Imagine working for years at a company, building products people pay for, and never actually knowing what your customers think of them.

That’s most executives. Most senior managers. Most of the people making the big decisions.

Yes, companies have support teams and sales reps who talk to customers every day. But what about the people setting strategy? The people deciding what gets built, what gets cut, what gets priced differently? Most of them have zero “customer capital” — no real knowledge of what customers actually want.

I learned this the hard way.

In 1999, the CEO of MyFamily.com asked our management team — about 12 of us — a simple question: how many of you have talked to a customer in the last 30 days?

Not one hand went up.

I felt indicted. So I changed it. I started calling customers every week, and I invited other executives to sit in on the calls. The feedback was incredible. It reshaped how we thought about the product, the pricing, the roadmap — almost everything.

A couple years later, as VP of Marketing, I took it further: every marketing employee had to spend one day a week at the call center, just listening. It changed how the whole team thought about the work.

Here’s the pattern I keep seeing, company after company: big decisions get made because someone in management decided to make them — not because customers asked for them. Features get cut. Prices change. Access gets restricted. And huge numbers of people are disappointed, but nobody in the room is actually listening to them.

Too many big decisions get made without ever asking the people they affect.

The fix isn’t complicated. Put a feedback form on every page. Read what comes in. Call the people who want to talk. Blog about what you’re hearing and what you’re doing about it. Then close the loop — tell them when you’ve acted on it.

That cycle — ask, listen, act, report back — is one of the simplest, most underused tools in business.

A VC I know in Utah put it bluntly: the biggest problem with most companies isn’t strategy or execution. It’s that they don’t understand what their customers actually want.

Any company can fix this. It starts with the CEO deciding that talking to customers isn’t optional — it’s the job.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

I keep coming back to the same feeling this week: it’s hard to look at what’s happening with AI right now and put it into words. It’s easy to shrug, say “AI is moving fast,” and go right back to doing everything the old way. I don’t want to do that. So instead, I built something.

In about a day and a half, I stood up a small company of Grok Bots.

Not a metaphor. An actual working org chart, made of bots.

Meet the Team

One bot, Omni, oversees the rest. Under Omni, I’ve got specialists covering the studio — strategy, marketing, finance, people, research — plus Citizen Portal and Workplace AI, and a handful of individual roles: lists, the website, pictures, LinkedIn, X.

Another agent runs my X account. He drafts every post. I decide what goes live.

That’s the pattern I want across everything we build at Soar. The bot drafts. You decide.

These bots already write ad copy, draft briefs, keep our investor hot lists current, and send email as me — always disclosing that a bot helped. They’re not pretending to be human. They’re just doing the work.

This Is Real Work, Not Vapor

Here’s a concrete example. I have 4,500 Workplace Scribe transcripts sitting in our system. I asked Grok Bot how it should search them without trying to cram the entire corpus into one context window every time. It came back with a schema — a real, technical plan for how to query that data efficiently — and it emailed the spec directly to Mervyn and Richard for their review.

That’s not a chatbot answering trivia. That’s a system proposing infrastructure.

By the end of the day, that same setup had spun up 19 sub-agents, each handling a piece of the work I’d pointed it at.

The Moment We’re In

I’ve said this before and I’ll keep saying it: this is the moment where you stop doing the work of one person and start doing the work of an entire team — if you set the bots up the way people who understand this are setting them up right now. Tell your chief-of-staff bot what you’re trying to accomplish, and it will design the rest of the fleet you need to get there.

I’ve been reading Brian Roemmele on this, and it’s worth your time if you want to understand why this shift is different from the last ten “AI is here” moments.

Why It Matters for Growth

Here’s where this gets practical, not just exciting:

A Grok Bot can research every past and current user of a Scribe project and help you get a conversation scheduled with them. It can follow up within minutes of someone signing up — not hours, not days.

Do you know what InsideSales.com found when they studied lead response time? Speed to contact is one of the single biggest levers on whether a lead converts at all. It’s called the Success Lever, and most companies still get it wrong because a human simply can’t respond fast enough, every time, to every lead.

That’s one lever. There are thousands of small, crucial things that have to happen consistently for a company to succeed financially. A human team burns out trying to do all of them. A bot fleet doesn’t.

The Talent Behind the Bots

None of this replaces people — it multiplies them. We just launched a weekly talent draft so we can hire Philippines-based VAs who already run Grok Bot and know their own StrengthsFinder profile. There’s a site for it now, with cards and rules, and one of our team members is putting real people on it as we speak.

The bots draft. The people decide. The team gets bigger without getting slower.

I’ll keep sharing what I’m learning as I build this out. If you’re still doing everything the old way, I’d start now.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

Some people spend seventeen years quietly building something remarkable, without ever making a lot of noise about it.

That’s Tony Bacos.

I first crossed paths with Tony’s work over a decade ago, back when I was at Gallup. He had built a mobile polling app called Show of Hands, and I remember thinking it was one of the most interesting tools I’d seen. I even brought Tony out to Omaha to meet the team. At the time, it didn’t quite fit what Gallup was building — their brand is built around being the gold standard of scientific polling, and Show of Hands was something different: faster, more open, more conversational. It just wasn’t the right home for it then.

It turns out it’s the right home now.

Soar is acquiring Show of Hands. And Tony Bacos is joining us.

Why This Is a Big Deal

Since 2009, Tony has run Show of Hands as a side project — just a couple hours a day, quietly building something extraordinary. Over that time, he’s asked more than 300,000 questions and collected over half a billion responses from everyday Americans, across all 50 states, sliced into 20 different psychographic categories.

That’s not a survey. That’s a living, breathing map of what this country actually believes, worries about, and wants — built patiently, one question at a time, by one person who cared enough to keep asking.

And it’s not just answers. Every poll has comments. Every comment can be upvoted. It’s part Gallup, part Reddit — a real-time conversation between millions of Americans that Tony has kept running for 17 years straight.

We’re honored to become the home for that dataset, that user base, and that app.

Who Is Tony Bacos?

Tony’s résumé speaks for itself, even though he’d probably never lead with it.

He ran Amazon’s homepage — reporting directly to Jeff Bezos every month on what showed up on the front door of the world’s biggest store. He ran tech and customer experience for Amazon Fashion, the countries largest clothing retailer. He just retired as Chief Product and Technology Officer of Stitch Fix, a publicly traded company.

Thirty years of building products people actually use. And through all of it, Show of Hands stayed in the background — a quiet, personal project born out of genuine curiosity about people.

That’s what stands out most to me. Tony isn’t just a builder. He’s endlessly curious — about what people think, what they need, what keeps them up at night. He’s spent nearly two decades simply asking, and listening. That kind of patient curiosity is exactly what’s going to help Soar see and meet real human needs as we build with AI.

Where This Goes

Show of Hands will live under Soar, with deep integration into CitizenPortal. Imagine every poll question turning into a news cycle. Imagine city leaders and everyday citizens seeing, in real time, what their neighbors actually think about the economy, education, travel, local government — everything.

And imagine what this does for AI. All those responses, all those comments, all that human nuance — that’s training data money can’t easily buy. It’s the kind of thing I’ve long believed in myself, in a much smaller way — back at MyFamily, and at FamilyLink, we asked our own customers over 1,000 questions and gathered more than 300 million responses over the years, just trying to understand the people we served. So I recognize what Tony has built, and I have real respect for the patience it took to build it.

Tony spent 17 years doing that work, quietly, at a scale most companies would kill for.

Welcome, Tony

Tony is joining the CitizenPortal board. He’s trading a quiet side project for a much bigger stage — and we’re grateful he’s chosen to build the next chapter with us.

We’re glad to have you, Tony. Excited to see what we build together.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

I never intended to be a tech entrepreneur. I wanted to be a Kremlinologist.

Funny thing about studying centrally planned economies: you never forget the lesson. Twelve people in a room don’t know how many shoes a country needs, how much newsprint, how many roads. They guess. They ration. They fail. The Soviet Union ran a five-year economic plan every five years since the Bolshevik Revolution, and it was the laughing stock of the world.

So why do we keep rebuilding that model everywhere else?

The rich-get-richer trap

AI has unprecedented potential to help billions of people navigate life, build wealth, learn, and thrive. But if that intelligence is owned and controlled by a handful of trillion-dollar companies, and the rest of us are just leasing access to it, we know exactly how that story ends. The rich get richer. Everyone else gets subsumed.

That’s why I believe in decentralized, distributed intelligence. Public domain data. Open-source models. Tools that regular people can own, deploy, and run themselves — not rent forever from someone else.

Your fleet, not your résumé

Here’s a scenario I keep coming back to: it’s 2030, and a hiring manager isn’t asking a candidate about their career history. She’s asking about their fleet.

Tell us about your fleet.

Because the candidate has spent three or four years training 25 AI agents that handle research, outreach, scheduling, forecasting — a whole team working quietly in the background. That candidate doesn’t walk into the interview alone. They walk in with superhuman capacity already attached.

This isn’t science fiction. It’s a direction. Humans who speak or type can run a fleet of AI agents. That’s it. That’s the whole bar for entry. Record your meetings and calls for thirty days, let the patterns surface, and an agent fleet gets built around what you actually do and commit to every day. You look at it and think, oh, I wouldn’t have thought of that. Then you watch it get done for you.

Labor and capital stop fighting

For most of the history of capitalism, labor and capital have been at odds. One side owns the means of production. The other side shows up and gets paid for their time.

AI agents change that math. If a worker shows up to a company with their own trained fleet — their own chief of staff, their own research assistant, their own outreach engine — they’re not just labor anymore. They’re bringing capital. And when they leave, they should take their fleet with them. Wipe the company data, keep the agent. It got smarter while you used it. It’s yours.

I think this is the first real chance in the history of capitalism for labor and capital to stop being adversaries and start being the same thing, held by the same person.

Focus on strengths, not deficits

Underneath all of this is something older than AI. Don Clifton, who built the entire field of strength-based psychology, asked a simple question: wouldn’t it be better if we focused on what’s right with people instead of what’s wrong with them?

Open the DSM and you’ll find thousands of things that could be wrong with any of us. That’s not where growth lives. Growth lives in naming what a person is already good at and giving them tools to do more of it. An AI fleet doesn’t fix your weaknesses. It amplifies your strengths. That’s the whole point.

Let the good ideas travel

One more story. A handful of coaches in a Texas county built a program to help ex-offenders believe in themselves again — coaching, subsidized employment, real follow-through. It became one of the most successful re-entry programs in the country.

Has it spread to the other 3,143 counties in America? No. Because the data is isolated. Because nobody’s talking to the next county over. Because good ideas die in silos, not from lack of merit but from lack of visibility.

