Every general-purpose/horizontal technology charts a familiar course between early excitement and mature, scaled deployment. At first, euphoric money floods the zone to build the infrastructure and explore novel possibilities, creating paper wealth and paying for the buildout/installation.

Eventually every bubble burst (railways in 1847 and 1873, utilities in 1929, fiber in 2001, crypto in 2018) leaving behind critical infrastructure for a next generation of companies and investors to build newly possible companies.

There is euphoria and mania on the way up, and a brutal hangover after an inevitable crash before the real work starts. Clearly we are in “The Frenzy” today.

The refrain is always “it’s different this time.” But what’s different specifically - the scale, the speed, the sophistication, that it’s finally coming for knowledge work? All in some sense true but orthogonal to the point of how businesses work and who “decides.” That is, each of those is a claim about the supply side (fast, cheap, high quality).

And value capture is not principally gated by the supply side (the vendors). It’s gated by the customer prerogative: how long it takes a hospital, a bank, a law firm, etc. to refactor around the new tool. A better model doesn’t buy you a faster customer because the binding constraint doesn’t move. The cycle of diffusion is slow, even if its onset is sudden.

We are long-term bulls. AI is going to break (is breaking) the economics of industries everyone assumed were untouchable. That is a big deal - obviously. Much of the market treats that as a sufficiently investable idea unto itself. It is not, at least not for us.

Accepting that the economics break doesn’t tell us enough about where to put the next dollar. The real questions come after.

• Who is organized to rebuild the broken economics and win?

• Where does the value sit long term?

• Who can defend it once they’ve got it and what does it cost them to hold?

Everything short of answering those is a trade. Trades can make great money if you know when and how to get out. But that’s not our bag; we want to call the shot on what is durably valuable along the way and after.

Historically, the biggest long term winners have always been the consumers and users of a technology, not its developers:

• Steel producers and oil majors vs cars

• Internet service providers vs internet platforms

• Electric utilities vs electrified industry

• Datacenters vs AI, ironically

Consumer not vendor surplus is the historical norm. And given our hold period and presumption of illiquidity, the long view is all we have.

And it’s recursive: the market cap of steel today is a fraction of the market cap of planes and cars which is a fraction of the market cap of all the businesses made possible by planes and cars. Same for rare earths vs chips vs the computerized economy (functionally, global GDP).

So we want to back things that are newly possible using AI infrastructure, talent, and technology which also conform to our ideas about what makes a good business (terminal value).

Increasingly, we think/see/can prove that AI brings businesses closer to selling outcomes not workflow. The best businesses have always sold outcomes and now there’s more surface area to do that in big markets. That’s where we’re largely focused, across B2B and consumer, business models, and markets.

We are looking for the planes and the cars of AI (and the businesses relying on the planes and the cars) that conform to our basic rubrics for quality (durability, defensibility, and value prop).

To the users go the spoils.

Big Things Take Time

Consistent feature, kind of suprising, worth remembering: time to first revenue is rarely a meaningful predictor of future growth rates.

But once you get going you gotta really go!

Elsewhere

• Valuing AI Harnesses - Tomasz Tunguz

• Style war: inside Wall Street’s battle to revive J Crew

• The ‘vibe shift’ was a leveraged buyout - by Vincent Bevins

• It’s time to build software - Phin Barnes

• Why would you ever invest in consumer at pre-seed? - Nathan Lee.

  • Nathan and I have been debating this for the last couple weeks. I’m not completely sold yet but he thinks he’s onto something.

Last week I shared an rough way to measure the relative importance of revenue, growth, and narrative in fundraising right now.

Rates (how fast) and levels (how much) each matter and can compensate for one another. If growth is 0 then great topline doesn’t mean anything. If topline is near-zero, great growth doesn’t mean much.

And the more complex your narrative and story is, the harder it is for people to pay attention to the momentum. Simple, powerful stories let great numbers shine. Complex stories are drags on the internal proof/momentum/traction you’ve created.

If that is something of an answer to/heuristic for “when should I raise,” it’s definitely not sufficient for “how do I raise” or “what do investors want.”

Right now no one knows and predicting the success of a fundraise feels often impossible.

This is basically all anyone at seed (companies and investors) are talking about right now.

It’s hard to look a founder in the face and say “no one cares about your company”. But at some level the whole market has turned into “team plus TAM” analysis.

