still arguing about the “vibes.”

F.

Sources & Data Points

• Microsoft AI Economy Institute: Global AI Diffusion Report 2025 (H2) – Confirms 16.3% global adoption.

• Stack Overflow: 2025 Developer Survey – Data on the 72% developer gap and vibe coding.

• OpenAI Usage Data (Early 2026): Times of India Tech / OpenAI Restructuring Report – Estimates of 35M+ paid subscribers against ~900M weekly users.

• DemandSage / Backlinko: ChatGPT User Statistics Feb 2026 – Market share and paid user estimates.

Other articles you might be interested in

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Hi,

We’ve covered Earth—your systems and foundations. We explored Water—adaptation and timing. Today, we’re going into Fire, the ring everyone sees but most people misunderstand.

Think of the boldest idea you’ve shelved because it “felt risky”. That’s your Fire moment.

Fire isn’t about posting more. It’s not about “always on” content or hustling harder. Fire is about the decisive strike—the bold campaign that makes people talk, remember, and act.

It’s February 2022. You’re watching the Super Bowl. A bouncing QR code fills the screen. No voiceover. No celebrities. No explanation. No brand mentioned Just a floating, color-shifting square for 60 seconds.

Within minutes, Coinbase’s platform crashes. Over 20 million hits in one minute. App downloads spike from 186th to 2nd on the App Store. The internet explodes.

That’s Fire.

Measured risk doesn’t mean playing it safe. It means planning for where it might break, and deciding the risk is worth taking anyway.

This is the Fire Ring. Not reckless. Not guesswork. Bold, decisive strikes backed by preparation.

What Fire Actually Is

Fire is campaigns that make people talk.

Not content. Not posts. Campaigns.

Could be: A Super Bowl QR code. An OOH takeover. A 360 launch with video, influencers, and PR. A guerrilla stunt with $500 and a concept that breaks the internet.

It’s not about budget—it’s about boldness.

The idea matters more than the money.

Chili’s opened a fake “Fast Food Financing” shop next to a Manhattan McDonald’s in April 2025, lampooning inflation and celebrating their new Big QP burger. Three-hour lines. 6 billion impressions. Cost? A fraction of a Super Bowl ad.

Nike lit up the “D” in the Hollywood sign after the Dodgers won the World Series. Turned a city landmark into a victory billboard. Millions saw it. The brand owned the cultural moment.

Liquid Death partnered with Yeti to release a $68,000 casket cooler. Absurd? Yes. On-brand? Absolutely. Did people talk? For weeks.

What they share: Boldness of concept. Total commitment. Willingness to push boundaries.

Fire is the moment you stop planning and start attacking.

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The Dojo Work Comes First

Here’s what nobody tells you about bold campaigns: you can’t attack without preparation.

Fire without foundation is just chaos.

Before Chili’s opened a fake financing shop, they aligned it with their brand positioning and value message. Before Nike lit up the Hollywood sign, they confirmed it served their “Just Do It” ethos.

The vision must connect: brand → company goals → campaign goal.

You can’t launch Fire just to make noise. The strike has to serve your positioning.

Your Earth work (systems and process) tells you how to execute without falling apart.

Your Water work (timing and cultural awareness) tells you when the window is open.

Your Wind work (positioning and taste) tells you which battles to fight.

Your Void work (strategy and instinct) tells you this is the moment.

When all four align, Fire doesn’t feel reckless. It feels inevitable.

The Measured Risk

Let’s be clear: bold means some people won’t get it. That’s fine.

Bold means you might push your brand boundaries. That’s the point.

Bold means something might break. You’re ready for that.

But measured means you’ve done the work to know it’s the right move.

When I produced work for a Super Bowl campaign, we had a dev team on standby the day of broadcast. We knew traffic could spike. We knew the platform might strain. We planned for failure modes and had people ready to respond in real time.

That’s the difference between bold and reckless.

Measured risk = willing to take the risk, but prepared for where it breaks.

Coinbase’s campaign, as simple as it might looked, it generated more awareness and signups than any traditional ad could have.

Their platform crashing became part of the story. “So popular it broke the internet” is better PR than “performed as expected.”

Bold vs. Gimmicky

Not every risky move is worth taking.

Taste is the filter between bold and desperate.

Bold serves your positioning—even if it stretches it. Gimmicky chases attention without purpose.

How to tell the difference:

Does this move your brand forward, or just get eyeballs?

Liquid Death’s casket cooler is absurd, but it’s on-brand absurdity. The brand built its identity on irreverent, boundary-pushing stunts. The casket cooler reinforces that positioning.

Contrast that with brands that jump on trends they don’t understand. The forced meme. The awkward TikTok dance. The “How do you do, fellow kids?” energy.

Fire without taste is noise. Fire with taste is cultural impact.

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The Anatomy of a Fire Strike

Let’s break down how bold campaigns actually work.

Before the Strike

1. Crystal clear brief

What does winning look like? Not “engagement” or “awareness.” Be specific.

Coinbase: Get people to sign up for accounts. Clear goal. Clear metric.

2. Know the risk you’re taking

What might break? Who might you lose? Is that acceptable?

Document the downside. If you’re not willing to accept it, don’t launch.

3. Total alignment

Brand positioning. Company goals. Campaign goal. Creative execution.

If any of these are misaligned, don’t strike yet.

During the Strike

4. Total commitment—no hedging

Once you launch, you’re all in. No “let’s test this” energy. No apologizing mid-campaign.

Fire only works when you commit fully. This is the concept of Zanshin used in Kendo.

5. Fast feedback loops

Monitor in real time. If something breaks, adapt execution (not strategy).

Coinbase’s team throttled traffic when the platform strained. They didn’t pull the campaign. They adapted the infrastructure.

6. Multi-channel or single-channel—doesn’t matter

Some Fire campaigns are 360 plays: OOH, video, digital, influencer, PR.

Others are single-channel precision: one QR code, one stunt, one moment.

What matters is decisiveness. One clear message. One goal.

After the Strike

7. Measure impact, not just metrics

Did people talk? Did it move the needle culturally? Did it shift perception?

Clicks matter, but cultural echoes matter more.

8. Document and move on

What worked? What broke? What would you do differently?

This is Earth work again—compound the learning so the next strike is sharper.

9. Strategic recovery

You can’t stay in Fire mode constantly. Bold campaigns burn energy—yours and your audience’s.

Rest between strikes. Build between attacks.

Fire at Any Budget

Here’s the truth most marketers need to hear: Fire isn’t reserved for brands with Super Bowl budgets.

Big budget Fire:

Coinbase spent $14 million on a 60-second ad. Nike lit up the Hollywood sign. Liquid Death partnered with Yeti on a $68,000 cooler.

These are bold because of concept, not just spend.

Scrappy Fire:

Chili’s fake financing shop cost a fraction of a traditional campaign and generated 6 billion impressions.

IKEA’s 2025 campaign slid into Canadian customers’ DMs at 2 a.m. with “u up?” to promote mattresses. Cheeky. Unexpected. Generated massive buzz.

Duolingo “killed” its owl mascot in a staged TikTok drama. 120 million views. Cost? Basically zero.

What they share:

Boldness of idea. Total commitment. Willingness to look stupid if it doesn’t land.

Fire for startups and small businesses isn’t about matching big-brand budgets. It’s about thinking outside the box with concepts that punch above your weight.

The guerrilla mindset: constraints breed creativity.

When to Strike (and When Not To)

Not every moment deserves Fire.

Fire without the right setup is just noise.

How to know when to strike:

1. Your positioning supports it

The campaign should feel like an extension of your brand, not a departure.

If you have to explain why this is “on brand,” it’s probably not.

2. The timing is right

Is the culture ready for this? Is your audience primed?

Water work (timing and adaptation) tells you when the window is open.

3. You’ve done the dojo work

Is your infrastructure ready to handle success?

Can your team execute without panic?

Do you have contingency plans for failure modes?

4. The instinct says “now”

Sometimes, all the data says go but your gut says wait. Trust that.

Sometimes, the data is inconclusive but your instinct says strike. Trust that too.

This is Void—where strategy meets intuition.

When NOT to strike:

• Just because a competitor did something bold

• Because you’re bored and want to “shake things up”

• Because the CEO saw a cool campaign and wants one too

• Because you haven’t launched anything in a while

Fire for the sake of Fire is noise.

Strategic patience is Fire discipline.

Building Your Fire Capacity

You don’t have to launch a Super Bowl campaign tomorrow. Start building the capacity for bold moves.

Step 1: Know what deserves big swings

Not every product launch needs Fire energy.

Your positioning determines which battles matter.

Ask: Does this moment deserve a decisive strike, or is steady execution enough?

Step 2: Build the brief that demands boldness

Force clarity upfront.

Questions your brief must answer:

• What does winning look like? (Be specific.)

• What are we willing to risk? (Budget, reputation, time.)

• Who might we lose? (And is that acceptable?)

• What’s the one thing this must accomplish?

Step 3: Plan for where it might break

Document the failure modes.

• Traffic spike crashes the platform → dev team on standby

• Controversial concept offends some → response plan ready

• Competitor reacts aggressively → have your counter-narrative prepared

Measured risk means being ready for the downside.

Step 4: Execute with total conviction

Once you launch, no hedging.

No “let’s see how it goes” energy.

No apologizing mid-campaign unless you truly missed.

Strike as if this is your defining moment.

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Managing Fire Without Burning Out

Here’s the hard truth: you can’t run Fire mode constantly.

Bold campaigns require energy—creative energy, strategic energy, team energy.

Fire that burns continuously becomes background noise.

Strategic recovery between strikes:

Build (Earth), adapt (Water), observe (Wind), and reflect (Void).

Then strike again.

The rhythm of attack and recovery is what makes Fire sustainable.

Musashi didn’t fight 60 duels back-to-back. He prepared. He trained. He waited for the right moment. Then he struck decisively.

Your marketing should work the same way.

What’s Next

Fire is what people see. But it only works when the other rings are aligned.

Earth gives you the systems to execute without chaos.

Water gives you the timing to strike when the window opens.

Wind gives you the positioning to know which battles matter.

Void gives you the instinct to feel when the moment is right.

Fire is where they all converge.

Next up: Wind Ring—reading the competitive landscape, understanding cultural shifts, and knowing which battles to fight.

But before that: what’s the bold move you’ve been circling but haven’t pulled the trigger on?

Reply and tell me. That’s your Fire work.

— Fabien

P.S. — Share this with someone who needs permission to be bold. Fire isn’t reckless when it’s backed by preparation.

References:

• Coinbase Super Bowl 2022 QR Code Campaign (CNN Business, The Drum)

• Chili’s Fast Food Financing Guerrilla Campaign 2025 (StoryChief)

• Nike Hollywood Sign Dodgers Campaign (BrandXR)

• Liquid Death x Yeti Casket Cooler (HAVEN Creative)

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Every team says they want better creative.

They want sharper ideas. Faster cycles. Fewer revisions. Work that actually lands.

And yet, the moment a project kicks off, there’s a familiar pressure to move.
Start designing. Start writing. Start shipping.

Briefing feels like friction. Creation feels like momentum.

So teams jump straight into execution. Often with a document that looks complete, sounds confident, and is quietly full of holes.

Halfway through production, it happens.

Someone asks a “small” question.
A stakeholder reacts oddly.
The work feels… off.

And that’s when you realize the worst thing possible:
you’re solving the wrong problem.

Now you’re three steps in, with sunk time, bruised trust, and creative energy already spent, walking backward to a conversation that should have happened at the start.

I’ve lived this more times than I care to admit.
And it’s one of the most expensive patterns in modern creative work.

The Rush to Create (and the Work We Skip)

Most teams don’t skip briefing because they’re careless.

They skip it because:

• Speed is rewarded

• Output is visible

• Thinking is invisible

Doing the quiet, unglamorous work of alignment doesn’t feel like progress.
It feels like delay.

In martial arts, there’s a word for this kind of preparation—the dojo work.
The drills, the stance, the fundamentals you don’t see in the fight.

Skip it, and the cost doesn’t disappear.
It just shows up later, under pressure.

Creative work is no different.

When teams rush past the brief, they’re not saving time.
They’re deferring thinking and pushing it downstream, where it’s far more expensive to fix.