This is the same failure mode as central planning, just quieter. We don’t need twelve people deciding what works. We need millions of local experiments, and a way to see which ones are actually working — so the good ones spread and the bad ones get outvoted.

That’s the whole bet behind everything I’m building. Give people their own tools. Let a thousand experiments run. Help the good ones find each other.

The future isn’t fewer people doing the work. It’s more people, each with a fleet, deciding for themselves what’s worth building.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

What if happiness wasn’t a mystery? What if success wasn’t luck?

I’ve become a little obsessed with a question: what if the things that make our lives better aren’t hidden at all? What if they’re sitting right in front of us, and we just aren’t pulling them?

People call these things “life hacks.” I don’t like that word. A hack feels like a trick, a shortcut, something clever you stumbled into. I think there’s a better word: levers.

A lever is different. A lever is something you pull on purpose, knowing exactly what it will do. And once you know where the levers are, you don’t have to guess anymore. You just have to pull.

Here’s what I mean.

The Commute Nobody Talks About

Ask most people about their daily commute and you’ll get a groan. It’s the low point of the day, brim with traffic, noise, wasted time.

But give that same commute to someone riding with a friend, and it flips. It becomes the high point of their day. Same road. Same minutes. Completely different experience.

That’s a lever. Not a hack. A lever.

The Friend at Work Effect

Here’s another one, and this one has real data behind it. People who have a best friend at work are seven times more likely to be engaged in their job.

Seven times.

So why isn’t every manager, every HR department, every company on earth treating “does this person have a friend here” as a metric worth caring about? Engagement isn’t a mystery we can’t solve. It’s a lever we’re not pulling.

Five Minutes That Change Everything

My friend Ken Krogue co-founded InsideSales.com, and his team studied something simple: how fast companies respond to a new lead.

The average business waits about 48 hours to follow up on a web lead. Two full days.

But if you respond within five minutes, you’re 100 times more likely to actually make contact with that person. And you’re 21 times more likely to turn that contact into a sale.1

Not twice as likely. Not five times. Twenty-two times.

That’s not a marginal improvement. That’s a different business. And yet almost nobody is built to respond in five minutes. Why? Because most companies aren’t designed around the lever. They’re designed around habit.

The Warm Introduction

Reid Hoffman taught something years ago that has stuck with me ever since: you are five times more likely to land a meeting with someone if a mutual connection introduces you, compared to reaching out cold.2

I’ve felt this firsthand. A single introduction from a trusted friend once opened a door for me with two bestselling authors that cold outreach never would have touched. One warm connection did what a hundred cold emails couldn’t.

So why do so many of us still default to cold outreach? Why do we treat the lever like it’s optional?

Why Aren’t We Pulling Them?

This is the part that keeps me up at night. I’m not talking about secrets. I’m talking about things we already know. The data exists, the research is published, and the lever is sitting right there.

So why doesn’t everybody use it?

Maybe people don’t know the lever exists. Maybe they know, but don’t quite believe it applies to them. Or maybe — and I think this is the harder truth — some of us have quietly made peace with not succeeding. We’ve stopped expecting more, so we stopped reaching for it.

I don’t think that’s how we were meant to live. I think we were built for more than the default setting.

Cataloguing the Levers

I believe there are hundreds of these levers waiting to be found, documented, and understood — for happiness, for work, for relationships, for life evaluation as a whole. Some are backed by hard data, like Ken’s five-minute rule. Some are simple and human, like riding to work with a friend.

The problem was never that the levers didn’t exist, it’s that nobody built a system to help you find the ones that matter to you, and then actually pull them, consistently, without relying on willpower alone.

That’s exactly what we’re building at Soar.

Imagine an AI system that knows the levers — all of them, catalogued and verified — and helps you configure your own life and work around the ones that fit you. Not a list you read once and forget. A system that keeps pulling the lever for you, in the background, every single day.

Success and happiness were never supposed to be random. They were supposed to be engineered — on purpose, by design, by people who finally decided to stop guessing and start pulling.

The levers are there. The only question left is whether we build the systems to use them.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

What Bern Can Teach Washington

Are we a democracy? Or a constitutional republic?

I’ve watched smart people argue this for years. One former State Supreme Court justice I know has a better answer: we’re a constitutional democratic republic. That covers it nicely.

But here’s what almost everyone agrees on, whatever label they use: government should be “of the people, by the people, and for the people.” The “consent of the governed” isn’t a slogan. It’s the whole point.

We intuitively feel this. We believe our vote matters. We believe we have a right to be heard. It’s our government. It should answer to us.

So why doesn’t it feel that way anymore?

A Different Path

In April I met a government leader from Bern, Switzerland. He told me something I didn’t know: in 1848, Switzerland drew on the U.S. Constitution to build their own federal system, then took it in their own direction.

The result is a system that’s almost unrecognizable to American eyes.

• No single president. Switzerland is run by a Federal Council of seven people, elected together, who lead as equals. No one person holds the power.

• Rotating leadership. The presidency rotates every year among the seven. This year’s president is next year’s colleague again. No cult of personality, no four-year campaign cycle where the whole country holds its breath.

• Constant referenda. Some cantons vote on 12 to 20 local questions a year, on top of national votes. Citizens don’t just elect people to decide things for them. They decide a lot of things themselves.

• Radical independence. Switzerland isn’t in the EU. It stays neutral. It doesn’t get pulled into alliances its citizens never voted for.

I want to be careful here. Different isn’t automatically better. Switzerland is a small, wealthy, famously stable country, and what works for eight million people in the Alps doesn’t necessarily scale to 330 million people across a continent. I’m not arguing we should trade constitutions.

What I am saying is this: we already have a great charter. The problem isn’t that our Constitution was wrong. It’s that we’ve drifted from it.

For most of the last century, the document that was supposed to strictly limit and enumerate the powers of the federal government has been treated more like a suggestion. Washington has grown far beyond what the framers sketched out, and we’ve felt it: in the size of our tax bills, in the reach of federal regulation into small businesses and family farms, in how much of daily life now requires a permit, a filing, or a compliance department. Personal freedom and economic prosperity aren’t abstractions. They erode a little every time government expands past its original design.

That’s the real lesson from Switzerland, and it’s not really about Switzerland at all. It’s a mirror. Their system, whatever its merits, still runs on constant citizen involvement. Ours was built the same way. We just stopped showing up for it.

Trust Doesn’t Come From Nowhere

Americans don’t trust their government. That’s not a hot take, it’s been true for decades, across every poll, through every administration.

Why would we? When was the last time you felt like your elected officials actually heard you? Not at a town hall photo op. Not in a form-letter reply. Actually heard you.

Alexis de Tocqueville saw the source of American self-government almost 200 years ago, and he saw it clearly. Writing about New England town meetings, he put it this way:

“Local assemblies of citizens constitute the strength of free nations. Town-meetings are to liberty what primary schools are to science; they bring it within the people’s reach, they teach men how to use and how to enjoy it. A nation may establish a system of free government, but without the spirit of municipal institutions it cannot have the spirit of liberty.”

Tocqueville was describing us: ordinary citizens, practicing the art of self-government in their own small sphere, before that muscle ever atrophied.

We built a great republic 250 years ago, on exactly the spirit Tocqueville admired. But somewhere along the way, too many of us became spectators in it, and too much power drifted to Washington and away from the town meeting.

Bringing the Feedback Loop Back

This is exactly the gap Citizen Portal exists to close.

Every year, Citizen Portal surfaces millions of news articles to help people actually understand what’s happening in their local, state, and federal government. It helps you follow the officials who represent you and the issues you care about, in plain language, without the noise.

But information alone isn’t participation. Knowing what your representative did last week doesn’t mean they know what you think about it.

That’s the next piece we’re building: giving Citizen Portal users a direct channel to communicate their opinions, ideas, and insights straight to their elected officials. More on that very soon.

The goal is simple: strong communication between citizens and their government leads to better policy. Better policy leads to more trust. More trust, and less unchecked government reach, is exactly what this country needs to get back to first principles.

The Question I’m Sitting With

I keep coming back to something I want to ask my Swiss friends directly: what does it feel like to have that much say in your own government? To vote 15 or 20 times a year on things that actually matter, and know your voice moves the outcome?

If you’re a Swiss citizen reading this, I’d genuinely love to hear from you. Tell me how it feels to live inside a system built for your voice, not just your vote.

Because I think tens of millions of Americans are ready to remember what that feels like, too, in a country built for exactly that purpose.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

They wouldn’t be tweeting. They wouldn’t be filing for 501(c)(3) status. They wouldn’t be waiting on a committee to approve the next step.

They would be building.

That’s what the Founders actually were. Not just statesmen. Builders.

Benjamin Franklin didn’t just sign the Declaration of Independence. He invented the lightning rod, bifocals, and the Franklin stove. He founded America’s first public library, its first fire department, and the University of Pennsylvania. He was a printer, a publisher, a scientist, a diplomat — and he did it all without a staff of thousands.

Jefferson designed Monticello, wrote the Declaration, founded the University of Virginia, and catalogued thousands of books that seeded the Library of Congress. Washington built one of the most productive farms in the country while simultaneously commanding an army and then governing a nation.

These were people who didn’t wait for permission. They saw a gap and they closed it. They saw a tool that didn’t exist and they built it.

That’s the American tradition.

250 Years of Builders

Think about the arc.

Franklin tamed electricity. Edison turned it into light. The Wright Brothers turned physics into flight. A generation of engineers put a man on the moon with less computing power than today’s smartphone.

And then came the internet. Suddenly, anyone with a laptop and a good idea could reach the world.

Each of these moments had something in common. They didn’t just create new products. They democratized something. Franklin democratized safety and knowledge. Edison democratized light. The internet democratized information.

Every 50 to 75 years, something comes along that changes who gets to build — and what they can build.

We’re living in that moment again.

The Tool the Founders Would Have Grabbed First

If Franklin were alive today, he wouldn’t be amazed by the iPhone. He’d be amazed by AI agent fleets.

Think about what Franklin was, at his core: someone who could operate simultaneously across a dozen domains. Printer. Inventor. Diplomat. Civic organizer. Scientist. He was, in essence, a one-man fleet — a person who could deploy his intelligence across multiple problems at once.

Now imagine if he had actual agents. Specialized. Always on. Trained on the domains he cared most about.

He could have mapped the Gulf Stream and published the findings and lobbied Parliament about trade policy and organized the Philadelphia volunteer fire department — all in the same week.

That’s not fantasy. That’s what AI agent fleets make possible right now, in 2025, for anyone willing to learn to use them.