So the gate/bar to capital is not just “high” but actually rather specific:

One friend who works in growth summited it up: “If we can’t see a path to a $20 billion company with you as the emerging winner, we can’t do it at all.”

Another friend simplified it further: “Is it a market I need to be in, and do you seem likely to win that market?”

• You are competing for dollars with every other “tech” asset in the world, many of which are already represented within the funds you’re talking to

• One of the hardest things is “educating” vs “convincing” an investor about an opportunity. Convincing almost never works, at least not in this environment. If they’ve considered it and think/know they don’t want to be in it, it ain’t gonna happen. If it’s novel to them (or novel to the world) you stand a shot.

In the past you might have said: “Well, there’s capital in my vertical, and that capital has to invest in something, so all I need to do is be the best company in my category and the people who need to invest in my category will invest in me.”

That’s no longer true. It’s increasingly common for people to abandon prior categorization or any categorization at all.

• The fintech investors don’t want to be fintech investors.

• The healthcare investors don’t want to be healthcare investors.

• The consumer investors don’t want to be consumer investors

Everyone just wants to be in the current thing they know they need to do, whatever category it might be in.

Capital is an input, but it’s not the desired output/prime constraint to business building, at least for truly idiosyncratic, asymmetrically risky startups

This kind of chart is obviously a little silly given the people who frequently post them, but it isn’t wrong.

Great companies get built outside of the obvious box because they are exceptional on some other criteria and find sufficient true believers to capitalize them.

For now, you need to either find true believers, educate the market, or find a way to successfully attach yourself to the things people know they need to do.

Read More

• No Revenue Is Enough Revenue

• Narrative Is the Interface

• Martin is right about “non-consensus”

“How much revenue do we need to raise (a Series A)?”

A few years ago, when I started investing, I could have said “get to $1M ARR with good growth and the Series A will materialize.” Storytelling mattered of course, but it was an easy and functional (good enough) approximation to say that if you’re building in a good market, with a good team, and get [this much] traction, the round probably comes together.

Then the bar increased (maybe $2M). Then it went up more ($3M). And now it has just materially changed, rather than merely moved.

Now there really is no answer; it’s a dynamic set of inputs rather than a simple target. Seed investors are supposed to be this bridge to downstream capital and have this answer to shepherd founders but we don’t know, or at least don’t have anything simple/concrete to share.

The outcomes have gotten bigger, the dollars have gotten bigger, the cycles have gotten faster. So early stage is more uncertain and no one wants to be in anything but “the obviously great” thing. Obvious is really key here, and the things that make something obvious are big, fast, and simple.

In the simplest terms everyone is looking for expected value (can this be a public company, which really means $20B+ of semi-rational valuation) and category potential (is this a category worth winning). That’s not super useful, or at least not sufficient, in immediate normative terms beyond making sure you’re in an opportunity that can support such an outcome.

After all, the A investor needs to believe you can attract a B. And the B investor needs to believe you can attract a C. And the C investor… No one wants to make that bet when they have infinite dollars and time to sit on the sidelines for the “can’t miss” round.

So - at least when it comes to companies that will raise on the basis of commercial traction at all - this is the rough formula I’ve come up with to explain how the market works and what you need to raise a Series A:

Rates (how fast) and levels (how much) each matter and can compensate for one another. If growth is 0 then great topline doesn’t mean anything. If topline is near-zero, great growth doesn’t mean much.

And the more complex your narrative and story is, the harder it is for people to pay attention to the momentum. Simple, powerful stories let great numbers shine. Complex stories are drags on the internal proof/momentum/traction you’ve created.

The more logical leaps you have to take in either explaining what you are (this is why people like X for Y framings) or explaining what you’re doing (this is why people like “we went N to M in Z months” to understand traction) the harder your job becomes and the less compelling the story is overall. As soon as you’re justifying the size of your opportunity, you’ve probably already lost. The simplest stories are the ones we’ve all already agreed on.

The bar to clear will move around in time and from investor to investor, but this is the rough measuring stick.

The normative advice here is really about framing yourself as simply as possible with the goal of becoming a financial earworm, meme, or cognitive virus. And of course, grow.

Addendum

For someone out there there’s a great opportunity to lead $8-15M Series As and basically get your choice of every asset in that category, if you can either 1) underwrite the rest of the market waking up to it later or 2) have some measure of capital independence (not necessarily FCF+).

Read more

• Startups are just stories about the future

• Do something important, quickly.