Why Most Briefs Fail (Even When Everyone Is Smart)

Here’s the uncomfortable truth:
Most creative briefs don’t fail because people are lazy or untalented.

They fail because they’re trying to do too many things at once.

Common patterns I see across companies, agencies, and founders:

• Context overload, decision drought
  Lots of background. Very few clear calls.

• Inputs masquerading as strategy
  “Here’s what we like” instead of “Here’s what we’re choosing.”

• Vibes instead of constraints
  Aspirational language with no teeth.

• Hidden contradictions
  “Bold but safe.”
  “Premium but mass.”
  Everyone senses the tension. No one names it.

On paper, the brief looks fine.
In reality, it’s a liability document.

It passes ambiguity forward and asks creative teams to resolve it under deadline—through taste, guesswork, and iteration.

That’s not collaboration.
That’s outsourcing decisions.

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The Reframe: A Brief Is a Decision Document

A useful creative brief isn’t a form.

It’s a set of committed decisions.

It answers questions like:

• What problem are we actually solving?

• Who are we choosing to ignore?

• What tradeoffs are we willing to accept?

• What does success look like this time?

When those decisions are made upstream, creative work accelerates.
When they’re not, creative work becomes a negotiation.

This is where many teams get stuck:
They think briefs are about alignment.
In reality, briefs are about commitment.

Alignment is the outcome.
Decision-making is the work.

The Operator’s Pain Point No One Talks About

If you’ve led creative teams long enough, you know this feeling:

You’re not frustrated because the work is bad.
You’re frustrated because it could have been great—if only the brief had been clearer.

The real cost isn’t revisions.
It’s:

• Lost momentum

• Eroded trust

• Teams feeling like they “missed” without knowing why

And worst of all, the post-mortem always sounds the same:

“We should’ve clarified this earlier.”

Everyone agrees.
Nothing changes.

Why I Built Briefchecker

Briefchecker (it’s 100% free) didn’t start as a product idea.

It started as a repeated pattern across projects, teams, and roles:

• Smart people

• Good intentions

• The same avoidable breakdowns

What bothered me wasn’t that briefs were imperfect.
It was that their weaknesses were predictable.

Missing decisions.
Unresolved tensions.
Contradictions hiding in plain sight.

And yet, catching them depended on experience, seniority, or someone brave enough to slow things down.

That felt wrong.

Good briefing shouldn’t require:

• Being the loudest person in the room

• Having “great instincts”

• Learning the hard way, repeatedly

So the question became:

What if we could pressure-test a brief before creative energy gets spent?

Not to rewrite it.
Not to generate ideas.
But to surface what’s unclear—early, calmly, and without ego.

In the end, any creative effort that is produced ( wether video, image, blog post etc…) should be ultimately cross-checked with the original brief to see if it is fulfilling it.

What Briefchecker Actually Does

Try Briefchecker now for free

At a high level, Briefchecker acts like a second set of experienced eyes.

You run a brief through it, and it looks for:

• Missing strategic decisions

• Conflicting signals

• Overloaded goals

• Vague success criteria

Instead of suggesting “better copy” or “cooler ideas,” it focuses on clarity quality.

The output isn’t inspiration.
It’s friction—in the right place.

A scoring system forces the brief to earn its confidence.
Not based on polish, but on decisiveness.

It doesn’t tell you what to choose.
It makes it harder to avoid choosing.

That distinction matters.

A Note on How It’s Built (and Why That Matters)

A quick word on the tech—because the choices here are intentional.

Briefchecker is powered by Mistral AI, chosen for control, efficiency, and alignment with how we wanted the system to think—not hype.

There’s no data retention.
Your briefs aren’t stored, or reused. Trust comes before growth tricks.

And the scoring system isn’t there to gamify the process.
It’s there to do one thing: surface discomfort early.

Every technical decision reflects a belief:

• This tool shouldn’t replace judgment

• It shouldn’t smooth over tension

• It should make thinking visible

If the brief passes easily, great.
If it doesn’t, that’s the point.

Who This Is (and Isn’t) For

Briefchecker isn’t for teams looking to “move faster” by thinking less.

It’s not for people who want AI to do the work for them.

It is for:

• Creative leaders tired of mid-project course corrections

• Operators who care about clean handoffs

• Founders who want better output without burning teams

If you believe creative work is a system—not just a spark—this will feel familiar.

One Simple Invitation

If this post sounds uncomfortably familiar, try this:

Take one real brief you’re about to send into production.
Run it through Briefchecker.

Not to validate it.
Not to perfect it.

Just to see what questions surface before you spend creative energy.

Because fixing a brief at the start doesn’t slow teams down.

It’s how you stop walking backward halfway through the work.

Thanks for reading,

Fabien.

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Check out the podcast here

Build your foundation. Sharpen your systems. Execute with precision. Brand Runner brings you creative productivity frameworks and brand strategy insights rooted in timeless principles. Subscribe for the dojo work nobody sees but everyone feels.

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This month, I got myself a set of Apple EarPods Pro 3. I saw it offered a hearing test. I decided to take it “just for fun”.

The result was unremarkable in the way that matters most:
“Little to no loss.”
Actually, slightly better than average.

But the insight wasn’t medical.
It was operational.

Because once you understand how you perceive signal, you start to understand why certain environments, workflows, and leadership styles either work for you… or quietly drain you.

Signal Is Not Neutral

This lives squarely in Ring One: Earth.

Before tools.
Before tactics.
Before optimization.

You need to understand the system you’re operating with. And your first system is your body. I talked before about chronotypes and how to tweak your own calendar based on your on rhythm.

My hearing profile showed strong sensitivity in the ranges that matter for:

• speech

• tone

• subtle environmental cues

Not superhero hearing.
Just high signal resolution.

Cognitive sociology has a name for this: sensory gating. The brain’s ability to filter relevant input from background noise. Research shows that people vary significantly in how much raw sensory information they take in before filtering even begins

Translation:
Some people are wired to notice more before conscious effort kicks in.

Dog Hearing vs Wolf Hearing

Dogs hear more frequencies than humans.
Ultrasonic range. Dog whistles. No debate.

But range isn’t the point.

Dogs hear more.
Wolves hear what matters.

Wolves evolved for:

• directional awareness

• contextual sound

• early threat detection

That distinction maps cleanly to modern work.

In complex systems, teams, markets, creative orgs, success rarely comes from hearing everything. It comes from detecting weak signals early.

Sociologist Karl Weick’s work on sensemaking shows that people who detect small anomalies early often prevent large failures later. Not because they’re smarter, but because they’re more attuned to subtle cues.

That’s wolf hearing.

The Hidden Cost of High Signal Sensitivity

There’s a tradeoff no one talks about.

If your sensory system is tuned:

• noisy environments fatigue you faster

• chaotic inputs degrade focus disproportionately

• constant context-switching isn’t neutral — it’s expensive

Neuroscience backs this up.
Studies on cognitive load show that high-sensitivity individuals expend more neural energy suppressing irrelevant input. That suppression cost accumulates.

This isn’t fragility.
It’s bandwidth management.

Which leads directly to strategy.

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Protect Before You Amplify

Most productivity advice assumes:

“More input + better tools = better output.”

That’s backwards for people with high signal sensitivity.

In Five Rings terms:

• Earth: Know your sensory configuration

• Water: Adapt the environment instead of fighting it

• Fire: Act decisively — but selectively

For some people, leverage doesn’t come from amplification.
It comes from reduction.

Fewer meetings.
Cleaner audio ( I upped my own home setup with a good mic so there’s much less frictions when communicating).
Intentional silence. (give the space for who you are talking to can really take in what you’re saying).
Tighter feedback loops.

Research in attention economics consistently shows that reducing irrelevant stimuli improves decision quality more than adding information (Kahneman, limited attention framework).

Less noise → better judgment.

Why This Matters for Creative Leaders

Creative leadership isn’t about having the loudest ideas.
It’s about timing, tone, and trajectory.

People with tuned sensory systems often excel at:

• sensing misalignment before it’s visible

• detecting emotional undercurrents in teams

• knowing when something is “off” even if metrics look fine

But only if they design around their configuration.

When they don’t, they burn out, not from workload, but from signal overload.

The Actual Lesson

This post isn’t about hearing.

Don’t optimize blindly.
Calibrate first.

Before you add tools, AI, dashboards, or workflows, ask:

• What signals do I naturally detect well?

• What noise drains me disproportionately?

• Where should I protect clarity instead of chasing scale?

That’s not self-indulgence.
That’s operational intelligence.

Final Verdict

I don’t want dog ears.

I’ll take wolf ears:

• selective

• contextual

• tuned for meaning, not volume

Because in a world obsessed with more —
clarity is the real advantage.

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Hi all.

Today I am stepping away of my usual creative productivity posts to talk about a road bump I hit just before the holidays.

If you are like me, by now you have figured out a way to leverage AI and LLMs to optimise your work day. I was looking something that was exceptionally good at reasoning, coding, and writing. I also needed something that could help me vibe code a few tools, help me with my writing, challenge my thinking, and optimise what I’d throw at it. Different LLMs can achieved different things and have their strength and weaknesses. But eventually I settled for Claude.

So I built a complex workflow, and set up Claude in a way it could “learn me”. I used customized pre-instructions in the preference, set up skills, “projects” and custom instructions and files per project.

MCP power up

I am big proponent of the PARA system. It is a way to organise notes and build a second brain.

I talk about it here:

I had been using PARA system in Apple Notes for a while now. But Apple Notes is a walled garden: can’t bulk export without tap-dancing through third-party apps, and compromising formatting and some of the content.

But then realized I could use Claude and MCP to connect to Notion. This is way I could leverage Claude as an AI-powered search assistant through my second brain.In essence, I could say something like “Pull all notes relating to my five rings framework”. Or “I remember capturing a quote about XYZ, give me the link to the entry”. I started implementing and transferring my notes to Notion. This greatly verified my theory of the Earth ring: systems create freedom.

I also created various “Projects” for different use. Such as “Content studio” to brainstorm some ideas, “video and podcast studio” to adapt some ideas into short for content, all custom prompted with Five Rings prism, and channel best practices. I also have more personal threads discussions about tax optimisations, travel planning etc..

I also have a project to help me debug and keep empirical and historical knowledge on my Creative TLDR app, and help me debug and improve. It is basically a daily whatsapp delivery system that scans top-tier marketing and advertising publications, and send a daily TLDR message designed for creative marketers, creative directors and producers.

This was a short summary of the time and effort invested in order to set up Claude so it works effectively for me.

In short, I was finally starting to understand how to leverage LLMs to do more for me so I could focus on what is important.

In this article, I talk about the immediate action that should be taken should this happen to you, and the appeal process.

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My AI bubble being bursted

Suddenly on December 16th, my momentum was cut short when I tried to login. To my great surprise, I could not.

Got this message, with no justification.

No email notice.

No warning.

I had no clue why I had received such a message in the first place. I didn’t knowingly violate any terms, but it’s possible an automated filter algorithm (more on this below) interpreted one of my prompts in a way that triggered a suspension.

In a time where the use of LLMs are propagating so quickly in our daily professional life, a lot of the work force, better handoffs, due diligence are needed. I am just a guy using it to work on a few vibe coding projects, strategic brainstorms, experimentation and content. But you can imagine how certain businesses could be completely paralyzed if something like this would happen to them. Especially when you see more and more businesses are developing their own internal tool this way instead of buying third parties.

I realised:

1. Anthropic and most LLMs scan see everything you do.

2. Any LLMs can cut you off one day to the next without warning, and your operations can be at a standstill instantly.

3. Only true privacy is if you run LLM locally via Ollama and Mistral for instance. Or maybe Lumo by Proton, but not quite comparable to the other big LLMs yet.

If you are interested on AI, regulations and ethics, I recommend checking Luiza’s phenomenal Substack here.

Luiza's Newsletter

AI is transforming the world as we know it, and we must make sure that pro-human policies, rules, and rights remain at the forefront. Join 88,000+ subscribers who never miss my essays.

By Luiza Jarovsky, PhD

I am writing this article so you can be better informed and take the necessary measures and choices.