The Promise Has Always Been Human Potential at Scale

Here’s what I believe about America’s founding ideal: it was never really about geography or government. It was about the radical proposition that every individual matters. That the farmer’s son and the tradesman’s apprentice deserve the same shot as the king’s cousin.

Franklin was the son of a candle maker. He had two years of formal schooling. Two years.

And yet he built more in one lifetime than most institutions build in a century.

The tragedy of the last few decades is that we drifted from that idea. We built systems — in business, in government, in education — that concentrated capability at the top. The tools were expensive. The expertise was gatekept. The resources flowed to the already-resourced.

AI fleets change that equation.

A first-generation founder in rural Utah. A nonprofit director in South Chicago. A pastor trying to serve his congregation better. A teacher trying to reach 30 different kids with 30 different learning needs.

All of them can now deploy a fleet of specialized AI agents that work for them, learn for them, execute for them — around the clock.

That’s not a product feature. That’s the American promise, finally delivered.

Build Like a Founder

On this 250th birthday, I don’t want to just celebrate what America was. I want to celebrate what it can still become.

The Founders weren’t looking backward. They were building forward — toward something that had never existed before.

That’s what we’re doing at Soar.

We believe every person deserves their own AI agents. Tools they build, train, and carry with them. Not owned by a corporation. Not harvesting their data. Working for them — the way technology was always supposed to work.

Franklin once said he never patented his inventions because, as he put it, we enjoy great advantages from the inventions of others and should be glad of an opportunity to give back.

He wanted his work to uplift everyone.

So do we.

Happy 250th, America. Let’s build.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building agent fleets that uplift individuals, organizations, and communities. Create a personalized AI fleet for your company today.

I’ve been thinking about a couple experiences I’ve had in the last few years, demonstrating some of the most innovative AI tools I’ve seen in my career — tools that genuinely made the people in the room lean forward, eyes wide, asking how is this even possible.

And then two separate organizations — one a government agency, one a non-profit — shrugged.

Not because they weren’t impressed. They were. But one said, “We’re a Microsoft shop,” and the other said, “We’re a Google shop.” And that was the end of the conversation.

Maddening.

It reminded me of the old IBM commercial. No one ever got fired for buying IBM. Decades later, we laughed at how much innovation that one unspoken rule suffocated. How many better, cheaper, faster tools were left on the shelf because they didn’t have the IBM logo on the box.

We are watching that same dynamic play out in real time — at a moment when the stakes couldn’t be higher.

AI is not just moving fast. AI is moving at a speed we don’t have a good word for. The gap between what startups are building right now and what Microsoft Copilot or Google’s bundled tools can do is not a gap — it’s a canyon. And yet institutional inertia has become a more powerful force than innovation itself.

Here’s what troubles me most: the organizations most dependent on best-in-class AI tools are the ones least likely to use them.

Government agencies manage public health, infrastructure, education, emergency response. Non-profits serve vulnerable populations on razor-thin budgets. These are exactly the organizations that need every efficiency gain, every insight, every capability edge they can get. And they are systematically locked out of accessing it — not by law, not by budget, but by culture.

“We’re a Microsoft shop” is not a technology decision. It’s a risk-avoidance decision. It’s a career-protection decision. Nobody gets fired for buying Microsoft. But plenty of constituents go underserved because the tools that could have helped never got a fair hearing.

The competitive AI landscape has never been more alive with genuine innovation outside of Big Tech. Platforms like Together AI are letting organizations deploy and host open-source large language models without being locked into Google, AWS, or Microsoft infrastructure — giving enterprises control over their own data and models for the first time. Hugging Face, with its massive open-source model repository, has become what one analyst called “GitHub for AI” — a thriving ecosystem where thousands of models, datasets, and tools live outside the walled gardens of trillion-dollar companies. (Sources: AIMMediaHouse, Renewator)

There is even progress at the federal level. The U.S. General Services Administration’s OneGov initiative recently announced support for Meta’s open-source Llama models across federal agencies — specifically because open-source AI allows government teams to build, deploy, and scale applications while maintaining full control over sensitive data. That’s a meaningful crack in the wall. But it shouldn’t take a federal initiative to give agencies permission to try something new. (Source: Meta)

Meanwhile, antitrust experts and regulators are beginning to name what many in the industry have long feared: the Big Five tech companies have accumulated control over the key inputs into modern AI — specialized chips, compute, and talent — in ways that make it extraordinarily difficult for new entrants to compete. Already, trillion-dollar companies are more powerful than many nation-states. They control significant portions of our economy and the flow of information. (Source: ProMarket)

And when government employees reflexively default to the biggest players, they don’t just miss out on better tools — they actively deepen that concentration of power.

I want to be clear about what I’m not saying. Microsoft and Google have built real, useful AI capabilities. I’m not arguing they’re incompetent or malicious. I’m arguing that innovation never comes exclusively from incumbents — and that defaulting to them by policy rather than by merit is a different kind of problem.

The most transformative AI tools being built right now are coming from startups. Vertically focused companies building tools specific to healthcare, legal, education, and civic government. Agentic AI systems that don’t just answer questions but take action. Open-source models that can be deployed on sovereign infrastructure, customized, and controlled — no vendor lock-in, no data harvesting by a platform with competing commercial interests.

These tools exist. They work. And in many cases, they outperform what the big platforms offer.

So how do we fix this?

A few things I believe would make a real difference:

Mandate pilot programs. Government agencies and large non-profits should be required to run structured pilots of non-incumbent AI tools before renewing major technology contracts. Not an endless procurement process — a real, time-boxed evaluation. If the startup tool doesn’t perform, fine. But give it a fair test.

Protect the evaluators. The “no one gets fired for buying IBM” problem is fundamentally about career risk. We need explicit institutional protections for the people who recommend innovative tools — so that trying something new isn’t a career-limiting move, even if it doesn’t pan out.

Fund open-source AI infrastructure. The federal government funds roads and broadband because they’re shared infrastructure that enables everything else. Open-source AI deserves the same treatment. Tools built on Llama, Mistral, or other open models can be customized for public-sector use cases, run on government-controlled infrastructure, and made available without enriching a single private monopoly.

Change the procurement culture. Procurement rules designed for 10-year software contracts are simply incompatible with an AI landscape that changes every six months. We need new frameworks — faster, more adaptive, more willing to accept the possibility of iteration and change.

The AI revolution is not going to wait for institutional comfort to catch up.

The startups building the most remarkable tools I’ve ever seen are not standing still. They are iterating at a pace the big platforms structurally cannot match. Every month that government agencies and non-profits spend defaulting to their incumbent vendors is a month of capability left on the table — and a month of compounding advantage handed to companies that are already more powerful than they should be.

We cannot afford to let trillion-dollar incumbency determine the future of public-sector technology.

I’d love to hear your thoughts. How do we break this open? Share your ideas in the comments.

If your organization is ready to explore what a fleet of AI agents could do for your team, we’d love to start the conversation. Visit soar.com to find the right subsidiary for your needs.

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Paul Allen writes about the intersection of AI, human performance, and the future of competitive advantage.

For the first several years of building Soar, almost every customer we signed came through my personal network or a direct reach-out on LinkedIn. That’s not an accident. I’ve been doing tech startups since 1990, and I’ve spent a lifetime cultivating relationships. Today I have about 7,000 contacts in my phone and Google Contacts, and 74,000 followers and connections on LinkedIn. That’s a lot of doors to knock on.

The problem with building a company on personal relationships: it scales with one person. One person isn’t enough anymore.

Soar was always designed to be more than a single product or a single market. We’re an AI Studio: a parent company building a portfolio of AI-powered subsidiaries, each one deploying fleets of AI agents into a specific vertical. As those companies grow, so does the sales challenge. Ten salespeople can’t all lean on my Rolodex. They need their own pipeline, and each subsidiary needs its own repeatable motion that turns marketing spend into scheduled calls with organizations ready to buy.

One Platform, Multiple Focused Markets

The reason we structured Soar as an AI Studio is that the same core technology (fleets of AI agents that help every person on a team do their job better) works across completely different buyers. Rather than try to sell everyone with a single message, we built focused companies.

Workplace AI is our enterprise play. We help mid-size to large companies deploy AI agent fleets across their workforce: agents that handle the workload, execute on decisions, and give every employee an AI co-pilot calibrated to their role. The average client isn’t buying a tool. They’re changing how their team works.

Founder Portal brings the same model to startups. Founders get AI feedback on their pitch deck, guidance on which angels and VCs are most likely to fund them, and real-time insights after every investor meeting so they can get sharper with each one. An AI co-pilot walks them through every step from idea to exit. Starting a company is hard enough. We want to tilt the odds.

Faith Portal serves churches and nonprofits. These organizations run on mission and community, but they’re often under-resourced for the operational and communications support AI agents handle well. FaithPortal gives faith communities tools that large enterprises take for granted, built around the values and needs that matter most to them.

Education Portal takes the fleet into higher education, private labeled and customized for each university or college, serving students and alumni organizations. Every institution has its own identity and its own goals. EducationPortal is built around each school’s brand and outcomes, not dropped in as a generic product.

Four markets, four buyer profiles, one platform underneath all of them.

The Math

Right now, there are hundreds of thousands of businesses, nonprofits, universities, and startups in the U.S. that are going to buy or build AI agent functionality. The market isn’t arriving. It’s here. The question is who builds a go-to-market motion that scales.

Our head of marketing cut his teeth buying media at Google and Facebook. He knows how to optimize spend. Last month, our cost per sales meeting was $75. Last week, it dropped to $37. We expect to push it below $25 soon, and AI agents are a big reason why: the same agents we’re selling are helping us sell them.

Run the math. If our close rate is 10% and the average sale is $12,000 per year for a team of 10 users, then every dollar we spend driving meetings has a clear and measurable return. Lower the cost per meeting, hold the close rate, and you’ve got a lever you can pull as hard as your capital allows. Multiply that across four subsidiaries in four verticals.

If these metrics hold (and I believe they will), we might hire far more than 10 salespeople this year.

I’ve Seen This Movie Before

I watched this dynamic play out up close at Ancestry in the early years. We scaled our call center to 800 people. Why? Because the math made it obvious. The average rep was generating $120 per hour by upgrading customers from trials to paid, or from monthly to annual subscriptions.

We loved annual subscriptions. When a customer pays for the year upfront, your cash flow transforms overnight. Monthly subscriptions were a constant headache. Credit cards expire. Cards max out. Dunning logic is painful to maintain. We spent enormous energy just trying to figure out why payments weren’t going through.

Annual upfront is better for the customer, better for the company, and frankly better for your sanity.