Short windows

The 90-day exercise window and the inability to do cashless exercise are hostile and undermine a lot of the promises - explicit and implicit - that companies make to talent.

First, this compensation scheme was based on outdated assumptions, namely that startups get liquidity reasonably quickly (four to seven years instead of 10 to 20) and cheaply (exit values in the tens and hundreds of millions instead of billions).

When the time frame is pretty short, it’s reasonable to expect that you’ll actually be there for the liquidity event vs exercising and holding forever.

And when the dollars are pretty small / the intermediate values are pretty low, exercising your options may not actually cost that much. That’s obviously not true today.

Second, the whole pitch of accepting less cash for equity only works if you actually get the equity. It’s premised on the idea that you share in the upside of the company and forgo some short-term guaranteed compensation in exchange. If you put in years of good work and service but are ultimately unable to hold on to the equity, you have basically just worked for discount rates with no upside.

This is not academic.

90-day exercise windows force people to make these super high-stakes decisions quickly and under a lot of pressure. The lack of cashless exercise means that they are often not receiving the equity that they earned but rather paying for it twice, both in the form of deferred/reduced cash compensation and in the actual strike price (three times with AMT).

It’s super common for someone to do years of good work at a company and ultimately walk away with little or none of their equity, usually because exercising was too expensive and the liquidity prospects too uncertain. They’ve already bet with their time/opportunity cost and should retain the option - that’s how they were paid! This is a failure of an outdated comp system compounded by long and overfunded private hold periods, not a clever strategy to minimize option pool outflows.

If someone is vesting equity instead of taking larger cash comp, it’s a fair deal. It is unfair to use legal maneuvering to effectively claw back the hard-earned compensation of ex-employees in good standing.

The beauty of things like vesting schedules and equity cliffs is that it makes it possible to take risks on talent. The challenge of exercise windows and cash-only exercise is that it makes it really hard for talent to take risks on companies (and benefit when they do).

Much like four-year vesting schedules (which are bad and should be longer), these are just conventions that nobody has any real incentive to go against or change up until they really have to. But it winds up being a big gift to the biggest, most late-stage companies that can offer their employees liquidity that everyone else doesn’t. Just lack liquidity, but rather effectively lack equity compensation at all/in many cases

An obviously better solution would be to move to either much longer exercise windows and/or net/cashless exercise for departing employees in good standing. You can reward loyalty by tying the length of the exercise window to the length/years of service at the company and/or gate the option for cashless based on years of service.

If there’s a “get” here it’s that you should be firing people faster if they’re not performing - giving out equity and letting it cliff/vest ~should~ be expensive and high consideration. And of course, the optimal compensation package is a long vesting schedule coupled with a long exercise window. Seems fair!

I was really happy to hear from a couple (Slow) companies that are experimenting with this:

• Backplanes does tenure minus one year for exercise windows (so a 4 year employee has 3 years to exercise)

• Craftwork has a straight up 10 year exercise window

I’d love to work with any founders on how to rethink the details of their equity compensation plans to make this better.

Grocery Slopulism

Good government should always experiment with ways to enrich the lives of the governed and extend a hand of compassion to those in need. The status quo is not optimal just for being the default.

But the discount grocery stores underway in NY (“Mamdani-Marts” if you want to get partisan and hacky) are not the right way and won’t work, at least not to the extent that their purpose is to help people efficiently. They do/will work great as politics.

Groceries are not expensive because of corporate greed. The gross margins across a bunch of big box grocers are ≈25% (profits are more like 2%). And these are the stores with the most efficient operations/economies of scale and pricing power. It’s inconceivable that a small, city-run grocery store can beat out their buying, supply chain, staffing, etc.

In real terms, food has gotten MUCH cheaper: in 1960 Americans spent 14% of income on groceries. That’s down to 5% today. That is true for all but the left-most tail of the distribution (the poorest people whose incomes have stagnated and spend 70% of income on food) but the stores won’t be targeted enough to do the most good - there is no means testing.

And to the extent that grocery prices are expensive/growing in real terms at all, it’s because of upstream factors like rising labor costs and production disruptions/supply shocks that are scarily becoming more common (Trumprhea, Avian flu, Brazilian coffee drought, etc). That usually spikes prices in a particular category, not across the whole basket.

The municipal grocery stores will focus on staples (bread, milk, pantry items, etc). These are already the lowest margin (sometimes negative margin!) items a grocery store sells. Grocers know you pick based on staples so they drive traffic with staples and drive margins with things like fresh departments, hot food, and snacks (40-60% gross margins) which these stores mostly won’t carry.