Immediate risk management and mitigation

First thing I did was to take the consumer terms and usage policy mentioned in the suspension message and fed them back to ChatGPT. There, I told it, just got this message trying to logging in my Claude account. Was told I was suspended, but have no idea what I did wrong. From my recollection, I don’t remember doing anything shady. Read the policies attached and from what you know about me, try to help me figure out what I could have done to trigger this. I also want to know what is the appeal process, time response etc... Help me go through the process.

ChatGPT recommended to go through the appeal and request immediately a copy of all my data and convo threads, leveraging GDPR and privacy laws.

After a pretty healthy ping pong conversation between myself and Chatty, here are my findings.

Most LLMs use an automatic filtering system

To prevent shady stuff to happen, all LLMs have what they call an automatic filtering system that basically scan everything that is prompted. Think if someone says something like “I want to build a bomb at home” or, tell me how I can plan a terror attack”. These are legitimate concerns for AI being used for wrong (especially with a company like Anthrophic positioning itself for ethical AI).

Large language model providers use automatic filtering systems (“guardrails”) to reduce harmful or abusive use before responses ever reach users. At a high level, this works by screening both inputs (what users ask) and outputs (what the model tries to say) using a mix of rule-based policies and AI classifiers. These systems are designed to detect things like hate speech, self-harm encouragement, illegal instructions, sexual exploitation, and attempts to bypass safeguards (“jailbreaks”). If content crosses defined risk thresholds, it may be blocked, rewritten, refused, or escalated for review. Importantly, these filters are layered on top of the base model and are continuously updated as new misuse patterns appear.

Different companies implement this idea in slightly different ways, but the principle is the same. Anthropic (Claude) emphasizes “Constitutional AI,” where models are trained and evaluated against explicit safety principles and paired with automated classifiers that enforce them at runtime (including blocking repeated harmful attempts).

Google’s Gemini models use configurable safety filters in their APIs that automatically block or limit unsafe responses by category and severity, especially in production applications.

Across all three, the key idea is that LLMs are not deployed “raw”, They’re wrapped in automated filtering systems plus policies and human oversight to reduce shady or harmful use, even though no system is perfect.

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Once account suspension is triggered, an appeal is possible, pushed to a real human

You fill a google form ( which is kind of strange for a company that advocates privacy, but ok). You explain why you think your account should be reinstated. In my case, I came down to the conclusion (because Anthropic never confirmed the reason), that what triggered the suspension was one of my experiment. I was trying to develop a very basic extension that would tell me when an email I sent would be opened. That’s it. Since there are already many existing options such as Mail Suite, Mail Butler, and most CRM suites using something more, I didn’t see the harm. Just, most of these solutions work on gmail only and I’m not using gmail.

I believe the filtering system interpreted it as a “hacking”/cybersecurity flag. In my appeal, I stated that if they checked the prompt history ( even suggested that I’d send copy from data request once received), they would see that I stated in the prompt “I only want to know if the mail is open”. That’s it. No fingerprinting, no location logging, no profiling whatsoever. I also stated that per the prompt “this was for personal use only”. We (Claude and I) also discussed integrating a disclaimer inside the body of mail to be transparent.

I submitted the appeal and data request on Dec 16th, followed several time since. Their AI bot replied to me ( mail trackers included).

🚨Warning🚨: do not use same email address for API use

I created an app called Ideas Go Here that allows to record ideas on the fly and automatically summarized them and plug them in your favorite PM tool. It was powered by Anthropic’s Haiku.

I did not get any notice for that one either, but turns out if you are using the same email address for the API of the same company, (let’s say Marthy@McFly.com for both your Claude ai and your console.anthropic.com (which are not related), if your account gets suspended your API access also get suspended as well, even though what you are doing on the API might have nothing to do with what you prompted in the LLM and triggered the suspension in the first place. Here I did not get a notice either, my app just stopped working, and while debugging realised what happened.

Wasn’t much but didn’t get refund for API tokens funds still avail either…

Quick fix: immediately generated a new API key and switch the API to Mistral AI. I adjusted the edge function to reflect as well.

Immediate request for all data/conversation/logs leveraging GDPR regulations.

First thing I did before the appeal was to request through their privacy email address, a copy of all my data. My hope was to not have to retrain another LLM from scratch, and use some of the pre prompts, reference guides I gave etc… to fasten the process.

Where I stand today

Got a negative response on Dec 30th, without explanation nor acknowledgement of my explanation (but delivered yet with another different mail tracker).

The copy of my data request is still in process. They (there AI bot) asked for additional information on Dec 31st then again on January 3rd.

Lesson learnt for next time

1. It’s not because you are “AI tube-testing” that you are not at risk of being shut down. In privacy tech, it is known that nobody really read the use and privacy terms. But when you are pushing the limit a bit of something new like LLMs, you should ask your LLM to scan the privacy/use terms and ask if what you are trying to build goes against the terms and could trigger the automatic filtering. Even if just at exploration phase.

2. Don’t expect customer support to be immediate. None whatsoever after 10 days after multiple follow up. Granted we entered EOY holidays, but I expect more from a company at 183 billion dollars evaluation. I am just one guy. I am sure they have guardrails for enterprise accounts. But for smaller business and solopreneurs that can have multiple automations, operations, sales and what not, this can be devastating.

3. Use different email addresses for log in between LLMs and their corresponding API. So if you get kicked out of Claude/ChatGPT, you don’t lose access and functionalities to Anthropic/OpenAI models of your apps.

4. Unknowingly, I had started the following prior to the suspension, and I recommend it. I started to record all my main pre prompts into a notion board. Such as my main brand guidelines, social templates, custom prompting about myself what trying to accomplish etc… This way you already have a base should you reset. I would even go further, and record all reference files/custom prompt project based ( if important/on-going)

   

5. Don’t do anything illegal😅

How I feel about this

Obviously I am a little bummed out as I got to the point I felt I built a pretty efficient LLM partner but also through a few custom prompt challenged my thinking. But this was a pretty good learning curve. I think I know what I need to do to build another one.

I know Anthropic’s positioning is stricter on the ethical and privacy side, but I feel here it was an overkill. Also based on the various FinAI replies, I am not sure a human actually reviewed more precisely my appeal, yet still took their sweet time. I showed I was more than willing to collaborate with very valid reasons (did I mention that tracker also never worked?).

Say what I do but don’t do what I do

I also find a little bit hypocritical that my account get suspended for one simple email tracker, that only tracks if mail is open, while Anthropic obviously use a series of mail trackers tracking open rates, fingerprinting, IP and what not. I understand I might have agreed by accepting their terms, but again, I did disclaim in the prompt the exact use and that the receiver would be disclaimed as well.

They should implement a better warning system. Like an official mail or something. ChatGPT mentioned sometimes the warning is in the reply from the LLM while answering a prompt, but I don’t remember seeing any.

Would be good to get a confirmation of why the trigger happened. Because maybe I am all wrong, and it is not this mail tracker at all, Maybe it is because I prompted once that my cousin is gluten intolerant (not same as celiac), and wanted to check if maybe I can just use flour without telling her, because that’s all I had in my kitchen, God knows?

“Do it but, better”

So here’s the takeaway: a ban or suspension isn’t a death sentence, it’s a reset opportunity. As much time, energy, and emotional investment you put into your favorite LLM, remember: what went wrong isn’t the end of your creative workflow, it’s a signal to rethink, refine, and rebuild smarter.

In advertising, as in AI tools, the mindset that matters isn’t attachment, it’s adaptability. You can always re-shape your stack, improve your prompts, and choose models that fit your needs better than before.

Drop your favorite LLM alternatives and rebuild strategies in the comments. Let’s treat this not as loss, but as a launchpad.

Thanks for reading, and here’s to the next iteration.

F.

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In this episode of Brand Runner, Fabien discusses the evolving landscape of marketing, focusing on the integration of AI as the new operating system. He explores six significant shifts in the industry, including the rise of AI in marketing, the transformation of search into answer engines, and the emergence of every company as a media company. Fabien also delves into the financial infrastructure of the creator economy and the importance of human elements in an AI-driven world. The episode concludes with actionable insights on how brands can adapt to these changes.

Keywords

AI, marketing, brand strategy, creator economy, answer engines, media companies, human elements, digital transformation, marketing shifts, AI integration

Takeaways

• AI is becoming the operating system of marketing.

• Search is evolving into answer engines.

• Every company is now a media company.

• The creator economy is gaining financial infrastructure.

• Human elements are becoming a luxury in an AI-driven world.

• Brands need to adapt to AI-driven changes.

• AI is transforming discovery and commerce.

• The importance of direct audience relationships is growing.

• Brands must simplify measurements before scaling.

• The shifts in marketing are already underway.

Title Options

• AI: The New Marketing OS

• Transforming Search: The Rise of Answer Engines

• Every Company is a Media Company Now

• The Creator Economy's Financial Revolution

• Human Elements in an AI World

• Adapting to AI-Driven Changes

• AI's Impact on Discovery and Commerce

• Building Direct Audience Relationships

• Simplifying Measurements for Growth

• Navigating Marketing Shifts

Sound bites

AI is the new marketing OS. Search evolves into answer engines. Every company is a media company. Creator economy gains financial infrastructure. Human elements are a luxury now. Adapt to AI-driven changes. AI transforms discovery and commerce. Direct audience relationships matter. Simplify measurements before scaling. Marketing shifts are underway.

Chapters

• 00:00:00 Introduction to Marketing Shifts

• 00:00:00 AI as the New Operating System

• 00:00:00 The Evolution of Search

• 00:00:00 Media Companies Everywhere

• 00:00:01 Financial Infrastructure in the Creator Economy

• 00:00:01 The Luxury of Human Elements

• 00:00:01 Adapting to AI-Driven Changes

Links

• Connect on LinkedIn: Fabien Hameline

• Subscribe to the newsletter: Brand Runner Newsletter

• The app Creative TLDR: Sends a WhatsApp daily and keeps the pulse for you on all things marketing: https://creativetldr.com

Sources links:

Amazon’s AI ads agent and campaign manager – https://www.adweek.com/media/amazon-ai-ads-agent-campaign-manager ↩

WPP launches self-serve AI platform – https://www.adweek.com/agencies/wpp-launches-a-self-serve-version-of-its-ai-platform-to-court-small-biz-dollars ↩

Unilever’s AI beauty marketing assembly line – https://digiday.com/marketing/inside-unilevers-ai-beauty-marketing-assembly-line-and-its-implications-for-agencies ↩

Google AI Overviews reach 2B+ monthly users – https://digiday.com/media/googles-ai-overviews-reach-over-2-billion-monthly-users ↩

ChatGPT Shopping changes ecommerce SEO – https://searchengineland.com/chatgpt-shopping-ecommerce-seo-rules-462865 ↩

Zero-click landscape challenges – https://digiday.com/marketing/how-brands-are-trying-to-optimize-outsmart-ai-answer-engines-across-the-zero-click-landscape ↩

American Express launches ad business – https://www.adweek.com/commerce/american-express-launches-ad-business-in-growing-commerce-media-race ↩

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Introduction

In the last few months, the marketing newsfeed has been wild.

Netflix agreed to swallow Warner Bros. Discovery. Amazon quietly shipped an AI “ads agent” to run campaigns for you. Visa stepped into the creator economy’s money problems. Retailers, banks and streaming platforms all decided they’re ad networks now.

If it feels like the ground is moving under your feet, you’re not imagining it.

Every day, thousands of marketing stories compete for your attention. New campaigns. Platform updatAI launches. Leadership moves. Most of it is noise. But buried in that noise are the real pattern shifts—the tectonic movements that will separate the brands that thrive in 2026 from the ones still optimizing for a world that no longer exists.

This report comes from analyzing 400+ recent stories across brands, platforms, AI, retail media, creators and consumer behavior. The goal wasn’t to recap headlines. It was to answer a harder question:

What actually changed in the last few months that will still matter 12–18 months from now?

The answer isn’t a single trend or buzzword. It’s six interconnected shifts that are quietly rewiring how discovery happens, how media is bought, how creators get paid and what “brand” even means in an AI-saturated world.

Let’s walk through them—then talk about what you should do in Q1.

1. AI Stops Being a Stunt and Becomes the Operating System

The era of “we made an AI ad” press releases is ending. What’s replacing it is something more profound and less flashy: AI is becoming the invisible infrastructure that runs modern marketing.