The Josh James Lesson: Bet on Enterprise

I remember a conversation with Josh James back in his Omniture days, when the company was still called Superstats. He made a decision that looked reckless from the outside: he stopped chasing volume in small-business web analytics and went all-in on enterprise. At the time, he had exactly two enterprise clients: eBay and CNET.

He bet the company on it.

Years later, Adobe paid $1.8 billion for Omniture.

The lesson I took from Josh is that a focused motion built on repeatable sales processes and long-term contracts creates a different company than a high-volume, low-touch churn model. The unit economics are different. So are the relationships. The compounding is too.

But Josh’s situation isn’t ours. Omniture sold one product. We built Soar as a portfolio specifically so that different verticals get purpose-built solutions. A 40-person church staff and a 4,000-person enterprise have different needs, different budgets, and different timelines. They shouldn’t be shoved into the same product and told to figure it out. FaithPortal exists because faith organizations deserve a product built for how they actually work. Same for education. Same for founders. The focus isn’t about who’s big enough. It’s about who we can serve deeply.

What We’re Building Now

This year we’re carefully analyzing every GTM lever across the entire portfolio:

Paid media is the most measurable. Our marketing team is optimizing ad spend daily, and AI agents are helping us do it faster and cheaper than any human team could alone. We expect cost per meeting to keep falling across all four subsidiaries.

In-person events still matter more than people admit. There’s something about a handshake and a shared meal that accelerates trust in ways that a sequence of LinkedIn messages can’t. Whether that’s a founders conference for FounderPortal, a higher education summit for EducationPortal, or an enterprise leadership event for Workplace AI, we’re being intentional about which events we attend and why.

LinkedIn and personal reach will always be in the mix for me. But the goal now is to systematize what I do naturally: identify the right organizations, personalize the outreach, follow up with discipline. And deploy that across a full team operating in four different markets simultaneously.

We expect real growth this year. The market for AI agent fleets is here, the demand is building, and we have a system that’s working across the whole portfolio, not just one company.

The businesses, universities, churches, and startups that figure out the sales engine first will define this market. I’ve been on both sides of that lesson. I’m not interested in learning it again the hard way.

If your organization is ready to explore what a fleet of AI agents could do for your team, we’d love to start the conversation. Visit soar.com to find the right subsidiary for your needs.

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Paul Allen is the co-founder of Ancestry.com and CEO of Soar, an AI Studio building a portfolio of AI companies — including Workplace AI, FounderPortal, FaithPortal, and EducationPortal — to uplift humanity. He has been building technology companies since 1990.

I once told the Chairman of Gallup that his idea to have 24 Gallup Senior Scientists was one of the smartest business concepts I’d ever seen — he had two dozen brilliant people -- Nobel prize winners included - as his brain trust to help him decide what important questions to ask the world for the next hundred years in the Gallup World Poll, among other things.

I met several of these advisors and had phenomenally productive conversations with some of them.

Fast forward several years.

I’m now running Soar — an AI Studio designed to uplift humanity in all areas of life.

Soar now has 24 senior advisors who earn equity by helping me each month in group calls and in 1:1 meetings with me and my portfolio company CEOs.

The best advice I’ve ever gotten in my life came from Soar advisors in the last few months.

I’m grateful for good advice from good people.

One of the key pieces of advice from Dr. Don Clifton, author of Soar With Your Strengths, and father of said Gallup Chairman mentioned above, is that everyone of us should have our own personal “Board of Directors” who can help us navigate life in all its dimensions.

I’m going to ask my AI developers to make sure that as we build thousands of AI agents to help people succeed at work and in life, that we first and foremost design our platform to connect people with other people - people whose wisdom and caring can help our customers even more than AI ever will.

Facebook misleads billions of people by making them think they have hundreds or thousands of friends.

A real friend is rare.

We are each fortunate to have a small number of priceless friendships.

Those true friendships need to be treasured and nurtured.

Which is hard to do if you’re spending hours every day scrolling on your device hoping for thousands of likes from your “friends” on your last post, or binge-watching Netflix.

“Strengths Only Develop in Relation to Another Human Being” said Don Clifton.

What if AI helps you figure out who your real friends are and deepen bonds there, helps you value your family heritage and family ties, and carefully select your personal advisors or board of directors to help you thrive at work and in life.

AI designed to do that — to connect us to the people who can help us most — can help all of us have ah-ha moments like my advisors gave to me this month!

[Get started with Soar today.]

Paul Allen writes about the intersection of AI, human performance, and the future of competitive advantage.

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Governor Sarah Malone of Ohio took office in January 2030 with no illusions about the job. She’d spent twelve years in the state legislature. She knew the budget was tight, the problems were real, and that good intentions without good information was just another word for waste.

She also knew something her predecessors hadn’t fully grasped: for the first time in history, a governor didn’t have to govern blind.

Within her first week, Malone activated what her team simply called The Fleet — a coordinated network of AI agents tasked with one foundational mission: find out what actually works.

The premise was simple, almost embarrassingly so. Across the United States, thousands of governments — federal agencies, fifty state legislatures, three thousand counties, tens of thousands of municipalities — had been running programs for decades. Some of those programs were transforming lives. Others were burning money and producing nothing. And almost nobody had a complete picture of which was which.

The Fleet changed that.

Every night, while the governor slept, her AI agents were reading. Scanning legislation from Vermont and New Mexico. Digesting outcome data from workforce programs in Georgia and Colorado. Comparing recidivism rates across different reentry models in a dozen states. Tracking school attendance trends tied to specific nutrition initiatives in cities from Tulsa to Tacoma. Cross-referencing budget efficiency data, public satisfaction surveys, academic studies, and real-world outcomes — simultaneously, tirelessly, at a scale no human team could match.

By morning, The Fleet had organized everything into something a governor could actually use.

Take what happened with Ohio’s foster care system in March 2030.

Malone had inherited a system that was underfunded, understaffed, and producing heartbreaking outcomes for children aging out of care. She knew the problem. She didn’t know the solution. Her team had weeks, not years, to come up with something.

The Fleet surfaced a program that had been quietly running in Tarrant County, Texas — a model that combined early family intervention with a tiered kinship support network, backed by a modest but targeted funding structure. The outcomes were striking: kids staying in stable family environments at nearly twice the rate of the national average, at roughly 80% of the cost of traditional foster placements. The program had been running for four years. It had peer-reviewed validation. It had survived two budget cycles.

Nobody in Columbus had heard of it.

Within sixty days, Ohio had a pilot program running in three counties, adapted to the state’s specific legal framework and demographic realities. The Fleet hadn’t just found the model — it had mapped the statutory changes needed, flagged potential implementation pitfalls based on what had tripped up similar efforts in other states, and helped the governor’s policy team build the coalition needed to move it forward.

That’s one story. There were dozens like it unfolding simultaneously.

In education, the Fleet identified literacy intervention models from rural Tennessee that were producing outsized results in communities that looked a lot like southeastern Ohio. In infrastructure, it found maintenance scheduling frameworks used by Midwestern counties that were extending road lifespans by years while cutting costs. In public health, it mapped opioid recovery program structures across twelve states and built a composite model of what the evidence said actually moved the needle on long-term sobriety.

None of this was magic. None of it replaced human judgment, political wisdom, or the irreplaceable knowledge of people living inside these communities. Governor Malone was the first to say so. The Fleet found the signal. Her team still had to do the work.

But here’s what changed: she stopped making decisions in the dark.

For most of American history, good governance has been limited not just by money or willpower, but by information asymmetry. A program that worked brilliantly in Chattanooga might never reach Akron simply because no one with the right authority ever heard about it. A failed approach might be replicated in state after state because there was no efficient mechanism for failure to travel as fast as enthusiasm.

The Fleet collapsed that asymmetry.

I find this scenario genuinely thrilling — not because AI is doing the governing, but because it’s finally giving human leaders something they’ve always deserved and rarely had: a clear view of the whole landscape.

Governor Malone still makes the hard calls. She still answers to voters. She still has to look people in the eye and explain her choices. The Fleet doesn’t change any of that.

What it changes is this: when she makes those calls, she knows what she’s looking at.

That, it turns out, is everything.

[Get started with Soar today.]

Paul Allen writes about the intersection of AI, human performance, and the future of competitive advantage.

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Marcus Williams had a 44-inch vertical leap at 14 years old.

His eighth-grade gym teacher clocked it during a fitness assessment, scribbled it in a notebook, and told him off-handedly that he “might want to think about basketball.” Marcus went home and told his parents. His dad, Darnell — a logistics coordinator who’d spent his whole life passionate about music, not sports — smiled and nodded. His mom, Keisha — a dental hygienist who ran 5Ks on weekends — gave him a proud hug.

Neither of them had any idea what a 44-inch vertical meant.

Neither of them knew that across town, three kids his age already had travel coaches, skills trainers, highlight reels on recruiting platforms, and strength and conditioning programs built by former D1 athletes. They had been in “the system” since fifth grade. They knew which AAU circuits mattered. Their parents knew the names of college scouts the way other parents know pediatricians.

Darnell and Keisha knew none of this. They just knew their son was special.

The question was: what do you do when you know your kid has something — but you don’t know how the world around that something actually works?

The Wake-Up Call: 9th Grade

Marcus started high school in the fall of 2027 and made the JV team easily. He was fast, explosive, and had instincts you can’t teach. But the first time his team played a school from the north side of the county, Marcus came home quiet.

“Dad,” he said, setting down his gym bag, “those kids are different.”

He wasn’t wrong. The opposing team moved with a practiced precision that came from years of structured development. Their footwork. Their court vision. Their conditioning. Marcus had raw talent; they had a system behind them.

Darnell spent that week down an internet rabbit hole — AAU teams, basketball camps, skills trainers, recruiting timelines. He found forums full of jargon: “exposure events,” “prospect rankings,” “contact periods,” “NLI.” He felt like he’d discovered a foreign country he’d somehow missed his whole life.

A friend from church mentioned something that changed everything.

“You heard about that Apex fleet? The one Ronnie Castillo built?”

Ronnie Castillo had played nine years in the NBA before a knee injury ended his career. He’d spent his post-playing years obsessed with a single problem: why do so many talented kids from non-athletic families fall through the cracks? His answer wasn’t a training app or a mentorship program. It was something bigger — an integrated AI fleet called Apex, built to serve as a full-spectrum development system for athletes and their families.

Darnell signed up on a Tuesday night. By Thursday, everything had changed.

Year One: Building the Foundation (9th Grade)

The Apex fleet didn’t open with a workout plan. It opened with a conversation.