So the city is going into a low gross margin business, focusing on ONLY the lowest margin products, and believing it (or its contractors) can operate more efficiently with no pricing power or economies of scale relative to incumbents. The proposed 30% discount is more than the entire gross margin of a normal grocery store before even accounting for taking out the high margin items.

The only way to make the city-back groceries work is to heavily subsidize it and try to cover that up with accounting tricks like stripping out the costs of free rent and tax breaks. The city-backed grocery stores will lose a bunch of money on every sale.

But this is fine! Governments don’t exist to make money. They are not businesses, even when we pay them for services. The post office (USPS) serves a civil purpose (delivering mail to every American); it is not UPS or fedex (making money by delivering packages).

So if we’re comfortable “losing money” to feed the needy (I am!) why would city owned grocers be the right way to do it? Opening a grocery store is not some magic hack to solve poverty or food insecurity; it is just one (bad) option of many (better ones) to invest in social programs and help people.

That being the case, shouldn’t we weigh this against other opportunities to invest the city’s finite resources on the basis of efficacy and outcomes, not just aesthetics and ideology? Why is a grocery store which needs to built and staffed (and lobbied for - expending political capital as well as dollars) the best delivery mechanism to subsidize low income New Yorkers?

It isn’t.

If the goal is to help the most people most efficiently there is no good argument for this leaky pipe when we could just increase food subsidies through existing channels like EBT supplements. Experiments, however bold, need to be honestly and rigorously conducted.

But it’s great politics and good theater to lay every problem at the feet of an omnicause. And giving people money is too invisible and boring to be a signature policy. So this is what we’re getting.

New York shouldn’t descend into slopulism.

I made a financial model

I made a financial model for a portfolio company. Unremarkable on its own. But the “how” was fun and cool, at least to me. Rather than going right into it, I wrote an 800+ word prompt with detailed instructions on the goals, style notes, tab by tab architecture, etc., along with some open questions to home in on before building. All told I got a fairly sophisticated build pretty quickly and with far fewer turns of revisions than it would otherwise take (and yes I spot checked it). Tokenminning!

It felt like the closest I’ll come to experiencing what a good engineer does with AI: working within a domain of excellence (or at least competence) and using AI to operate at a high level with my architecture and “design” choices rather than playacting as more sophisticated than I really am (what it looks like when I “code”).

Annoyingly Claude can’t really do XLookup and instead relies on IndexMatch which is not my preferred formula... C’est la vie.

Elsewhere

• General Catalyst is lucky to have Reggie... very sophisticated thinker about media right now.

• I just finished Avery Trufelman’s gear podcast, which is ostensibly about the history of the outdoor industry but winds up turning into a history of military dress and culture (as you’ll see - deeply intertwined!). I like Avery and am excited for what she’s working on with Derek Guy. Thanks Zoë for turning me onto this pod.

Open Models

Oligopoly is bad for startups. If intelligence is expensive and the returns/margin accrue to the foundation model labs then we will basically see the current productive base accelerated but not transformed, which is good but only as a difference of degree.

But if intelligence is abundant and free, we can see a difference in kind - the most interesting AI businesses are predicated on some combination of model diversity, local models, free intelligence, etc.

Open models are better for the broader (more decentralized/long tail) innovation ecosystem and especially for the app layer. And the vast majority of companies are “app layer” in that they consume and use inference, intelligence, (language) models rather than develop models or manage infrastructure.

The pro-market position is obviously to encourage competition on price and quality, not regime coziness.

America should have an open source model ecosystem and the returns on intelligence should go to its consumers/users, not just its creators.

Open models are only decelerationist (discouraging investment and recursive improvement) insofar as the leading labs have structured/capitalized themselves on the basis of oligopoly and protectionism. A fiercely/maximally competitive market for intelligence is better than the captive world we’re otherwise moving to.

The most pro-social, pro-innovation, pro-market outcome is for model development and infrastructure to be a fiercely competitive commodity business not a (gross) margin rich oligopoly propped up by government mandates as quasi-GSEs.

Lots of the biggest VCs will reflexively be open models them because 1) Trump is against them 2) the American foundation model labs are against them - most investors reflexively kowtow to the powerful/root and side with winners. To their credit, a16z seems to be saying the right thing here.

The best version of venture should be an index of the entrepreneurial innovation economy, not civilization clash of kings.