Amazon launched an AI “ads agent” alongside a redesigned campaign manager, letting advertisers automate optimization decisions that used to require manual intervention.¹ Yahoo is testing six AI agents within its DSP to handle everything from audience targeting to creative rotation.² Publicis debuted “Leona,” an AI engine designed to power production at scale across its network.³ WPP launched a self-serve AI platform specifically to court small business advertising dollars—a market that was previously too expensive to serve.⁴

This isn’t about using AI to generate a single image or write a headline. It’s about AI handling the operational complexity of modern marketing: the bidding, the routing, the personalization, the measurement. Unilever built what it calls an “AI beauty marketing assembly line” for its brands—an in-house system that could fundamentally change its relationship with agencies.⁵

The implications are significant. Stagwell reported that its AI pivot drove Q3 growth even as other revenue streams pulled back.⁶ Publicis noted that its AI-driven approach is winning business without requiring traditional pitch processes.⁷ The holding companies that invested early are now seeing returns.

But there’s a catch. A Gartner report found that despite recognizing AI’s potential impact, most marketing organizations haven’t made the deeper organizational changes required for success.⁸ Knowing AI matters and being structured to use it are two different things.

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What this means for marketers

• Audit your current tech stack for AI-native capabilities—not as add-ons, but as core functionality

• Ask your agency partners: what percentage of media optimization is now AI-driven vs. human-driven?

• Consider whether your org structure (approval chains, creative briefing, media planning) was designed for human speed or machine speed

• Watch for the “AI tax”—platforms will increasingly charge for AI features that used to be free or included

2. When Answer Engines Replace Search Boxes

How AI intermediaries are rewriting discovery and SEO

Google’s AI Overviews now reach over 2 billion monthly users.⁹ ChatGPT launched shopping capabilities that are changing ecommerce SEO rules.¹⁰ Google itself acknowledged that SEM and SEO will need to “coevolve” with search because “SEO is not dead”—which is exactly what you say when people are worried it might be.¹¹

The shift here isn’t subtle. The research phase of the buyer journey is increasingly happening inside AI interfaces, not traditional search results. Brands are scrambling to understand “answer engine optimization” (AEO) and “generative engine optimization” (GEO)—new disciplines focused on getting recommended by AI systems rather than just ranked by algorithms.¹²

This has real commercial implications. When ChatGPT agents start booking and buying on behalf of users, sites need to be optimized for AI-driven conversion, not just human browsing.¹³ When AI systems synthesize information rather than link to sources, the whole model of search-driven traffic fractures.

Media agencies are already using AI search insights to predict what audiences want before they search for it.¹⁴ The zero-click landscape—where users get answers without clicking through to publishers—is forcing everyone to rethink their content strategy.¹⁵ One analysis found YouTube has a 200x citation advantage in AI search results, suggesting video content may be more defensible than text.¹⁶

The SEO community is responding with new metrics. LLM “perception drift”—how AI systems describe your brand over time—is emerging as a key measurement for 2026.¹⁷ It’s not enough to rank; you need to be recommended, and you need to monitor how AI systems talk about you.

What this means for marketers

• Start tracking AI mentions and sentiment alongside traditional search rankings

• Invest in structured data and clear, authoritative content that AI systems can confidently cite

• Consider video as a more defensible content format in an AI-summarized world

• Build direct audience relationships (email, community) that don’t depend on search traffic

• Test how ChatGPT and Google AI Mode describe your brand—then optimize for that

3. Every Company Becomes a Media Company (Whether They Wanted To or Not)

The retail media explosion has been building for years. But 2025 marked the moment it became unavoidable—and spread far beyond retailers.

Mastercard launched an ad business to pitch its shopping data to advertisers.¹⁸ American Express did the same, formalizing “Amex Ads” as a platform.¹⁹ PayPal is turning small business websites into ad networks.²⁰ Shopify rolled out an ad network for millions of merchants.²¹ These aren’t retailers. They’re financial infrastructure companies that realized their transaction data is a media asset.

Meanwhile, traditional retail media networks are racing to stay ahead. Amazon’s DSP is now “fully featured” as ad sales continue to boom.²² Best Buy is building in-store takeovers and sports deals into its retail media offering.²³ Instacart integrated with TikTok to bolster its retail media credibility.²⁴ Albertsons partnered with NBCUniversal on data collaboration that drove measurable CTV ad outcomes.²⁵

But there’s a threat on the horizon. As chatbots become shopping assistants, the appeal of on-site retail media ads may diminish.²⁶ If consumers increasingly discover products through AI recommendations rather than browsing retailer sites, the whole retail media model needs to evolve.

The response is already emerging. Industry players are uniting to accelerate programmatic’s AI-driven future through frameworks like AdCP (Ad Context Protocol).²⁷ PubMatic partnered with Kontext to place ads inside AI chatbots through programmatic auctions—a glimpse of what post-search commerce media might look like.²⁸

What this means for marketers

• Evaluate commerce media partners beyond Amazon; financial platforms and grocery chains are building serious capabilities

• Prepare for a world where AI intermediates the shopping journey—your retail media strategy may need an “AI-first” layer

• Watch for measurement fragmentation as every platform launches its own ad network with its own attribution model

• Consider whether your brand is positioned to benefit from first-party data partnerships, or whether you’re just renting access

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4. The Creator Economy Gets Its Financial Infrastructure

The creator economy has always had a monetization problem. Creators make content; brands pay for sponsorships; platforms take a cut. It’s inefficient, opaque, and leaves most creators underpaid.

That’s starting to change. Visa extended its reach into the creator economy’s “liquidity crunch,” offering financial products designed for creator income patterns.²⁹ Agentio raised $40 million to bring programmatic advertising to creator marketing.³⁰ Wpromote acquired Giant Spoon, merging performance and creative proficiencies into a single agency model built for creator-driven campaigns.³¹

The creator economy M&A boom signals that investors now see creators as valuable media entities worth consolidating.³² “Creator conglomerates” are emerging—individual creators expanding from content into diversified business units with multiple revenue streams.³³

But the measurement problem persists. A Digiday report argued that the creator economy needs a “new currency” for brand deals—better metrics that can justify creator spend against traditional media.³⁴ Advertisers are expanding affiliate efforts as creator marketing matures, looking for more rigorous and measurable investment models.³⁵

What’s particularly interesting is where creator marketing is heading next. Brands are tapping “outside-the-box personalities” to differentiate as influencer marketing gets more competitive.³⁶ Target shifted from studio shots to influencer-driven content for its Woolrich collaboration—a social-first approach that required rethinking the entire creative process.³⁷ Twitch is testing livestream shopping ads with E.l.f. Cosmetics, piloting new formats that could turn streaming into a commerce channel.³⁸

What this means for marketers

• Look beyond follower counts to creator business models—creators with diversified revenue are more stable partners

• Expect creator marketing costs to rise as financial infrastructure makes the market more efficient

• Test affiliate-based creator deals that tie compensation to outcomes, not just impressions

• Consider whether your creative briefing process can accommodate creator-led content, or whether you’re still treating creators as talent rather than partners

5. Humans Become the Luxury Feature

Here’s the paradox: as AI becomes more prevalent, brands are increasingly emphasizing their humanity.

Aerie launched a campaign explicitly rejecting AI in its ads, vowing to stay “100% real.”³⁹ After backlash to its AI-generated Wrapped, Spotify returned with a more “human touch” for 2025.⁴⁰ Coca-Cola used AI to refresh its holiday ads, but the story it told was about emotional connection, not technology.⁴¹

This isn’t anti-AI sentiment. It’s a recognition that AI ubiquity creates a differentiation opportunity for brands willing to emphasize human craft, authenticity, and emotional resonance. The most shared work isn’t technically impressive; it’s emotionally resonant.

Nostalgia marketing is surging as part of this counterswing. Pringles brought back “Once You Pop” to meet Gen Z tastes.⁴² Herbal Essences ran an infomercial-style campaign celebrating “scent traps” with a deliberately retro aesthetic.⁴³ Welch’s introduced a new kid mascot that bridges nostalgia with modern marketing.⁴⁴ These brands are betting that familiar formats and emotional cues cut through better than novel AI executions.

The AI industry itself is responding. Adcolor’s conference message emphasized that AI needs diverse voices to create ethical, inclusive solutions.⁴⁵ A new agency called “Artists & Robots” launched specifically to inject human creativity into AI-powered brand experiences.⁴⁶ Even the technologists recognize that “more AI” isn’t always the answer.

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What this means for marketers

• Audit your brand’s AI usage for backlash risk—where does automation feel authentic vs. where does it feel cynical?

• Consider whether “human-made” or “AI-free” could be a legitimate brand positioning for certain products

• Lean into nostalgia and emotional storytelling as differentiation strategies in an AI-saturated landscape

• Train creative teams on AI tools, but also on when not to use them

6. The Walls Between Social, Streaming and Commerce Collapse

What happens when everything starts to look like everything else

The streaming wars are consolidating. Netflix acquired Warner Bros. Discovery for $83 billion, a deal that reshapes the entertainment landscape and dramatically expands Netflix’s advertising opportunities.⁴⁷ Tubi reached profitability for the first time, proving that free, ad-supported streaming can work at scale.⁴⁸ Disney and YouTube TV remain locked in distribution disputes that highlight how fragile the streaming ecosystem remains.⁴⁹

Meanwhile, platforms are bleeding into each other’s territory. TikTok launched a podcast network with iHeartMedia.⁵⁰ Pinterest acquired TvScientific to expand into CTV advertising.⁵¹ Amazon is recasting Twitch as a core part of its CTV pitch, leveraging gaming audiences for brand advertising.⁵² Reddit unveiled interactive ad formats piloted by Paramount.⁵³

The IAB shifted its NewFronts calendar and added a dedicated Creator Upfront, acknowledging that creators now deserve their own buying event alongside traditional media.⁵⁴ Amazon launched location-based interactive Prime Video ads, letting brands target specific geographies within streaming content.⁵⁵

What does convergence mean for marketers? It means fewer clean distinctions between “social,” “streaming,” “search,” and “commerce.” It means buying decisions that span platforms and formats. And it means measurement complexity that most organizations aren’t equipped to handle.

What this means for marketers

• Rethink media plans around audience behavior rather than platform categories

• Expect CPMs to shift as Netflix scales its ad business and streaming inventory grows

• Build measurement frameworks that can attribute across platforms, not just within them

• Watch creator-led content as a bridge between social and streaming audiences

What To Do Now: Six Actions for Q1 Planning

These shifts don’t operate in isolation. AI is changing search, which is changing commerce, which is changing creator marketing, which is changing how brands tell stories. The organizations that win in 2026 will be the ones that see these connections clearly.

Here’s where to start:

1. Audit your AI infrastructure. Not just tools—organizational readiness. Are your approval processes designed for machine speed? Can your teams actually use what you’ve bought?

2. Build an answer engine strategy. Track how AI systems describe your brand. Invest in content formats (video, structured data) that AI can confidently cite.

3. Diversify beyond search traffic. Direct audience relationships—email, community, loyalty programs—are the hedge against AI-mediated discovery.

4. Professionalize creator partnerships. Move from one-off sponsorships to ongoing relationships with measurement rigor. Consider affiliate structures that align incentives.

5. Find your human story. In an AI-saturated landscape, emotional resonance and authentic craft become differentiation strategies, not just nice-to-haves.

6. Simplify measurement before you scale. Platform convergence creates attribution chaos. Get your measurement house in order before spending scales.

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Stay Ahead of the Shifts

This report synthesized hundreds of stories. But the landscape keeps moving. New AI capabilities launch weekly. Platforms evolve monthly. Consumer behavior shifts quarterly.

Creative TLDR exists to help you spot these shifts earlier—not by drowning you in more news, but by curating the signal from the noise. Every day, we scan the top creative and advertising publications and distill them into sharp, scrollable insights for marketers who want to stay ahead without getting overwhelmed.

If this report was useful, subscribe to Creative TLDR to get the daily intelligence that feeds analysis like this. And share it with your team—the best strategic conversations happen when everyone sees the same patterns.

The shifts are already underway. The question is whether you’ll see them coming.