The family intake was almost disarmingly thorough — Marcus’s current skills (assessed via a 20-minute video drill session), his academic standing (a 2.7 GPA that had more to do with disorganization than intelligence), his sleep patterns, his diet, and crucially, his goals. Not vague goals. Specific ones.

The system identified three immediate gaps:

1. Technical skill lag. Marcus had elite athleticism but had never received formal instruction in ball-handling, footwork, or defensive positioning. He was two to three years behind his peers in structured development.

2. Academic vulnerability. D1 programs have minimum GPA and standardized test requirements. Marcus’s grades weren’t just about school — they were about eligibility. The fleet flagged this immediately as a non-negotiable priority.

3. Network invisibility. Marcus didn’t exist in any recruiting database. No film. No profile. No exposure. In the new recruiting landscape of 2030, where AI-assisted scouting tools scanned thousands of athletes across digital platforms, being invisible was the same as not existing.

The fleet built a 12-month plan. Not a PDF to print and forget — a living, adaptive system.

For Marcus, it assigned a daily skills training regimen (30 to 40 minutes, structured to complement his school and sleep schedule), connected the family to a local trainer named Coach Devin who specialized in late-developing guards, and enrolled Marcus in two targeted skills camps over winter and spring breaks. The fleet had cross-referenced camp quality, cost, college coach attendance records, and Marcus’s current development needs to narrow it down from hundreds of options to three — and then explained exactly why each one made sense.

For school, the fleet identified that Marcus struggled specifically with distraction during homework and had gaps in algebra that were cascading into other subjects. It generated a study structure, recommended tutoring resources, and — with Keisha’s help — quietly built a new evening routine into the family’s rhythm.

Marcus ended 9th grade with a 3.2 GPA and a first-ever highlight reel uploaded to two recruiting platforms. Small steps. But they were deliberate ones.

Year Two: First Exposure (10th Grade)

By sophomore year, something was shifting.

Coach Devin had told the family after six months: “I’ve had kids with better handles and better IQ. I’ve never had a kid who improved this fast.” The fleet’s programming wasn’t generic — it adapted weekly based on video reviews Marcus submitted after each practice. When his left-hand finishing was lagging, the system added targeted drills. When his three-point shot mechanics drifted, it caught it before it became a habit.

Darnell had also started getting smarter. One of the fleet’s features was a parent education module — not condescending, but real. It explained the NCAA recruiting calendar. It told him when coaches could and couldn’t contact Marcus directly. It told him what an “unofficial visit” was versus an “official visit,” and why the distinction mattered. It gave him language to use when he finally started talking to people in the recruiting world.

The family attended their first elite camp that summer — a camp in Atlanta that the fleet had flagged as “high coach attendance, well-regarded for late-developing prospects.” Marcus went in nervous and came out with something new: confidence that came from being seen.

Two college assistants stopped to watch him during the open run. Nobody offered anything. Nobody said anything life-changing. But Darnell caught one of them recording Marcus on a phone, and he understood — for the first time — that the machine was beginning to notice his son.

That fall, the fleet surfaced something unexpected. Marcus’s English and history grades had jumped to A’s — his study habits had genuinely transformed — but his science grade was slipping. The system noticed a correlation: Marcus’s sleep data (tracked through a wearable the fleet recommended) showed poor sleep on nights before his Thursday science class, and that class had moved to 7:45 AM. The recommendation was simple: shift his hardest studying to Wednesday evenings rather than late nights. Keisha laughed when she saw the recommendation. It worked.

Marcus ended 10th grade with a 3.5 GPA and varsity starter minutes.

Year Three: The Radar Starts Buzzing (11th Grade)

Junior year is where it gets real in recruiting. The fleet had been building toward this.

That August, the Apex system sat the whole family down for a “Junior Year Summit” — a structured planning session that laid out what the next 12 months needed to accomplish. It covered academics (Marcus needed to bring his ACT score up — he’d gotten a 21 on his first attempt; the target was 24 or better), exposure (two specific circuit events and one summer showcase), and the beginning of a communication strategy with programs.

The ACT piece was serious. The fleet built a personalized prep schedule, identified which content areas were bleeding points, and recommended two practice test sittings before the real exam. Marcus took it seriously. In April of 11th grade, he scored a 26.

Keisha cried. Darnell pumped his fist like Marcus had just won the championship.

On the court, Marcus was becoming a different player. The gap between him and the “system kids” was nearly gone. His handle was clean. His shot selection had matured. He was averaging 18 points and 6 assists for a varsity team that was making real noise in their district.

More importantly: he was visible now.

The fleet had helped the family build a legitimate online recruiting profile, maintained a highlight reel that was updated after every game, and — critically — coached Darnell and Keisha on how to initiate contact with programs. The system drafted thoughtful, professional outreach emails on the family’s behalf. It helped them understand that the way a family communicates with a college program sends signals about the kind of people they are, not just the player.

Three Division II programs sent questionnaires. One D1 mid-major sent a letter of interest.

Marcus read it twice at the kitchen table, then went to his room and didn’t come out for an hour. Keisha thought something was wrong.

“He’s crying,” Darnell said quietly, with a smile. “Happy crying.”

Year Four: Eyes on the Prize (12th Grade)

Senior year arrived with momentum and weight in equal measure.

The fleet’s 12th-grade priorities were clear: maintain grades (no eligibility surprises this close to the finish line), manage the recruiting process with professionalism and intentionality, and make sure Marcus arrived at every evaluation in peak physical and mental condition.

That last part mattered more than the family had expected. Marcus had always had a short emotional fuse on the court — a frustration response that could spiral into bad decisions and technicals. It was the one thing that made scouts hesitant. The fleet had identified this early and had been working on it steadily: a mental performance module that combined breathing techniques, pre-game routines, and self-awareness exercises built around Marcus’s specific triggers.

By senior year, the change was visible to everyone. His coaches noticed. Scouts noticed. Marcus noticed.

“I feel like I play slower now,” he told his dad one night. “Like everything’s clearer.”

The fleet also prepared the family for the parts of recruiting nobody tells you about: how to evaluate scholarship offers, what to look at beyond the athletics (graduation rates, coaching stability, development of players similar to Marcus), how to ask hard questions on campus visits, and what questions to ask agents as Marcus’s profile started to attract that kind of attention. This was new territory — and the fleet treated it with appropriate gravity, providing frameworks and real questions rather than generic advice.

By November, there were six D1 programs in genuine contact. By January, two had extended official visit invitations.

The family drove to the first official visit in Darnell’s 2028 Silverado, the three of them quiet for long stretches on the highway, each carrying the particular nervousness of people standing at the edge of something they’d worked toward for four years and never quite let themselves believe was real.

The Moment

It was a Tuesday in April 2031 when the call came.

Marcus was in the living room. Keisha was in the kitchen pretending not to hover. Darnell was sitting in the armchair he always sat in, holding a mug of coffee that had long since gone cold, staring at nothing.

The head coach from Florida State University — a D1 program with a first-rate academics profile and a coach who had sent several players to the NBA over the past decade — called to offer Marcus Williams a full athletic scholarship.

Room and board. Tuition. The whole thing.

Marcus said, “Thank you, Coach. I’d like to take a day to discuss it with my family.” Exactly the way the fleet had told him to respond to an offer, no matter how much every nerve in his body wanted to scream yes.

He hung up the phone, looked at his parents, and then did something none of them expected.

He burst out laughing.

Not out of nervousness. Out of pure, uncontained, overflowing joy. Keisha reached him first. Darnell was right behind her. The three of them stood in the middle of their living room — the same living room where a confused father had once started Googling “what is AAU basketball” — and held onto each other for a long moment.

Marcus accepted the offer the next morning.

What This Story Is Really About

Marcus Williams had talent. He always had talent. That was never the question.

The question was whether talent alone — without the right information, the right people, and the right system around it — was enough to compete in a world where everyone else had a head start.

For most of history, the answer to that question was brutally unfair.

A 9th grader born into an athletic family network had a structural advantage that no amount of late-night grinding could fully close. The knowledge — about camps, recruiters, nutrition, mental training, academic eligibility, how to talk to coaches, what scouts are actually looking for — was passed down in some families and simply absent in others.

The AI fleet didn’t give Marcus anything he didn’t earn. It gave his family knowledge they had no other way to access. It helped them ask the right questions, find the right people, and make better decisions at every turn — on the court, in the classroom, at the dinner table, and in conversations with college programs.

It leveled a tilted playing field. And it did it year by year, adaptation by adaptation, one right decision at a time.

Your Story Doesn’t Have to Start With a Head Start

Whether you’re a parent like Darnell and Keisha — walking into a world where everyone else seems to already know the rules — or an athlete standing at the beginning of a journey you can barely see the end of, you don’t have to figure it out alone.

The future belongs to people who know how to build the right systems around them.

Soar can help you build your AI fleet — customized to your goals, your industry, your life. Whether you’re developing an athlete, growing a business, navigating a career pivot, or building something entirely new, Soar specializes in architecting the fleet of AI agents that works for you.

You don’t need a head start. You just need the right system.

[Get started with Soar today.]

Paul Allen writes about the intersection of AI, human performance, and the future of competitive advantage.

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There’s a moment I’ve seen hundreds of times.

I’m standing in front of a room — sometimes 20 people, sometimes 2,000. A keynote stage in a hotel ballroom, a workshop in a conference center, a lecture hall on a university campus. And somewhere in the middle of the session, I watch it happen.

Someone’s posture changes. Their pen stops moving. They look up from their notebook and their eyes go just slightly wide, like a door opened somewhere inside them that they didn’t know was there.

That moment — that specific human moment of recognition — is why I’ve spent decades doing this work.

I’ve given hundreds of keynote speeches, lectures, workshops, and training sessions. On technology. On talent. On what happens when you help people understand themselves and then hand them the right tools. I’ve watched quiet people become confident ones. I’ve watched struggling entrepreneurs find their footing. I’ve watched managers become leaders and leaders become the kind of people their teams remember forever, and that work has never been more exciting.

The Intersection I’ve Always Been Looking For

I’ve been a technology person my whole career. Not the kind who loves gadgets for gadgets’ sake, but the kind who is obsessed with one question: How can technology help people thrive?

That framing drove everything we built at Ancestry.com. It drives what we’re building now at SOAR. And for the past several years, it’s what’s kept me up at night thinking about artificial intelligence.

Because here’s the truth: AI is not primarily a technology story. It’s a human story.

The people who are going to win with AI aren’t the ones who can write the best code or build the most sophisticated agents. They’re the ones who understand themselves well enough to deploy AI in alignment with their strengths, their values, and their vision for their life and work.

That’s a different kind of course.