Oligopoly is also bad for our politics/political economy. We are seeing state capture by the foundational models and business - a new unitary body at the further detriment of our democratic market system.

If our labs become state backed and controlled they’ll no longer really be “American” in any meaningful sense - and neither will we.

The worst case scenario of a ban on open source (chinese) models is that LLMs/intelligence winds up like energy. As the rest of the world moves to the electric stack and lithium ion supply chain, America doubles down on oil, losing an opportunity for global leadership to enrich regime-proximate-toadies. We’re going to fall behind on energy abundance, fail to develop our own critical industries/supply chain, and ultimately wind up losing soft power to China.

That can’t happen in AI.

I made a new CRM

I spent the last week and ≈$2k building a pretty slick replacement for a $10k SaaS product with Fable while consolidating together a bunch of vibe coded side projects that I’d built to supplement the SaaS we’re now churning from. All told, I’m gonna end up:

1. saving a few shekels/year (savings TBD because there’s now variable spend)

2. using a product much more tailored to what I actually need with flexibility to change it

Will I regret this? Maybe! I definitely wouldn’t want to have to support multiple users or try to commercialize what I’ve done.

Nevertheless, this was a lot of fun and I might write more about it since I’m using a ton of different services and tools.

Nathan Made a Crime Simulator

He started working on this at Slop Con and am glad he picked it back up at Slow. He’s been interested in the idea of “performative software”

Not all expressions have to necessarily be intentional, because personality is not. My point is that software has finally been added to the list of mediums for us to use. So create more performative software, and perhaps you’ll figure out what it meant later (if ever). The worst thing that happens is more people catch on.

Fun ideas - funny execution. Let’s see where it goes.

Why you should (maybe) send investor updates

If you want my opinion, advice, or help (and you may not!) I need context. Context is very hard to acquire on a point in time basis. I need time series data (quantitative and qualitative) to have a opinion beyond “Yoni’s general frameworks and shit-shooting”. This goes for all your investors too, obviously.

Investor updates are obviously useful for pushing to the top of mind/arming me to advocate for you whether that’s to downstream capital or to potential hires (and again you may be justified in not caring).

You can preempt lots of anxious and irregular but frequent Q&A by sending information. If you have a cap table to manage, you’d much rather send one email than do lots of 30 minute meetings just to transmit info.

Finally, investor updates are a good way to measure for yourself if you’re closing your books well, on top of your numbers, and hitting your plan. You may know your numbers and have that muscle already (great, in which case sending an update is easy) or not care to develop it (bad, in which sending an update is not necessary because your company probably won’t work).

If you are gonna send updates, here’s how to do it well:

• Don’t do a whole long thing. Short is good. Timebox yourself on how long you spend writing If it’s really hard to get your numbers together that’s a separate yellow blinking light which itself is worth reporting.

• Do it consistently. Monthly is better than quarterly but weekly is too much without good reason.

• Numbers are better than words wherever possible.

• Don’t market to your insiders. Things will be messy and hard. Don’t self flagellate but be honest.

• You’re allowed to kick people off the updates if they are annoying and create more work for you with follow up questions or if you suspect they’re not good stewards of the information.

Elsewhere

• Phoebe acquired Alden’s assets and customers. This is what it looks like when a winner starts emerging in a category.

• There is a real/seeming dearth of recruiting firms focused on non-technical hires, especially slop cannons (high tool use generalists) - or at least I don’t really know them. I’ve had multiple companies ask me for help in finding these people. Send me recs and/or start a boutique.

• Pangram is integrating with Substack for AI detection. There’s a great opportunity to create an “AI safety and research lab” that builds self improving bot-detection-defeating-agents in order to protect us from bots which defeat bot detectors. And it seems like an obvious objective benchmark to hillclimb for anyone willing to spend some money on Pangram tokens and inference. I’m mostly kidding but also I would fund this.

I’m back. We did ≈65 miles of the Tour du Mont Blanc (not Dolomites!) which was awesome along with some time in Amsterdam. It was the most unplugged I’ve been in years and the hiking trip was really special: backpacking place to place to eat pasta and drink beer in the most beautiful locales I’ve ever seen.

CEO Side Projects

No one batted an eye that Chesky might have been announcing an RWA project with a slop post1 because every enterprising CEO needs to be founding more/new/multiple companies.