Sources

Footnotes

1. Amazon’s AI ads agent and campaign manager – https://www.adweek.com/media/amazon-ai-ads-agent-campaign-manager ↩

2. Yahoo testing 6 AI agents for ads – https://www.adweek.com/media/yahoo-dsp-testing-ai-agents ↩

3. Publicis debuts ‘Leona’ AI engine – https://www.adweek.com/agencies/publicis-taps-deepti-velury-to-lead-production-debuts-leona-ai-engine ↩

4. WPP launches self-serve AI platform – https://www.adweek.com/agencies/wpp-launches-a-self-serve-version-of-its-ai-platform-to-court-small-biz-dollars ↩

5. Unilever’s AI beauty marketing assembly line – https://digiday.com/marketing/inside-unilevers-ai-beauty-marketing-assembly-line-and-its-implications-for-agencies ↩

6. Stagwell’s AI pivot drives Q3 growth – https://www.adweek.com/agencies/ai-pivot-drives-q3-growth-at-stagwell-despite-advocacy-pullback ↩

7. Publicis AI-powered marketing strategy – https://www.marketingdive.com/news/3-stats-publicis-ai-powered-marketing-strategy-paying-off/802690 ↩

8. Gartner: marketers unprepared for AI transformation – https://www.marketingdive.com/news/gartner-ai-agents-fail-to-ease-cmo-pain-amid-need-for-deeper-shifts/805487 ↩

9. Google AI Overviews reach 2B+ monthly users – https://digiday.com/media/googles-ai-overviews-reach-over-2-billion-monthly-users ↩

10. ChatGPT Shopping changes ecommerce SEO – https://searchengineland.com/chatgpt-shopping-ecommerce-seo-rules-462865 ↩

11. Google: SEM and SEO will coevolve – https://searchengineland.com/google-sem-and-seo-will-need-to-coevolve-with-search-since-seo-is-not-dead-465093 ↩

12. Answer engine optimization best practices – https://blog.hubspot.com/marketing/answer-engine-optimization-best-practices ↩

13. ChatGPT Agent mode shopping insights – https://searchengineland.com/insights-chatgpt-agent-mode-463127 ↩

14. Media agencies use AI search insights – https://digiday.com/media-buying/media-agencies-use-ai-search-insights-to-predict-what-audiences-want ↩

15. Zero-click landscape challenges – https://digiday.com/marketing/how-brands-are-trying-to-optimize-outsmart-ai-answer-engines-across-the-zero-click-landscape ↩

16. YouTube dominates AI search citations – https://searchengineland.com/youtube-ai-search-citations-data-462830 ↩

17. LLM perception drift as key SEO metric – https://searchengineland.com/why-llm-perception-drift-will-be-2026s-key-seo-metric-465676 ↩

18. Mastercard launches ad business – https://www.adweek.com/commerce/mastercard-launches-ad-business-to-pitch-its-shopping-data-to-advertisers ↩

19. American Express launches ad business – https://www.adweek.com/commerce/american-express-launches-ad-business-in-growing-commerce-media-race ↩

20. PayPal turning SMB websites into ad networks – https://www.adweek.com/commerce/paypal-is-turning-small-businesses-websites-into-ad-networks ↩

21. Shopify rolls out ad network – https://www.adweek.com/commerce/shopify-product-network-merchant-ads ↩

22. Amazon DSP fully featured – https://www.marketingdive.com/news/amazon-dsp-now-fully-featured-ad-sales-boom-continues ↩

23. Best Buy builds retail media – https://www.marketingdive.com/news/best-buy-builds-retail-media-in-store-takeovers-sports-deals/760466 ↩

24. Instacart integrates with TikTok – https://www.marketingdive.com/news/instacart-retail-media-bona-fides-tiktok-integration/802379 ↩

25. Albertsons-NBCU data collaboration – https://www.marketingdive.com/news/chobani-drives-ctv-ad-outcomes-via-albertsons-nbcu-data-collaboration/805628 ↩

26. Retail media networks and ChatGPT era – https://www.adweek.com/commerce/how-retail-media-networks-must-adapt-to-compete-in-the-era-of-chatgpt ↩

27. AdCP framework for AI-driven programmatic – https://www.marketingdive.com/news/industry-players-unite-to-accelerate-programmatics-ai-driven-future/803096 ↩

28. PubMatic-Kontext AI chatbot ads – https://www.adweek.com/programmatic/pubmatic-deal-kontext-ads-ai-chatbots-programmatic-auctions ↩

29. Visa extends reach into creator economy – https://digiday.com/marketing/visa-extends-its-reach-into-the-creator-economys-liquidity-crunch ↩

30. Agentio raises $40M – https://www.adweek.com/commerce/adtech-firm-agentio-40-million-creator-marketing-programmatic ↩

31. Wpromote acquires Giant Spoon – https://www.marketingdive.com/news/wpromote-acquires-giant-spoon-merging-performance-creative-proficiencies ↩

32. Creator economy M&A boom – https://digiday.com/marketing/in-graphic-detail-inside-the-creator-economys-ma-boom ↩

33. Rise of creator conglomerates – https://digiday.com/media/the-rise-of-the-creator-conglomerate ↩

34. Creator economy needs new currency – https://digiday.com/future-of-tv/future-of-tv-briefing-the-creator-economy-needs-a-new-currency-for-brand-deals ↩

35. Advertisers expand affiliate efforts – https://digiday.com/marketing/advertisers-expand-affiliate-efforts-as-creator-marketing-matures ↩

36. Brands tap outside-the-box personalities – https://digiday.com/marketing/brands-tap-outside-the-box-personalities-to-stand-out-as-influencer-marketing-gets-more-competitive ↩

37. Target’s social-first marketing – https://www.marketingdive.com/news/why-target-embracing-social-first-marketing-woolrich-collab/802597 ↩

38. E.l.f. tests Twitch shopping ads – https://www.marketingdive.com/news/elf-cosmetics-first-test-twitch-livestream-shopping-ads/802953 ↩

39. Aerie rejects AI in ads – https://www.adweek.com/brand-marketing/aerie-rejects-ai-in-ads-vowing-to-stay-100-real ↩

40. Spotify Wrapped returns with human touch – https://www.adweek.com/creativity/after-an-ai-backlash-spotify-wrapped-returns-with-a-more-human-touch-for-2025 ↩

41. Coca-Cola uses AI for holiday ads – https://www.adweek.com/creativity/coca-cola-uses-ai-to-rekindle-the-magic-of-its-holiday-ads ↩

42. Pringles brings back “Once You Pop” – https://www.marketingdive.com/news/pringles-brings-back-once-you-pop-tagline-to-meet-gen-z-tastes ↩

43. Herbal Essences nostalgia campaign – https://www.marketingdive.com/news/herbal-essences-infomercial-nostalgia-scent-traps/802754 ↩

44. Welch’s new kid mascot – https://www.marketingdive.com/news/how-welchs-new-kid-mascot-bridges-nostalgia-with-modern-marketing/803633 ↩

45. Adcolor: AI needs diverse voices – https://www.adweek.com/creativity/ai-moral-stance-dei-adcolor-2025 ↩

46. Artists & Robots agency launches – https://www.adweek.com/agencies/new-agency-artists-robots-aims-to-underpin-brand-experiences-with-ai ↩

47. Netflix acquires WBD for $83B – https://www.adweek.com/convergent-tv/what-to-know-about-netflixs-83-billion-acquisition-of-wbd ↩

48. Tubi reaches profitability – https://www.adweek.com/convergent-tv/foxs-tubi-reaches-profitability-for-first-time ↩

49. Disney and YouTube TV dispute – https://www.adweek.com/convergent-tv/disney-and-youtube-tv-dispute-could-continue ↩

50. TikTok launches podcast network – https://www.adweek.com/media/tiktok-launches-podcast-network-with-iheartmedia ↩

51. Pinterest acquires TvScientific – https://www.marketingdive.com/news/pinterest-expands-into-ctv-advertising-tvscientific-acquisition/807749 ↩

52. Twitch as core of Amazon CTV pitch – https://digiday.com/marketing/pitch-deck-how-amazon-is-recasting-twitch-as-a-core-part-of-its-ctv-pitch ↩

53. Reddit interactive ad format – https://www.adweek.com/media/reddit-interactive-ad-format-paramount-running-man-game ↩

54. IAB adds Creator Upfront – https://www.adweek.com/convergent-tv/iab-shifts-newfronts-calendar-adds-creator-upfront ↩

55. Amazon location-based Prime Video ads – https://www.adweek.com/convergent-tv/brands-can-now-buy-interactive-amazon-prime-ads-targeting-specific-locations ↩

Other articles you might be interested in

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Netflix Didn’t Buy Warner Bros. Discovery. They Bought Time.

The $83 billion headline sounds like a power move. But the real story isn’t about Netflix getting bigger. It’s about Netflix getting ready.

When the streaming wars began, everyone thought it was about content libraries. Whoever had the most shows would win. But that was never the game. The game was always about what happens when the content runs out.

And now we’re finding out.

What Actually Happened

Netflix isn’t acquiring Warner Bros. Discovery to add another thousand titles to their catalog. They already learned that lesson the hard way when they lost Friends and The Office. You can’t build a business on rented furniture.

What they’re acquiring is infrastructure. Production capacity. IP ownership. Distribution muscle. The ability to control their entire supply chain from script to screen.

This is vertical integration dressed up as a streaming play. It’s the same strategy that built the original Hollywood studio system, just with better technology and worse workplace lighting.

The Earth Foundation: Know Your Terrain

Here’s what most coverage misses: Netflix has been preparing for this moment for a decade.

They didn’t wake up one morning and decide to spend $83 billion. They spent years building the operational systems to absorb this kind of acquisition. Their content management infrastructure. Their global distribution network. Their data analytics capabilities that tell them exactly which content works in which markets.

Warner Bros. Discovery brings legacy assets, established franchises, HBO’s prestige brand. But more importantly, they bring production studios, post-production facilities, and relationships with talent that take decades to build.

Netflix needed those foundations. Not for what they are today, but for what comes next.

Because the streaming model as we know it is hitting its ceiling. Subscription fatigue is real. Price increases have limits. The growth-at-all-costs phase is over. What comes next requires different infrastructure.

The Water Flow: Adapting to New Realities

The streaming wars taught us something uncomfortable: there’s no such thing as infinite growth in a subscription business.

Every streamer tried to be everything to everyone. Netflix. Disney+. Max. Paramount+. Apple TV+. They all chased the same model: subscribe, binge, retain.

But audiences don’t want seven streaming services. They want good content when they want it, and they’ll rotate subscriptions to get it.

Warner Bros. Discovery learned this the expensive way. They built Max. They merged content libraries. They raised prices. Subscribers churned anyway.

Netflix is betting that the answer isn’t more streaming services. It’s fewer, bigger, better-resourced ones that can actually sustain production at scale.

This acquisition is Netflix flowing into a new position. They’re not fighting Warner Bros. Discovery’s fight. They’re absorbing their resources and adapting them to Netflix’s operating model.

The Fire Strategy: What They’re Really Attacking

The surface narrative is that Netflix is consolidating the streaming industry. True, but incomplete.

The real attack is on the traditional film distribution model.

Warner Bros. Discovery still operates with one foot in theatrical exhibition and one foot in streaming. That split focus is expensive and increasingly unsustainable. Netflix doesn’t have that problem. They never built their business around movie theaters.

By acquiring Warner Bros. Discovery, Netflix gets to make a decision that legacy studios can’t: they can fully commit to direct-to-consumer distribution without worrying about theater owners, box office politics, or release windows.

They can take HBO’s prestige IP, DC’s franchise potential, and Warner’s production capabilities, and route everything through their global streaming infrastructure. No middlemen. No split revenue. No compromises.

This is the Fire Ring in action. A decisive strike at a moment when competitors are weakest. Warner Bros. Discovery needed a buyer. Disney is focused on profitability over expansion. Paramount is struggling. Apple and Amazon aren’t interested in legacy media headaches.

Netflix moved when the opportunity was clear.

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The Wind Perspective: Reading the Industry Shift

Step back and look at what’s happening across entertainment.

Live sports are moving to streaming. Amazon has NFL. Apple has MLS. Netflix is experimenting with live events. The lines between “streaming service” and “broadcast network” are dissolving.

At the same time, theatrical releases are becoming event-driven. Barbenheimer wasn’t just marketing; it was proof that people will go to theaters for experiences, not just content.