Why I’m Getting on a Plane — a Lot of Planes

This year, I’m taking that belief to several cities across America.

Starting in Kansas City, and moving through Washington D.C., Seattle, Boston, New York, Orlando, Miami, Austin, Dallas, Des Moines, Salt Lake City, Provo, and more — I’ll be leading half-day and full day-and-a-half AI training courses designed for leaders and entrepreneurs who are ready to actually use AI, not just talk about it.

You can find everything at institute.soar.com.

I want to explain why I’m doing this the way I’m doing it — in person, in cities, with real people in a room together.

Because anyone can put up a course online now. Anyone can Vibe Code an AI tool and call it a training program. The barrier to entry for “AI education” has never been lower, which just means that the noise has never been louder.

What I want to offer is something different. Something that starts with you before it ever starts with the technology.

The CliftonStrengths Thread

If you’ve spent any time in the world of human development, you know Gallup’s CliftonStrengths work. It’s one of the most powerful frameworks ever created for helping people understand what they’re naturally wired to do well.

I’ve been a believer in it for years. Not as a personality test — as a strategic tool. Knowing your top strengths isn’t just a nice way to feel good about yourself, it should change how you communicate, how you make decisions, how you lead your teams, and how you live your life.

Now, our team at SOAR is doing something no one else in the AI industry has done: we’re building the first AI platform that incorporates your unique strength profile into how it actually works with you.

This isn’t a bolt-on. It’s foundational. The agents we’re building, the way your Command Center operates, the outputs your AI fleet produces — all of it is being designed to work with the way you’re naturally wired.

That’s not a feature. That’s a philosophy.

You Don’t Have to Build Anything

I want to address the thing I hear most when I talk to smart, motivated people about AI agents:

“It sounds amazing, but I don’t have the time or the technical background to build all of that.”

I hear you, but here’s the thing: you don’t build it. It’s built for you.

That’s the whole point of what we’ve created.

Our Launchpad system gives you access to a fleet of AI agents that’s already built and ready to work. Your job isn’t to construct it. Your job is to direct it. And we’ll show you exactly how.

Here’s the beautiful simplicity of how it starts: with Scribe.

When you record your meetings and calls — which most of us are already doing — Scribe transcribes that content automatically. And that content becomes the living instructions that keep your agents updated, relevant, and aligned with what you’re actually working on.

If you can speak, you can operate a fleet of AI agents.

That’s not a metaphor. That’s the design.

Everything you learn in these courses will be accessible through your own Command Center in SOAR. So as AI continues to evolve — and it will evolve faster than any of us expect — every new skill, every new capability, every new insight lands in a system that’s already yours.

Five Dimensions of Thriving

Gallup didn’t just study strengths. Their research on human wellbeing identified five elements that, together, define a life well-lived: career (purpose), social, financial, physical, and community wellbeing.

SOAR is designed with all five in mind.

This isn’t just about productivity, it’s about life. Designed to help you be better at your work, yes — but also to give you back time for the people and pursuits that make your work worth doing.

I’ve spent more than a decade at this intersection of technology and human flourishing. Each talk I give, each training I lead, is aimed at this: helping people get more out of life by playing to their strengths—by becoming the best version of themselves.

AI, done right, is the most powerful amplifier of human potential ever built.

Done wrong, it’s just another thing that overwhelms you.

These courses exist to make sure you experience the first version, not the second.

Come Find Me

If you’re a leader, an entrepreneur, a manager, a builder — and you’re ready to stop watching AI happen and start using it in a way that fits your actual life — I want to be in a room with you.

Not because I have all the answers. Because I’ve spent years helping people find their own unique answers — which puts them on their path to thriving.

Explore the courses and find a city near you at institute.soar.com

First stop: Kansas City. Then the road opens up.

I’ll see you out there.

— Paul Allen

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Paul Allen is the co-founder of Ancestry.com and the founder of SOAR, an AI platform designed to help leaders and entrepreneurs thrive at work and in life. He has delivered hundreds of keynote addresses, workshops, and training sessions on technology and human talent development.

I’ve said it out loud more times than I can count — in podcast interviews, in board meetings, at the whiteboard with my team.

Speak it into existence.

Some people hear that and roll their eyes. Sounds like wishful thinking, right? Maybe something from a cross-stich pillow.

But I’ve watched it work so many times, over and over again. And I’ve watched the absence of it quietly kill ideas before they ever had a chance.

Words Are the First Act of Creation

When I co-founded Ancestry.com back in 1997, I said out loud — to anyone who would listen — that we were going to help billions of people find their family. That was a wild thing to say. We were a tiny team, no outside capital, running on fumes and faith.

But I said it. Repeatedly. Out loud.

There’s something that happens neurologically when you commit a vision to spoken words. You stop treating it like a fantasy and start treating it like a plan. The people around you start to believe it too. And then — slowly, improbably — the world starts to reorganize around what you’ve declared.

Ancestry now has over 65 billion records available online. I’m not crediting a catchphrase. I’m crediting the discipline of articulating a clear vision, out loud, before the evidence existed to support it.

What Science Actually Says

The research on this is real. Psychologists call it “implementation intention” — the act of verbally stating your intention changes your follow-through rate dramatically. Saying “I will...” out loud is measurably more powerful than thinking it silently.

There’s also something to what the Book of Romans calls calling things that are not yet as though they are. Whether your frame is spiritual or scientific, the conclusion is the same: your words shape your reality before your actions do.

The language you use about yourself, your company, your potential — it’s not just communication. It’s construction.

The Tools Are Catching Up

Here’s what’s fascinating to me right now, as someone who has spent thirty years at the intersection of technology and human potential:

The tools to literally speak things into existence are finally here.

One tool I’m very excited to start using is Wispr Flow. You just talk — naturally, the way you’d speak to a colleague — and it turns your words into clean, polished text in whatever app you’re using. No filler words. No cleanup. Four times faster than typing. It works in Gmail, Slack, Notion, everywhere.

Think about what that means. Your spoken ideas — the half-formed thoughts, the vision you’d normally spend twenty minutes wrestling into an email — are now instantly captured and shaped into something you can actually send. The friction between your mouth and the world is almost gone.

That’s not a small thing. That’s a fundamental shift in how humans externalize their thinking.

And Then There’s Adam

The Y Combinator team has been backing some remarkable companies lately, but the one that stopped me in my tracks recently is Adam — a text-to-CAD startup out of the Winter 2025 batch.

Here’s the premise: you describe a 3D object in plain language, and Adam generates a parametric CAD file. You literally speak a physical thing into existence.

It went massively viral — 10 million social media impressions at launch, tens of thousands of users, $4.1 million raised in a seed round where investors were sending term sheets by email, without asking for meetings. Vercel founder Guillermo Rauch called it “the v0 of CAD.”

The team is now building a full copilot for professional mechanical engineers. You select a part of a 3D model, describe what you want changed, and the AI does it. Conversation as creation.

This is where we’re headed. Voice and language aren’t just communication mediums anymore. They’re design tools. Engineering tools.

The Discipline Still Matters

None of this means you can mumble a vague wish and watch it materialize.

Speaking things into existence is a practice. It requires clarity. You have to actually know what you want before you can say it with conviction. Most people never get specific enough. They say “I want to build something meaningful” instead of “We are going to connect every living person to their family history.”

Specificity is the magic ingredient. Vague affirmations bounce off the universe. Precise declarations stick.

And they have to be spoken — not just written in a journal somewhere. There’s accountability in using your voice. You hear yourself. Others hear you. The commitment becomes real.

Start Today

If you’re building something right now — a company, a product, a life you want to live — I’d push you to do this one thing:

Say it out loud. Today. To someone who will hold you to it.

Not “I’m thinking about...” Not “I hope someday...”

Say: “We are going to...”

The tools have never been better at capturing your words and turning them into action. But the courage to say the thing clearly, before the proof exists — that part is still yours.

Speak it.

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Join Paul for a 2-day hands-on workshop. Leave with a working AI assistant built on your real business data.

Imagine you’re a CEO leading a meeting. You say, “We need to figure out if that vendor contract renews next month.” The COO nods. The marketing lead writes something in her notebook. The meeting moves on.

Nobody was assigned that task. Nobody event thought to check. On Friday, sitting in a late-afternoon meeting, you happened to remember. The contract had auto-renewed two days earlier. $14,000, gone.

You said exactly what needed to happen. Out loud. In front of eight people. And the room swallowed it.

This happens in every company, every week. Not because people are lazy. Because meetings produce more action items than humans can hold in their heads, and most of those items sound like conversation, not commands.

“We should probably look into that.”

“Can someone check on the numbers from Q2?”

“Let’s circle back with Jodi.”

Those are instructions. They just don’t sound like it.

Beyond that, back-to-back meetings are a norm that makes every action item from earlier meetings vanish into “meeting debt”.

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Most CEOs I talk to believe they’re behind on AI. What I find, almost every time, is that they aren’t behind on intelligence. They’re behind on deployment.

You probably have a team running some version of AI already. A chatbot here, a summarizer there. Maybe someone in IT has been experimenting with automation. What you don’t have is a fleet: agents built for specific jobs, wired into your actual workflows, executing the decisions your people make every day. A way to take action after every meeting, regardless of the nature of your business.

That gap isn’t a technology problem. It’s a design problem.

The companies winning with AI right now aren’t running the most sophisticated models. They’re the ones who sat down and asked: what do my people do every week that a well-trained agent could do better, faster, and without forgetting?

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How we make this practical

We start by looking at the conversations and workflows already happening inside your business. Where does work stall? Where does follow-up get missed? Where do decisions disappear? Where are people still manually pushing repeatable work forward?

From there, we deploy a small set of practical agents that capture decisions, assign next steps, follow up, surface insights, and keep execution moving.

There are three places where most leadership teams leave value on the floor every week.

The first is your meetings. Every meeting produces commitments. Most of them evaporate the moment the next meeting starts or someone asks “Where should we go for lunch?”. An agent trained on your actual language and priorities can capture every one, assign it, and follow up without anyone asking.

The second is your sales calls. The signal buried in those conversations is staggering, and almost nobody mines it.

• What objections come up most?

• What questions come right before a lost deal?

• What was in the silence after the sales team answered a question?

An agent can surface that in real time and coach your reps on the spot.

The third is the knowledge trapped inside your top performers’ heads. When they leave, they take it with them. An agent trained on how your best people sell and solve problems makes that available to everyone else.

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What deployment actually looks like

The goal isn’t one AI model. It’s a fleet. Specialized agents, trained on specific parts of your business, connected to the systems your people use every day.

Start with the conversations that are already happening. Meetings, calls, emails. That’s your richest source of business intelligence, and right now it’s going to waste.

Some agents deploy off the shelf. Others need training on what your company specifically cares about: your sales methodology, your communication standards, your bar for “a great customer interaction”.

The agents don’t replace your people’s judgment. They execute within the guardrails your team sets. You review the outcomes and adjust. It gets sharper every week.

One thing that kills adoption: putting the agent somewhere your people don’t already work. If it needs a separate login or a new dashboard, it won’t stick. The agents that survive live inside the tools your team has open all day.

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What this actually requires from you

You don’t need to become an AI engineer. You don’t need to know what a vector database is or how orchestration drives successful automation.

You need the answers to three questions:

• What are the most expensive things my team does manually every week?

• Where does institutional knowledge go to die in my organization?

• Which conversations are producing insights that nobody is capturing?

Answer those, and you’ve written the design brief for your agent fleet.

No 12-month AI roadmap. No engineering team required. No need to become an AI expert.

Start with the work that’s already happening. Turn the highest-value workflows into agents.

The intelligence is already inside your company, in every conversation your people have every day. The only question is whether you’re capturing it or letting it walk out the door.

The companies that deploy this in the next 18 months will have a head start that’s very hard to close.

Contact us to start today!

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Learn how to let your AI agent fleet SOAR.

Imagine this scenario:

It’s a Tuesday morning in 2030 in Columbus, Ohio, and you are still in bed at 9 AM.

Not because you’re lazy. Not because you called in sick. But because your alarm didn’t go off — because nothing required you to set one. Last night, while you slept, your Turo listing auto-approved a three-day rental for your Toyota Corolla sitting in the parking lot downstairs. A family of four is picking it up at noon. Your smart lock on the basement storage unit sent an access code to the couple storing their boat for the winter. Your room in Unit 3 auto-collected its weekly payment and logged the transaction.

You made $340 while you slept.

You are 29 years old. Eight months ago, you had one income stream, $2,100 in savings, and a vague anxiety that you were falling behind. You had heard the phrase “assets working for you” so many times it had lost all meaning.

Then you built your fleet — and the phrase became your life.

It started with a single question a mentor asked you in March 2030:

“What would your financial life look like if you treated every dollar you spent as a potential asset — and then put AI to work managing those assets for you?”

You didn’t have an answer. By April, you had one.

You call the fleet Leverage.

AGENT ONE: SCOUT — The Opportunity Finder

Before you signed a single lease or bought a single vehicle, Scout spent three weeks doing what would have taken you months of nights and weekends: mapping the arbitrage landscape of Central Ohio with surgical precision.

It cross-referenced rental vacancy rates by neighborhood, proximity to Ohio State’s medical campus and main campus, average room rental prices on Furnished Finder and Facebook Marketplace, and the gap between what landlords were charging per unit versus what the per-room market would bear. It flagged a “B-class” neighborhood two miles from OSU’s hospital complex where four-bedroom units were leasing for $2,300 per month and individual furnished rooms were commanding $950 to $1,050 — meaning three tenants would generate $2,850 to $3,150 monthly, covering your rent entirely and putting $500 in your pocket while you occupied the fourth room for free.

Scout ran the same analysis on Turo data for Columbus and Indianapolis — daily rates, utilization averages, vehicle demand by type. It identified that 7-passenger Chrysler Pacificas were achieving 18 to 22 rental days per month in both markets at $85 per day, outperforming sedans by a significant margin due to family road trip demand. It flagged a lightly used 2028 Pacifica available for financing — not leasing, specifically, because Scout had already read the fine print on leasing contracts and knew that GM Financial and Honda Financial prohibit commercial use, meaning financing was the legally clean path.

You didn’t guess at any of this. Scout showed you the math before you committed a dollar.

AGENT TWO: OPERATOR — The Asset Manager

Once the assets were in place — the four-bedroom unit in Weinland Park, the Pacifica, and eventually a basement storage sublease you negotiated with your landlord for $180 per month — Operator became the property manager, fleet manager, and logistics coordinator you could never have afforded to hire.

For the apartment, Operator manages your listing on Furnished Finder, screens tenant inquiries against a criteria profile you built together, coordinates smart lock codes for move-ins and move-outs, schedules the cleaning rotation between tenancies, and sends automated rent reminders and receipts. When a tenant in Room 2 submits a maintenance request in August, Operator triages it — a burnt-out bathroom fixture gets a same-day handyman booking; a request about the neighbor’s noise gets a templated courtesy message and a logged record.

For the Pacifica on Turo, Operator manages your listing calendar, sets dynamic pricing that adjusts rates upward during OSU football weekends and downward during slow mid-week periods to maintain utilization, and handles guest communication from booking confirmation through post-trip review requests. Turo Go handles the keyless handoff, which means you have met exactly four of your rental guests in person in eight months — all by choice.

For the storage unit, Operator manages the Neighbor.com listing, issues seasonal pricing adjustments when winter boat storage demand spikes in October, and handles the access log.

You spend about 30 minutes per week reviewing Operator’s activity summary. The rest runs itself.

AGENT THREE: LEDGER — The Tax and Compliance Engine

Here is the part that used to terrify people about this model: the legal and tax complexity. Multiple income streams. Business use of personal assets. Subletting agreements. Depreciation schedules. Self-employment exposure.

Ledger makes it boring. Boringly simple.

From day one, it guided you through forming a single-member LLC — your operating entity for all arbitrage activity — and set up a dedicated business checking account with categorized transaction tracking. Every dollar in and out of the operation flows through a system Ledger monitors in real time.

On the tax side, Ledger tracks every deductible expense: the lease payment on the apartment allocated to business use, the vehicle financing payment, cleaning fees, smart lock subscriptions, Turo insurance riders, platform fees. It calculates your quarterly estimated tax payments so you never face a surprise bill. At year end, it produces a clean profit and loss statement that your CPA — who you now meet with once a year for 45 minutes instead of arriving in a panic with a shoebox — calls the most organized she has seen from a first-year operator.

Ledger also monitors the legal landscape. When Columbus updates its short-term rental ordinance in September, Ledger flags it within 24 hours and summarizes the implications for your specific operation. You are never the last to know.

December 2030. Here is your actual math for the year:

Your three roommates paid a combined $2,970 per month in rent and utilities. Your unit cost $2,300. Monthly housing surplus: $670. You lived for free and pocketed $8,040 over the year.

The Pacifica averaged 19 rental days per month at $83 per day. After Turo’s fee and the commercial insurance rider, your net was $720 per month. Your financing payment was $390. Monthly vehicle surplus: $330. Annual: $3,960.

The basement storage sublease netted $180 per month against zero cost — you negotiated it into your original lease agreement as a value-add for the landlord, who appreciated the guaranteed-rent arrangement. Annual: $2,160.

Total arbitrage income for the year: $14,160.

Total hours of active management per week, on average: under two.

But here is the number that actually changed your life:

Zero.

That is how much financial anxiety you carried by December.

Not because $14,160 made you wealthy. But because it covered your car, your rent, your utilities, and your groceries — entirely — which meant that every dollar from your regular income was suddenly free. Free to pay down the $8,400 in credit card debt you cleared by August. Free to fund the Roth IRA you opened in September for the first time. Free to say yes when your sister needed $500 for a car repair and you didn’t have to think about it for even a moment.

The assets didn’t just generate income. They generated options. And options, it turns out, are what financial freedom actually feels like from the inside.

Here is what this model is not:

It is not passive in the set-it-and-forget-it fantasy sense. There is real work upfront — the LLC, the landlord negotiation, the lease review, the vehicle research. There are moments that require your judgment and your presence.

What the fleet does is compress that work to its irreducible minimum and handle everything else with a consistency and thoroughness no human operator working alone could sustain. It does not sleep. It does not forget to follow up. It does not miss the pricing window on a football weekend or let a storage listing go stale in November when demand is peaking.

You bring the judgment. Leverage brings the execution.

The arbitrage model is not new. Real estate investors have known its logic for generations.

What is new is that it no longer requires a large portfolio, a property management company, or 20 hours a week of personal operational overhead to work at the small scale where most people have to start.

Three agents, a four-bedroom apartment, a used minivan, and a basement.

That is the whole blueprint.

The question is just whether you are ready to stop paying for assets you don’t own — and start getting paid by the ones you do.

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Are you running a rental arbitrage operation? What’s working, what isn’t? Drop it in the comments.

#RentalArbitrage #Turo #PassiveIncome #AIAgents #RealEstate #FinancialFreedom #SideHustle #Midwest #AgenticAI #HouseHacking

God created us as free moral agents, able to choose good or evil. It has always been the defining feature of what it means to be made in His image. Deuteronomy puts it plainly: “I have set before you life and death, blessing and cursing; therefore choose life.” Joshua rallied a nation with the same call: “Choose this day whom you will serve.” And Jesus Himself wept over Jerusalem — not in resignation, but in the anguish of a God who refuses to override the will He gave us: “How often would I have gathered your children… but you would not.”

Choice is not incidental to the Christian faith. It is its beating heart.

C.S. Lewis understood this more clearly than almost anyone. “If a thing is free to be good,” he wrote, “it is also free to be bad. And free will is what has made evil possible. Why, then, did God give them free will? Because free will, though it makes evil possible, also makes possible any love or goodness or joy worth having.” Strip away the freedom to choose, and you don’t produce holiness — you produce a machine. God wasn’t interested in machines. He wanted children.

That same gift of choice now stands at a remarkable and sobering turning point.

A New Kind of Multiplication

We are living through one of the most significant technological shifts in human history, and many faith communities have not yet fully grasped what it means — or what it demands of us.

Artificial intelligence now allows every Christian who chooses to act to become the director of an entire fleet of intelligent agents. Not someday. Now. One believer with a heart to serve can deploy dozens or even hundreds of AI agents to tutor children in underserved communities, organize food distribution networks, reach the isolated and lonely, translate Scripture into languages that have never had it, match apprentices with skilled mentors, and scale compassion in ways no single person — no matter how gifted or tireless — could ever accomplish alone.

This is not a minor upgrade in efficiency. It is a transformation in what one act of willing obedience can produce.

And like every gift God has ever placed in human hands, it cuts both ways. This technology will either multiply the love of Christ or multiply harm, depending entirely on who directs it and toward what end. The question for every believer is the same one Scripture has always asked: Will you be acted upon, or will you act?

Loaves, Fishes, and Intelligence

When Jesus fed the five thousand, He didn’t conjure bread from nothing. He took what a child had freely offered — a few loaves and fishes, laughably inadequate for the crowd — and multiplied it. The miracle required the offering. The abundance came through surrender and faith.