Netflix has been watching this shift. They know streaming isn’t the final form. It’s just the current distribution method. What comes after will blend streaming, live content, theatrical experiences, and global reach in ways we’re still figuring out.

Warner Bros. Discovery’s assets position Netflix for that future. HBO’s prestige programming gives them credibility with talent and critics. Warner’s studios give them production capacity. DC’s IP gives them franchise potential beyond Stranger Things and Bridgerton.

But more importantly, it gives them optionality. They’re not locked into one distribution model. They can experiment with theatrical releases. They can produce live events. They can create hybrid experiences that blend streaming and cinema.

The Void Question: What This Really Means

Here’s the uncomfortable part: this acquisition might be the clearest signal yet that the streaming boom is over.

Not that streaming is dying. That the phase of rapid growth, massive investment, and endless content libraries is ending. What comes next is consolidation, efficiency, and sustainable business models.

Netflix is preparing for a world where there are three, maybe four major entertainment companies that control production, distribution, and audience relationships. They’re ensuring they’re one of them.

The Void Ring asks: what are we not seeing?

We’re not seeing the hundreds of smaller production companies that will struggle to compete. We’re not seeing the independent creators who will find fewer buyers for their work. We’re not seeing the creative risks that won’t get funded because they don’t fit franchise models.

We’re not seeing the long-term cultural cost of vertical integration.

When a few companies control what gets made, what gets seen, and how audiences access it, creativity becomes standardized. Risk becomes calculated. Art becomes content.

That’s not a criticism of Netflix specifically. It’s the natural outcome of consolidation in any industry. But in entertainment, the stakes are different. What gets made shapes how we see the world.

What Happens Next

If this acquisition closes, expect more consolidation. Disney will likely make a move. Amazon and Apple will consider their positions. Paramount needs a buyer.

The streaming wars won’t end with a winner. They’ll end with a handful of survivors who carved up the industry between them.

For creators, this means adapting to a new reality. Fewer buyers. More standardized production models. Greater emphasis on proven IP over original voices.

For audiences, it means better production values and more consistent quality, but potentially less diversity in what gets made.

For the industry, it means the end of the Wild West phase and the beginning of something that looks a lot like the old studio system, just with different technology.

The Pattern Beneath the Deal

Netflix didn’t buy Warner Bros. Discovery because they wanted more content.

They bought it because they understand that the future of entertainment isn’t about streaming versus theatrical, or traditional versus digital.

It’s about who controls the entire value chain from creation to consumption.

And in that game, infrastructure beats content libraries. Systems beat catalogs. Foundations beat flash.

The streaming wars are ending. The consolidation era is beginning. And Netflix just made their move to be one of the survivors.

The question now is what we lose in the process.

What do you think gets lost when three companies control most entertainment? Reply and let me know what you’re watching change.

— Fabien

Sources

• https://about.netflix.com/en/news/netflix-to-acquire-warner-bros - Official Netflix press release: $82.7B deal structure

• https://finance.yahoo.com/news/netflix-to-acquire-warner-bros-studios-and-hbo-max-in-landmark-72-billion-deal-131724863.html - Deal breakdown, market concentration concerns

• https://id-times.com/news/industry-analysis-lists/streaming-platforms-2025-ranking/ - Netflix 301M subscribers, combined market share data

• https://evoca.tv/video-streaming-statistics/ - 45% canceled subscriptions in 2023, churn statistics

• https://variety.com/2025/film/news/wga-opposes-netflix-warner-bros-deal-merger-must-be-blocked-1236601433/ - WGA opposition: “This merger must be blocked”

• https://www.cnbc.com/2025/12/05/trump-netflix-wbd-deal.html - Trump administration “heavy skepticism,” Warren’s “anti-monopoly nightmare”

• https://deadline.com/2025/12/netflix-warner-bros-takeover-analysis-reshape-business-1236637120/ - Culture clash, layoffs, theatrical distribution concerns

• https://finance.yahoo.com/news/lowest-probability-outcome-netflixs-72-billion-deal-for-warner-bros-discovery-stuns-wall-street-153038741.html - Wall Street stunned: analyst gave it 5% probability

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Hi,

Two weeks ago, we explored the Earth Ring, the foundational systems that make everything else possible. Today, we’re diving into Water, the ring that determines whether your strategy survives contact with reality.

Water is this: knowing when your plan should bend and when it should break.

It’s 9am. You’re in the office kitchen making coffee when your phone lights up. The platform you’ve been betting on just announced a major algorithm change. The format you’ve spent three months perfecting? Dead in the water.

Your Q3 roadmap is locked. Creative approved. Budget allocated. Timeline set. Everyone’s expecting you to execute the plan.

But the plan just became obsolete.

You have two choices: pretend nothing changed and execute anyway, or adapt.

Most marketers freeze. Some panic and start over. The best ones flow.

This is the Water Ring. Not about abandoning strategy, but about knowing which parts bend and which parts hold.

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What Musashi Actually Said About Water

Miyamoto Musashi’s Water Book isn’t about going with the flow. It’s about becoming the flow.

His teaching: “The spirit of water takes any form. Water crashes from a height with force, covers any distance, becomes a trickle, becomes the ocean.”

Water adapts to terrain without losing its nature. Bruce Lee famously said Pour it in a cup, it becomes the cup. Pour it in a bottle, it becomes the bottle. But it never stops being water.

For marketers: “Make your fighting stance your everyday stance, your everyday stance your fighting stance.”

Your strategy shouldn’t have two modes—”the plan” and “panic mode.” It should flex naturally between execution states without losing center.

Think about the last time you had to pivot mid-campaign. Did it feel strategic or desperate? Fluid or chaotic?

That’s the difference Water makes.

The Real Problem: We’ve Built Rigidity Into Everything

We build quarterly roadmaps like they’re sacred texts. Lock creative in review cycles that take weeks. Set timelines that assume nothing will change between approval and execution.

Then reality hits.

A competitor launches something you didn’t see coming. A cultural moment makes your messaging feel tone-deaf. The platform deprioritizes your best-performing format.

And you’re stuck. Not because you lack ideas, but because your infrastructure wasn’t built to bend.

I’ve watched brilliant marketers lose opportunities because they couldn’t move fast enough. Not because they weren’t smart or strategic, but because adaptation wasn’t designed into their process.

The rigid marketer says: “We planned this in January. We’re executing it in June.”

The Water marketer asks: “What’s changed since January that should change how we execute?”

Notice: not whether we execute. Not what we execute. How.

Your positioning doesn’t change because Instagram prioritizes Reels. Your brand voice doesn’t shift because LinkedIn rewards carousels. Your strategic direction doesn’t pivot because TikTok launches a feature.

What changes is how you express those constants.

That’s the first principle of Water: your core is fixed, your execution is fluid.

Platform Changes, Principles Don’t

Think about how you talk to different people in your life.

You speak differently to your CEO than to your best friend. Different vocabulary. Different energy. Different references. But you’re still you. Same values. Same perspective. Same personality.

That’s not code-switching. It’s translation.

Water marketing works the same way. Your positioning stays constant. Your expression adapts to terrain.

What This Actually Looks Like:

Let’s say your brand positioning is: “Marketing grounded in timeless principles, not fleeting tactics.”

• LinkedIn: Strategic, case-study driven. “Here’s why foundational systems compound over time.”

• Threads: Conversational, insight-forward. “Most marketers optimize for motion. The best ones optimize for momentum.”

• Substack: Narrative, philosophical. “Musashi’s Water Book teaches flexibility in execution, not abandonment of strategy.”

Same strategic truth. Different terrain.

The Infrastructure That Makes This Possible:

You can’t adapt fluidly if every piece of content starts from zero.

This is where Water meets Earth. Your modular content system, the one you built in the Earth Ring, becomes the foundation for fluid execution.

Example from my own workflow:

My content lives in a modular system. Each insight is tagged by Ring, by platform, by format.

When I need to adapt, I’m not starting from scratch. I’m remixing from a library of strategic pieces. They might resonate differently

One Substack essay becomes:

• 5 LinkedIn posts (different angles, native format)

• 10 Threads posts (punchy, conversational)

• 15 quote cards for Instagram (visual, minimal text)

• 1 email sequence (narrative, deeper engagement)

One piece of strategic thinking. Multiple expressions.

That’s Water enabled by Earth. Build once, flow forever.

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Prepare Your Plays Before the Moment

You’re sitting in a conference room. Someone just said: “We need to respond to this trend. Can we have something by end of day?”

If your answer involves panic, scrambling, and “let me see what I can throw together,” you don’t have Water. You have chaos.

Water isn’t reactive. It’s prepared.

Here’s what changed for me: I stopped trying to be faster at creating and started being ready before the moment hit.

Last month, I presented a video case study to 200+ marketers at a monday.com event.

The video we screened was produced in record time—not because we rushed, but because we had:

• A distilled production process (Earth: systems create speed)

• A trusted partner who knows our rhythm (Water: flow with the right people)

• Pre-built creative frameworks we could adapt to the brief (Water: prepared plays)

No panic. No all-nighters. Just clarity under pressure.

This is what Musashi meant by preparation. He didn’t improvise in duels. He drilled technique endlessly so that when the moment came, his body moved before his mind decided.

Marketing works the same way. The brands that move fastest when opportunities hit aren’t winging it. They’ve built the infrastructure that makes speed possible.

What “Prepared Plays” Actually Means:

Not campaign decks sitting in a drawer. That’s rigidity disguised as readiness.

Real preparation is modular systems that let you deploy when timing matters:

1. Brief templates that answer strategy upfront

When a moment hits, you don’t have time to figure out positioning. Your brief template already answers: What’s the strategic goal? Who’s this for? What’s the one thing they should remember?

Fill in context, not strategy.

2. Content components ready to recombine

Your brand story. Your proof points. Your visual system. Your voice guidelines.

These don’t change week-to-week. Build them once (Earth). Remix them when timing matters (Water).

3. Decision frameworks that eliminate debate

“Do we move on this or not?” shouldn’t be a two-hour meeting.

Your framework answers it in five minutes.

When moments matter, process trumps panic.

Find the Right Window, Not the Loudest Crowd

Here’s where most “be agile” advice falls apart: people think adaptation means chasing everything.

It doesn’t.

Water’s real discipline is knowing which moments are yours and which ones to let pass.

Not every platform shift requires your response. Not every viral moment is your moment. Not every trend deserves your energy.

The Three Questions That Define Your Window:

1. Does this moment amplify our positioning, or dilute it?

A trend might be massive, but if engaging with it pulls you off-message, it’s not your window.

Example: Everyone’s doing “10 tips” listicles because they perform well. But if your positioning is “depth over speed, principles over tactics,” you don’t chase that format just because it’s loud.

You find the window where your message and the moment align.

2. Can we execute this authentically, or are we performing?

If you have to fake fluency with a trend to participate, you’ve already lost.

Water adaptation means bringing your perspective to the moment, not mimicking what others are doing.

Real talk: I see brands jump on viral formats they clearly don’t understand, and it shows. The audience can feel the performance. They scroll past.

The brands that win aren’t the ones who copy the format. They’re the ones who remix it through their lens, in their voice, with their point of view.

3. Is this a moment or a movement?

Moments pass. Movements compound.

Water marketers know the difference. They don’t burn energy on fleeting trends. They invest in shifts that have legs.

Example: Short-form video isn’t a moment. It’s a movement. Adapting your content strategy to include it makes sense.

A dance trend on TikTok? Probably a moment. Chase it only if it’s authentically your terrain.

Here’s the skill: strategic selectivity.

The brands that feel effortless aren’t moving constantly. They’re moving precisely.

The Discipline of Water

Fowing requires more discipline than rigidity.

Rigid execution is easy. You made the plan. You follow the plan. No calibration required.

Water execution is constant judgment. Knowing when to move and when to hold. Recognizing which moments are yours. Deploying prepared plays without hesitation.

The discipline of Water is this: stay loose in execution, stay firm in strategy.

Musashi never changed his fighting principles. He adapted his technique to every opponent. Same strategic core. Fluid tactical expression.

Without Earth, Water becomes reactive chaos. Without Water, Earth becomes rigid irrelevance.

You need both.

Building Your Water Ring: Where to Start

You don’t need to overhaul everything. Start with one adaptive system and let the benefits compound.

Step 1: Build Your Modular Content Library

Stop creating one-off posts. Start building reusable components:

• 10 core insights that define your positioning (written once, expressed many ways)

• Platform translation templates (how each insight adapts to LinkedIn, Threads, Instagram)

• Format variations (text post, carousel, video script, thread structure)

When you need to move fast, you’re remixing, not rebuilding.

Step 2: Define Your Decision Framework

Write down the criteria that determine when you adapt:

• What shifts require a response? (Format evolution, platform changes that affect your distribution)

• What shifts do you ignore? (Fleeting trends, competitor panic, noise disguised as signal)

• Who decides, and how fast can you move?

Clarity in advance creates speed in the moment.

Step 3: Prepare Three Plays

Identify three scenarios where speed matters and build the infrastructure now:

• Play 1: Cultural moment aligns with your positioning (brief template, approval path, content ready)

• Play 2: Platform format shift (modular content ready to adapt)

• Play 3: Competitive move creates opening (positioning response, messaging framework, distribution plan)

You won’t use these every week. But when the moment hits, you’ll move while others are still scheduling the meeting.

What’s Next

Water is the second ring. It builds on Earth and sets up Fire.

Earth gave you the foundation. Water gives you execution flexibility. Fire, which we’ll explore next, gives you the force to strike when the window opens.

The Five Rings aren’t steps. They’re simultaneous layers. You’re always operating in all five at once.

Next up: Fire Ring—how to strike with creative force when the moment is right.

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Your move:

What’s one prepared play you need to build before the next opportunity hits? What’s one moment you chased that wasn’t actually your window?

Reply and tell me. That’s your Water work.

— Fabien

P.S. — Share this with someone who’s stuck between “stick to the plan” and “wing it.” Water is the third option.

Other articles you might be interested in

Unlock Timeless Strategy for Modern Brands

What can a 17th-century swordsman teach you about content strategy, brand building, and growth?
Turns out — a lot.
The Five Rings of Marketing is a bold, battle-tested guide to mastering modern marketing with ancient wisdom.

Build your foundation. Sharpen your systems. Execute with precision. Brand Runner brings you creative productivity frameworks and brand strategy insights rooted in timeless principles. Subscribe for the dojo work nobody sees but everyone feels.

Subscribe now

Hi,

If you’ve been following along, you know I introduced The Five Rings of Marketing couple weeks ago: a framework for operating on five levels simultaneously instead of chasing tactics one at a time.

Today we’re going deep on the first ring: Earth.

It’s 3pm on a Thursday. You’re staring at a brief that should take 10 minutes but somehow requires an hour of back-and-forth. You’re hunting through Slack for that brand guideline doc someone shared three months ago. You’re rewriting the same positioning statement for the fifth time this quarter because nobody documented it properly the first time.

This isn’t marketing work. This is friction masquerading as work.

And it’s killing your creative output. And you... improvise.

Welcome to the Earth Ring, the least celebrated and most essential layer of The Five Rings of Marketing. This is the dojo work. The infrastructure. The systems that determine whether you’re building momentum or just staying busy.

Earth isn’t about productivity hacks or workflow optimization theater. It’s about building the terrain that makes everything else effortless.

Let’s talk about why most marketers avoid this work, and why the best ones can’t function without it.

Why We Resist the Foundation

Here’s the problem: marketing culture rewards output, not infrastructure.

Nobody gets promoted for “implementing a better brief template.” You don’t win awards for “building a knowledge management system that reduced decision fatigue by 40%.” The highlights reel shows the campaign launch, not the three months of operational groundwork that made it possible.

So we optimize for what’s visible. We chase the Fire Ring, bold creative executions, and skip the Earth Ring entirely. Then we wonder why every project feels like starting from zero. Why we’re constantly reinventing wheels. Why our best ideas die in execution because the infrastructure can’t support them.

But there’s a deeper reason we resist foundational work, and it’s written in our neurobiology.

The Psychology of Resistance

Every decision you make depletes a finite cognitive resource.

Psychologist Roy Baumeister’s research on ego depletion demonstrates that self-control and decision-making operate like a muscle, they fatigue with use. In his landmark 1998 study, participants who resisted eating chocolate performed significantly worse on subsequent problem-solving tasks than those who hadn’t exercised self-control. The act of making decisions, any decisions, depletes the same internal resource pool needed for creative work.

This phenomenon, known as decision fatigue, compounds throughout your workday. Research published in the Proceedings of the National Academy of Sciences found that judges were 65% more likely to grant parole at the beginning of the day or right after a food break, dropping to near zero as decision fatigue accumulated. The quality of our decisions deteriorates predictably as we burn through our daily cognitive budget.

In marketing, this manifests as a death by a thousand cuts. Every time you search for a file, you’re spending decision energy. Every time you explain positioning to a new stakeholder, you’re depleting cognitive resources. Every undefined process forces micro-decisions that tax your mental capacity. By the time you sit down to do actual creative work, your cognitive tank is running on fumes.

Cognitive Load and Creative Capacity

The second neurological barrier is working memory capacity. Cognitive load theory, developed by educational psychologist John Sweller, demonstrates that working memory can only process a limited amount of information at once, roughly four chunks of information simultaneously. When we exceed this capacity, learning and performance degrade rapidly.

Think about your current workflow. How many open loops are you juggling? That draft campaign waiting for feedback. The positioning doc you need to update. The three different file naming conventions across platforms. The approval process that changes depending on who’s asking. Each of these demands processing space in your already-limited working memory.

What cognitive load theory teaches us is that extraneous cognitive load, the mental effort spent on poorly designed systems and chaotic workflows, directly competes with germane cognitive load, the mental effort required for actual learning and creative problem-solving. Every badly designed system isn’t just inefficient. It’s actively preventing you from doing your best work.

The real cost of operating without Earth isn’t just inefficiency. It’s creative depletion.

Why Systems Create Freedom

Here’s the counterintuitive truth: the brain craves automation, not variety.

Research on habit formation by health psychologist Phillippa Lally shows that behaviors become automatic through repetition, with the average time to reach automaticity being 66 days. When a behavior becomes habitual, control shifts from the prefrontal cortex (which requires significant cognitive energy) to the basal ganglia (which operates automatically). This neural handoff frees up conscious attention for higher-order thinking.

This is why systems work. They’re not constraints on creativity, they’re cognitive offloading mechanisms. When you automate the routine, you liberate capacity for the novel.

Every documented decision is one less decision draining your daily cognitive budget. Every automated workflow is working memory freed for strategic thinking. Every systematic process is a neural pathway you don’t have to consciously navigate.

Earth work isn’t about being organized. It’s about protecting your capacity for the work that actually matters.

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What Earth Actually Means in Marketing

Earth is threefold: positioning, systems, and knowledge infrastructure.

1. Positioning as Terrain

Before you move, know where you stand.

Your positioning isn’t a tagline or a messaging doc gathering dust in a Google Drive folder. It’s your strategic ground truth, the answer to “what do we do and for whom?” that needs to be so clear, so documented, so internalized that every piece of content flows from it without debate.

Most brands don’t have positioning problems. They have documentation problems. The founder knows it. The CMO knows it. But it lives in their heads, not in a system. So every new team member, every freelancer, every campaign brief becomes a game of telephone.

Earth-level positioning means:

• One source of truth document everyone can access

• Decision frameworks that flow from that positioning

• Clear boundaries (”we don’t do this, we do that”) documented and enforced

• Empirical knowledge about your audience that compounds over time

This is unglamorous work. It’s also the difference between a brand with a voice and a brand that sounds like a committee.

2. Operational Systems That Route Work Automatically

The best systems are invisible. They make decisions so you don’t have to.

Think about your current creative workflow. How many decisions do you make just to move a project forward? Where does this brief go? Who approves this? Where do we store final assets? What’s the naming convention? What happens after it’s published?

Each of those micro-decisions is cognitive load. Each one is a small tax on your creative capacity.

Earth-level operations mean:

• Brief templates that force strategic thinking upfront (not after three rounds of revisions)

• Approval workflows that route automatically based on project type

• Asset management with clear naming conventions and findability

• Content repositories where finished work lives and can be repurposed

• Automated routing from creation to publication (one input, multiple outputs)

My Ideas Go Here system is pure Earth Ring thinking. Capture once, route automatically, zero friction between thought and action. It’s not about having more ideas. It’s about never losing the ones you have because your infrastructure failed you.

3. Knowledge Management: Write It Down Once

Here’s a test: Can a new team member find your brand guidelines, your positioning doc, your campaign retrospectives, and your competitive analysis without asking anyone?

If the answer is no, you don’t have knowledge infrastructure. You have institutional memory trapped in people’s heads.

Earth-level knowledge management means:

• Decision documentation: Why did we choose this direction? What did we test? What failed?

• Playbooks for repeatable work: Campaign launches, content calendars, partner briefs

• Centralized creative assets: Templates, brand resources, past work for reference

• Learning loops: Post-mortems that actually get documented and referenced

The “write it down once” principle is simple: if you’re explaining the same thing twice, you don’t have a system. You have a habit.

Document it. Template it. Automate it. Then move on to work that can’t be systematized.

Visibility Systems: Infrastructure, Not Tactics

Let’s talk about discoverability, because this is where most marketers confuse Earth with Fire.

SEO isn’t a campaign. It’s infrastructure.

Content strategy isn’t a calendar. It’s a taxonomy.

Cross-platform distribution isn’t posting the same thing everywhere. It’s building source content that adapts to multiple destinations automatically.

Most “content strategies” fail because they’re built in the Fire Ring. They’re about what to post, not how to be found. They optimize for output, not discoverability. They treat each platform as a separate silo instead of building a unified system that routes from one core truth.

Earth-level visibility means:

Content taxonomy and tagging
Your archive should work for you. Every piece of content should be tagged by topic, format, audience, and stage of awareness. Not for analytics theater, but so you can repurpose strategically. So you can see patterns. So you can answer “what have we said about X?” in seconds, not hours.

Cross-platform content routing
Write once, publish everywhere isn’t lazy. It’s smart infrastructure. A Substack essay becomes LinkedIn posts becomes Twitter threads becomes email sequences. Not because you’re recycling, but because you’re routing from a single source of truth through different distribution channels.

My Creative TLDR tool is Earth Ring infrastructure for the Wind Ring work of staying marketing aware. Instead of manually checking twelve publications daily, the system scans, synthesizes, and delivers. Build the visibility system once. Let it compound forever.

Discoverability as strategy
Fire Ring marketers chase virality. Earth Ring marketers build compounding discoverability. They structure content so search engines and platforms reward it over time. They create hub-and-spoke architectures where pillar content feeds ongoing campaigns. They build once and distribute forever.

The math is simple: would you rather spend 10 hours creating something that gets seen once, or 15 hours creating something that gets discovered continuously?

That’s the difference between Fire thinking and Earth thinking.

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The Compound Effect of Earth Work

Here’s the truth most productivity content won’t tell you: building systems takes more time upfront than just doing the work manually.

Creating a brief template takes longer than writing one brief. Building an automated content pipeline takes longer than posting manually. Documenting your positioning takes longer than just “knowing it in your head.”

But here’s what compounds:

10 hours of system-building saves 100 hours of execution.

Let me show you the math.

Example 1: Brief Templates

• Time to build a good creative brief template: 3 hours

• Time saved per project (no back-and-forth, clear inputs, strategic forcing functions): 2 hours

• Payback after: 2 projects

• Annual savings at 20 projects: 40 hours

Example 2: Content Routing System

• Time to build a Notion-to-Supabase-to-distribution pipeline: 12 hours

• Time saved per content piece (no manual posting, formatting, or scheduling): 30 minutes

• Payback after: 24 posts

• Annual savings at 200 posts: 88 hours

Example 3: Decision Documentation

• Time to document your positioning, voice, and strategic frameworks: 8 hours

• Time saved per new project (no re-explaining, no drift, no debate): 1 hour

• Payback after: 8 projects

• Annual savings at 50 projects: 42 hours

That’s 170 hours, over four full weeks of work, returned to you for creative thinking instead of operational friction.

And that’s conservative math. It doesn’t count the compounding effects of clarity, consistency, and not burning out your team with preventable chaos.