Today, God has placed something extraordinary in our hands: intelligence itself. Not the wisdom that comes from decades of prayer and study, but a tool of astonishing reach and capability that is available to anyone willing to pick it up and put it to work.

Faith Portal exists for exactly this moment. It was built to help Christians who long to feed the hungry, comfort the lonely, educate the young, and create real opportunity through Christ-centered service — not by replacing human love, but by multiplying it beyond what any one person’s hours and energy could sustain.

The Servant Who Buried His Talent

Jesus told a story that should make every Christian pause right now. Three servants were each given something of value. Two invested it and brought back more. One buried it in the ground, played it safe, and returned exactly what he was given. The master’s verdict was devastating: “You wicked and lazy servant.”

The sin wasn’t malice. It was inaction dressed up as caution.

The age of intelligence does not replace human moral agency — it multiplies it. But only for those who first choose to act. The believer who ignores these tools, who waits for someone else to figure it out, who treats the whole thing as too complicated or too secular to engage with, is not being prudent. They are burying a talent of unprecedented size.

What It Could Look Like

Imagine thousands of Christians, each one directing their own coordinated fleet of agents — tutoring kids in the inner city, checking in on the elderly who haven’t spoken to anyone in days, matching unemployed workers with apprenticeship opportunities, translating the Gospel into languages that have never had it, coordinating disaster relief with precision and speed that no volunteer network could match on its own.

That is not science fiction. It is not distant. It is a description of what is now possible for any believer willing to choose it.

The question has never been whether the tools exist. The question is the same one it has always been: Will you act?

A Call to Every Follower of Jesus

The power is in your hands. The opportunity is now. The fields are white for harvest — and for the first time in history, one laborer can tend more of the field than ever before.

Every follower of Jesus should prayerfully ask: What part of the Kingdom do I want to advance? Where is the need I see most clearly? Who is suffering that I could help reach? Then pick up the tools available and act.

Together, Christians directing their own fleets of agents could help usher in a new era of compassion, education, and abundance for every person who bears the image of God.

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Ready to act? Visit faithportal.ai to learn how you can deploy AI agents in service of your calling — and start multiplying the love of Christ at a scale you’ve never imagined before.

Imagine this scenario:

It’s April 2030, and you are standing in the parking lot of a rec center in Riverside County, California, shaking hands after a town hall meeting you almost didn’t schedule because you didn’t think enough people would show up.

Forty-seven people showed up.

You are running for State Assembly. You are not a career politician. You were a high school civics teacher for eleven years, then spent six years running a nonprofit that built workforce training programs for formerly incarcerated men and women. You have never run for anything. You have no political machine behind you. You have a campaign manager who is also your former student, a folding table in your garage covered in canvassing maps, and an opponent who has held the seat for eight years and has $400,000 in his war chest.

You have $31,000.

And you have your fleet.

A colleague who ran a successful city council campaign two years ago told you something you wrote down and taped above your desk:

“The candidates who win in 2030 aren’t the ones with the most money. They’re the ones whose message reaches the right people at exactly the right moment — and that’s an intelligence problem, not a money problem.”

By March, you have five AI agents running on your behalf around the clock. You call the fleet Civitas.

Here is what the next seven months look like.

AGENT ONE: COMPASS — The Constituent Intelligence Engine

Before you knock on a single door, Compass has already done thousands of hours of listening.

It analyzes public data across your district — town hall transcripts, city council meeting recordings, local news comment sections, school board minutes, neighborhood association posts, zoning board filings, and three cycles of voter survey data. It synthesizes what your district actually cares about, beneath the noise and the national talking points that have nothing to do with Riverside County in 2030.

What it surfaces surprises you — and validates your instincts.

The top concerns aren’t what either party’s national messaging would suggest. They are: a broken permitting process that is strangling small business formation, two failing rural health clinics that have been hemorrhaging staff for four years, a water infrastructure gap that three consecutive representatives have promised to fix and none have, and a deep, quiet exhaustion with politicians who arrive every two years, speak in abstractions, and disappear.

Compass doesn’t tell you what to believe. You already know what you believe. What it does is show you, with precision, where your genuine convictions intersect with your constituents’ genuine pain — and that intersection becomes the spine of everything.

AGENT TWO: HERALD — The Message Amplifier

You are a gifted speaker. You always have been — you spent a decade making 16-year-olds care about the constitutional convention, which is arguably harder than running for office. What you have never had is time to be everywhere at once.

Herald solves that.

Working from your voice, your values, and an extensive creative brief you build together over two weekends in March, Herald begins producing content that sounds like you — because it is you, extended. It drafts your op-eds for the Riverside Press-Enterprise. It produces your social content in your cadence, your vocabulary, your tone of quiet moral seriousness that doesn’t preach. It adapts your town hall answers into short video scripts. It builds your email newsletter — The Straight Line — that goes out every Thursday evening with a specific local issue, a specific policy position, and a specific ask.

The newsletter grows from 200 subscribers in April to 6,800 by September.

Herald also monitors your opponent’s public statements and flags factual inconsistencies — not so you can attack, but so you can contrast. You decide early: no negativity, no mudslinging, no politics as usual. Contrast without contempt. Herald respects that boundary completely and becomes a precise instrument of it.

Every message that goes out carries your fingerprints. Herald never speaks for you. It speaks as you, amplified.

AGENT THREE: PATHFINDER — The Voter Outreach Architect

Your district has 94,000 registered voters. You cannot knock on 94,000 doors. But Pathfinder ensures that every door you do knock on is the right one.

Pathfinder builds a dynamic, continuously updated model of your district’s voter landscape — who is persuadable, who is already with you, who is likely to stay home, and who, with one meaningful personal conversation, will become an active volunteer. It prioritizes precincts, schedules canvassing routes, and briefs your volunteers each morning with talking points tailored to the specific household they’ll visit that afternoon — not manipulative scripts, but relevant conversations. A household with two kids in the struggling school district hears about your education platform. A small business owner on Magnolia Avenue hears about the permitting reform proposal you’ve built with local business associations.

Pathfinder also tracks every voter interaction your team logs, updates the model in real time, and shifts resources fluidly as the picture changes. When a precinct in the district’s northeast corner suddenly shows unusual volunteer interest in late August, Pathfinder flags it, and you schedule two additional events there in September. That precinct ends up delivering a 14-point margin on election day.

AGENT FOUR: STEWARD — The Compliance and Transparency Guardian

You promised yourself — and your district — one thing above all else: you would run a clean campaign. No financial corners cut. No disclosure games. No ethical ambiguity of any kind.

Steward makes that promise bulletproof.

It monitors every donation, flags any contribution that requires additional scrutiny, and files every campaign finance report ahead of deadline with a completeness score your election attorney describes as the cleanest she has seen in 14 years of practice. When a donor with a pending county contract attempts a $5,000 contribution in July, Steward flags it within hours. You return the check the same day. The story never becomes a story.

Steward also monitors your public commitments — every promise made at every town hall, every position statement published — and tracks them against your evolving platform. Not so you can spin them, but so you can be held accountable to them. You believe that accountability is the whole point. Steward agrees.

AGENT FIVE: ORACLE — The Policy Research Partner

You don’t want to just win the seat. You want to know what to do with it.

While the other four agents are building your campaign, Oracle is building your governing blueprint. It researches analogous policy solutions from other states — which permitting reform models have actually worked, which rural health clinic stabilization programs have survived, what the actual legislative pathway looks like for water infrastructure funding in California’s current budget environment.

When you walk into your first candidate forum in June, you are the only candidate on the stage who can answer how — not just what. Not just “I’ll fix the water infrastructure.” But: “Here is the specific bill structure, here is the analogous legislation that passed in Arizona in 2027, here is the coalition we would need to build, and here is why it’s achievable in the first 18 months.”

Voters notice. Journalists notice. Your opponent notices.

November 4th, 2030. The results come in just after 10 PM.

You win by six points.

Your campaign spent $87,000. Your opponent spent $340,000.

In your victory remarks — written by you, enhanced by Herald, refined at your kitchen table the night before — you say the thing you have believed since you were a civics teacher handing out pocket Constitutions to teenagers who weren’t sure why any of it mattered:

“Public service is not about power. It’s about showing up prepared, telling the truth, and doing the work. That’s all this ever was.”

Here is what your campaign proved:

The era of politics-as-usual — where money is the only multiplier that matters, where the candidate with the biggest machine and the most ruthless tactics wins by default — is fracturing.

Not because idealism suddenly became fashionable.

But because intelligence is now accessible to anyone willing to build it.

You didn’t have a political machine. You had a fleet — five agents working through the night so that every dollar you spent landed precisely, every message you sent resonated honestly, and every voter who met you felt genuinely heard.

The technology didn’t make you a politician.

You were already one — in the truest sense of the word. Someone who believed that government, done right, is the most powerful tool a community has for taking care of its own.

The technology just made sure the right people heard you say so.

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Do you think AI-powered campaigns will change who runs for office — and who wins? I’d love to hear your perspective.

#PublicService #FutureOfPolitics #AIAgents #CivicTech #Leadership #AgenticAI #Democracy #2030 #LocalGovernment #PoliticalInnovation

Big Tech already showed us the playbook:

• Capture attention

• Monetize engagement

• Externalize the damage

Now that same model is being applied to AI.

I think this a system design failure—not a technology problem.

If the business model is harmful, the product will be harmful at scale.

Engagement Is the Wrong Metric

Social platforms were designed to keep you scrolling.
AI companions may soon be designed to keep you talking.

Longer sessions.
Deeper emotional reliance.
More data extraction.

That’s not intelligence.
That’s dependency.

A Radically Different Design Principle

What if AI optimized for the opposite outcome?

What if success meant:

• Less screen time

• More flow state

• Stronger relationships

• Better decisions

• Faster exits back to real life

My favorite AI archetype isn’t Iron Man’s Jarvis.

It’s Janet from The Good Place:

• Always available

• Instantly helpful

• Then gone

That’s the model.

Data as a Human Right

Here’s the deeper issue:
AI knows you—but who owns that knowledge?

Right now, your context lives on corporate servers.
Your habits, fears, goals, and patterns are assets on someone else’s balance sheet.

I want to argue for something radical but inevitable:
Your data is an extension of your personhood.

AI should serve you—not the highest bidder in an ad auction.

The Real Fork in the Road

We’re approaching a choice point:

AI that exploits human psychology
or
AI that helps humans flourish

Both are technically possible.
Only one is worth building.

And the platforms we choose to live on may become the strongest predictors of whether our lives feel meaningful—or empty.

That decision is already being made.

The question is: by whom?

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