The best marketers I know aren’t the ones with the most ideas. They’re the ones whose systems make executing ideas effortless.

Building Your Earth Ring: Where to Start

You don’t need to build everything at once. Earth work compounds, so start with the highest-friction points and let the benefits motivate the next system.

Step 1: Audit — Where Are You Making the Same Decision Twice?

Spend one week tracking every repeated decision, search, or explanation:

• “Where’s that file again?”

• “What’s our positioning on this?”

• “Can you send me that template?”

• “Why did we decide that last time?”

Those repetitions are your system gaps. Rank them by frequency and pain. Fix the worst offenders first.

Step 2: Build — Three Systems Every Marketer Needs

If you build nothing else, build these:

System 1: Idea Capture and Routing
A single place where ideas go, with automatic routing to the right destination. Not a notebook. Not scattered apps. One system, zero friction, automatic processing.

System 2: Content Source and Distribution
One place where you create, multiple places where it publishes. Whether it’s Notion to social, Substack to newsletter to LinkedIn, or brief to final asset, build the routing once.

System 3: Decision Documentation
A living document that captures: brand positioning, voice guidelines, strategic frameworks, past campaign learnings, competitive positioning. If someone asks “why do we do it this way?” the answer should be a link, not a meeting.

Step 3: Maintain — Rebuild vs. Refine

Systems aren’t set-and-forget. They’re living infrastructure.

The rule: if a system stops serving you, fix it immediately. Don’t work around it. Don’t let friction creep back in. The moment you’re manually doing something your system should handle, that’s your signal to rebuild.

But don’t confuse iteration with overengineering. Earth work should fade into invisibility. If you’re constantly tweaking your systems instead of using them, you’ve crossed from infrastructure into procrastination.

Build it once. Let it work. Refine when it breaks.

The Strategic Advantage of Earth

Here’s what nobody tells you about foundational work: it’s not just about efficiency. It’s about strategic compounding.

Every hour you don’t spend searching for files is an hour you can spend understanding your market. Every brief that’s clear from the start is a campaign that executes faster. Every documented decision is institutional knowledge that survives turnover.

Earth Ring marketers don’t just move faster. They move with accumulated wisdom.

While everyone else is starting from zero every project, you’re building on everything you’ve learned. While they’re chasing the next trend, you’re operating from a foundation that makes adapting effortless.

The Fire Ring gets the applause. The Earth Ring gets the results.

What’s Next

This is the first deep dive in The Five Rings of Marketing series. Earth is the foundation. Everything else, Water’s adaptation, Fire’s execution, Wind’s awareness, Void’s intuition, only works if your ground is solid.

Over the coming weeks, we’ll explore each ring:

• How Water Ring thinking turns cultural fluency into strategic moves

• Why Fire Ring creativity requires Earth Ring discipline to sustain

• How Wind Ring awareness prevents you from building in a vacuum

• What Void Ring mastery looks like when systems meet intuition

But it starts here. With the work nobody sees.

Your move:
What’s the one repeated decision, search, or explanation that’s draining your creative capacity? Reply and tell me. That’s your first system to build.

And if you’re already thinking “I need to fix my infrastructure before my next campaign,” you’re exactly where you need to be.

The dojo work isn’t glamorous. But it’s the difference between being busy and building momentum.

Let’s build yours.

— Fabien

P.S. — Subscribe to get each ring as it drops. This is a long game. The systems you build now will compound by then.

References:

• Baumeister, R.F., Bratslavsky, E., Muraven, M., & Tice, D.M. (1998). Ego Depletion: Is the Active Self a Limited Resource? Journal of Personality and Social Psychology, 74(5), 1252-1265.

• Danziger, S., Levav, J., & Avnaim-Pesso, L. (2011). Extraneous factors in judicial decisions. Proceedings of the National Academy of Sciences, 108(17), 6889-6892.

• Sweller, J., van Merriënboer, J.J.G., & Paas, F. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10, 251-296.

• Lally, P., van Jaarsveld, C.H.M., Potts, H.W.W., & Wardle, J. (2010). How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, 40(6), 998-1009.

Tools mentioned in this post:

• Ideas Go Here: Idea capture and routing system (Earth Ring infrastructure)

• Creative TLDR: Daily marketing intelligence (Wind Ring awareness, Earth Ring delivery)

Other articles you might be interested in

Unlock Timeless Strategy for Modern Brands

What can a 17th-century swordsman teach you about content strategy, brand building, and growth?
Turns out — a lot.
The Five Rings of Marketing is a bold, battle-tested guide to mastering modern marketing with ancient wisdom.

Get early access

In this short video, I unpack The Five Rings of Marketing: a framework that transforms chaos into clarity by applying Miyamoto Musashi’s timeless strategy to today’s creative battlefield.

🧩 Summary of the Five Rings

1. Earth — Foundation
Define your brand’s truth and systems before you move. Everything stable is built on this ground.

2. Water — Adaptability
Flow with culture, bend with channels, but never lose form.

3. Fire — Execution
Ignite bold creative action rooted in strategy, not reaction.

4. Wind — Awareness
See the whole field — trends, competitors, culture — without imitation.

5. Void — Mastery
Operate from intuition refined by discipline. Move with purpose, not panic.

💡 Key Idea

AI has leveled the playing field of tactics.
Your thinking — your strategy, rhythm, and intuition — is now your competitive edge.

💬 Reflection Prompt

Which ring do you need to sharpen this week — your foundation, your flow, your fire, your awareness, or your intuition?

Subscribe to Brand Runner for creative-systems strategy, productivity, and stories from The Five Rings of Marketing.

Subscribe now

🔥 Next up → “The Earth Ring: How to Build a Brand That Can Actually Withstand Pressure.”

Hi!

Last month, Ahrefs gathered 500+ marketers for their annual Evolve conference.

The theme? AI has fundamentally broken search.

Not “disrupted.” Not “transformed.” Broken.

Google AI Overviews now appear on 19% of queries and reduce clicks by 34.5%. Gen Z searches on TikTok first. Reddit is the new review site. And LLMs are citing brands they trust — which means 85% of your visibility now comes from what other people say about you, not what you publish on your own site.

The marketing landscape just became a battlefield with new rules, new terrain, and old strategies that no longer work.

Sound chaotic? It is.

But here’s what most people missed: the speakers who thrived at Evolve weren’t teaching tactics. They were teaching principles. And whether they knew it or not, they were teaching the Five Rings of Marketing.

Let me show you what I mean.

🌊 Water — Flow or Drown

“Be like water, not content calendars.”

The biggest shift at Evolve? Search isn’t just Google anymore.

Users are discovering content across YouTube, TikTok, Reddit, Instagram, Discord, Amazon — everywhere. One speaker called it “Search Everywhere Optimization”, which is just a fancy way of saying: you have to flow into every channel without losing your essence.

That’s Water thinking.

Water marketers don’t panic when the platform changes. They don’t cling to the old playbook. They adapt, not by abandoning strategy, but by understanding each channel’s current, its pull, its undertow.

The SEOs who treated Google like the only river? They’re drowning right now.

The ones who’ve been practicing channel fluency: understanding how their brand moves differently on TikTok vs. LinkedIn vs. Reddit — they’re already swimming.

The Water lesson from Evolve: Listen faster than you publish. The market just told you where it’s flowing. Are you still standing on the bank?

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🌪️ Wind — Know the Other Schools

“Observe everything. Copy nothing.”

Here’s the uncomfortable truth that kept surfacing at Evolve:

Brand is the new SEO.

LLMs cite brands they trust. And that trust isn’t built on your website — it’s built through reputation, category association, and what the internet says about you when you’re not in the room.

According to research presented at the conference, brands are 6.5x more likely to be cited through third-party sources than their own domains. Your biggest ranking factor? It’s not even on your site anymore.

This is Wind strategy in action: understanding that you’re not optimizing for algorithms, you’re competing for mental real estate in culture.

Carrie Rose said it perfectly: “The best marketers are training people and the Internet to associate their brand with the category term.”

Peep Laja called it “onlyness” figuring out what only you can be.

Cyrus Shepard said: be the expert, not an expert.

That’s Wind thinking. You can’t just execute tactics. You have to study the competitive landscape, understand cultural currents, and position yourself where no one else is standing.

The Wind lesson from Evolve: Your competitors aren’t just other companies. They’re every brand competing for the same mental shortcut in someone’s brain.

🪨 Earth — Systems Scale Taste, Not Chaos

“Document the way before you walk it.”

Here’s where it gets interesting.

Every speaker talked about AI. But the smartest ones weren’t saying “use AI for everything.” They were saying: build systems around AI so it serves your craft, not replaces it.

Ryan Law, Ahrefs’ Director of Content Marketing, nailed it: use AI to automate checklist items so you can focus on the 20% that matters — taste, judgment, and strategy.

JH Scherck went deeper. AI adoption isn’t about throwing prompts at ChatGPT. It’s about:

• Starting small with things that don’t scale (yet)

• Treating prompting as a learnable skill

• Establishing verification guidelines

• Creating internal learning systems

• Running weekly AI show-and-tells

That’s Earth discipline. That’s the unglamorous dojo work that makes everything else effortless.

Because here’s what happens when you skip the foundations: you scale broken processes, publish hallucinations, waste money on compute bills, and derail entire campaigns because of a single typo replicated at scale.

When moments matter, process trumps panic.

The Earth lesson from Evolve: AI is a tool. Systems are the craft. Don’t automate chaos and call it innovation.

🔥 Fire — Strike While They’re Sleeping

“Every message is a strike. Make it count.”

The final theme at Evolve was audacity.

When AI can generate competent content on command, the only advantage left is being unmistakably human.

Mark Schaefer showed that chewing cows perform as well as 86% of all ads. Translation? Most marketing is indistinguishable noise.

So how do you cut through?

Madhav Bhandari shared his PIPE framework:

• Pattern identification — Spot the sameness

• Interrupt guardrails — Set boundaries so you’re strategic, not reckless

• Portfolio design — Balance attention-grabbing plays with credibility-building plays

• Execution system — Test small, review monthly, scale what works

That’s Fire strategy. Not random chaos. Intentional strikes.

Chris Cunningham added another layer: every company will need a creator — someone who can tell stories, share opinions, and represent the brand publicly.

Ahrefs does this brilliantly. They have multiple known faces in the SEO community: Tim Soulo, Sam Oh, Ryan Law, Patrick Stox, Glen Allsopp. They’re not just a faceless brand. They’re a school of thought with human voices.

The Fire lesson from Evolve: Attention isn’t given. It’s taken — with precision, timing, and purpose. But only if you’ve done the Earth work first.

🕳️ Void — The Marketer Is the Weapon

“Create from stillness, not noise.”

The conference didn’t explicitly talk about Void, but it was there in every insight:

When everyone has the same AI tools, the differentiator is taste.

When algorithms change every month, the anchor is principles.

When search happens everywhere, the strategy is presence.

The marketers who’ll win in this new era aren’t the ones with the best tactics. They’re the ones with the clearest sense of who they are and what they stand for.

They’re the ones who can sense a wave before it forms. Who know when to strike and when to wait. Who build systems that protect their creative flow instead of drowning in operational chaos.

That’s Void mastery — when strategy becomes instinct.

The Meta Lesson

Ahrefs Evolve 2025 just proved something I’ve been saying for months:

When marketing moves fast, principles move faster.

AI broke search. Multi-platform discovery fragmented attention. Brand reputation became the new algorithm.

The marketers who panic and chase tactics? They’ll burn out.

The ones who’ve built Earth foundations (systems, positioning, process), who practice Water adaptation (channel fluency, cultural listening), who study Wind perspective (competitive strategy, category mastery), and who strike with Fire precision (audacious, human creativity) — those are the ones who’ll thrive.

The Five Rings isn’t just philosophy.

It’s a survival manual for the exact moment marketing is in right now.

What’s your move?

Are you flowing like Water, or clinging to the old river?

Are you building Earth systems, or scaling chaos?

Are you studying Wind strategy, or ignoring your blind spots?

Are you striking with Fire, or just making noise?

The battlefield changed. The principles didn’t.

I live you with this one quote from Musashi Miyamoto:

P.S. Want to go deeper into the Five Rings of Marketing? Subscribe to Brand Runner to get the framework breakdown

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Pillar post on the framework here👇