Vlad Tenev, Brian Chesky, Brian Armstrong, Daniel Ek, etc. others are all now doing fully capitalized, fully staffed companies as side projects. The extreme of course is Elon and Sama.

These aren’t merely hobbies - these guys are founding and funding companies that presumably take up significant amounts of finite and highly valuable time, attention, and energy.

Why do they do this and why are they “allowed” by boards and shareholders when it obviously takes away from what should be a full time job (running a multibillion dollar company)?

The first, most obvious answer is dual class shares. You literally can’t stop them. Boards and shareholders are largely passive advisors.

But really it’s about executive retention and status games.

Status games: this has long been a thing but some companies are just better suited to capture side projects internally (Google, FB, Amazon, etc). And now that those businesses have created the culture, everyone wants the status marker of a longevity or AI project (imagine the shame of only having an app at sun valley).

And SV doesn’t really do philanthropy and the arts in the way Wall Street does so this takes the place of say joining the board of the Met.

Retention: If you have a great CEO - every board should believe it has a great CEO - and make them choose between new and exciting and hum drum you risk losing them altogether.

Whether or not it’s bullish or bearish for a company mostly depends on how good and how critical the CEO is, but maybe not in the direction you think

• The all star CEO who is 100% essential to the success of the firm is being retained to work at a higher level of abstraction. Bullish!

• The mid or inessential CEO is preventing someone more locked in from taking the seat. Bearish!

After all, if the job of a ceo becomes largely vision, the best people will eventually operate at a level of abstraction such that one company (or one business in the case of 2010s web/app companies) can’t contain and obsorb all their vision

Liberty and Security

Shot spotter, traffic cams, bank SARs, etc. - there are legitimate tradeoffs between safety/security and privacy in every surveillance technology. Disliking them doesn’t necessarily make you a terrorist and supporting them doesn’t necessarily make you a totalitarian (but it can!)

Obviously these things can prevent and solve crimes (improving safety) and obviously they do so by infringing on privacy with the potential for abuse.

If you’re unwilling to accept that people might die/get hurt without it, AND/OR if you’re incapable of appreciating arguments against these technologies, you’re naive and have an inauthentic commitment to whichever side you land on.

I’m an ACLU and FIRE member... generally left libertarian and hate mass surveillance. I am willing to give up some safety in exchange.

People should be allowed to live their lives mostly free from intervention and that any tool that CAN be abused, will eventually be abused. If you put cameras everywhere people will be selectively targeted and tracked.

However, I’ve definitely come around to speed cameras and think we should be MORE aggressive on pursuing dangerous drivers. And surveillance can take the place of cops on the street, which spares more chance encounters that can go wrong.

If you believe your approach is “free” (there are no downsides to either panoptic surveillance or no surveillance) you don’t have a deep commitment to your ideals, whatever they may be.

Belief requires that you be willing to pay for it in less freedom or more harm.

Young adults are poor despite every metric which suggests otherwise

This was probably the most resonant, compelling thing I read this week:

On the surface it does seem as if the young are fine. Real median incomes are higher than they were for their parents at the same age, unemployment has spent most of the past decade at historic lows, and purchasing power has risen roughly 63 percent since 1973. Televisions, clothing, food, and air travel are cheaper than ever.

And yet this generation is also not marrying, not buying homes, not having children, and seem pretty miserable. I think we’re clearly in the midst of a tremendous measurement failure.

My argument is that previous generations received an enormous stock of social capital: trusted neighbors, functional public schools, a productive courtship culture, predictable career arcs, and a public square in which children could roam and adults could be relied upon. That stock, once given for free, has now been substantially liquidated.

Instead, the young must now buy back, item by item and at retail prices, what their grandparents received as a bounty of prior civilizational investments. The young must do so out of incomes that rose modestly while the prices of the essential elements of life rose radically. Price indexes measure the individual cost of discrete goods, but they are not intended to convey the total cost of personally repurchasing a destroyed commons.

On one hand, I make much more money than my parents did at my age. I can and do consume more and better than they did.

On the other hand they owned a brownstone and sent two kids to an elite private school at my age - a lifestyle I can’t imagine for myself without fabulous wealth.

Housing Theory of Everything: if housing were more abundant, we would all feel a lot richer.

Elsewhere

• We have 2 new associates joining Slow this week which reminded me of the best (early) career advice I’ve written/given: Be a Janitor or Be a Star. “You should always strive to do the work either 1) no one else can do or 2) no one else wants to do.” This is from 2021 and five years later definitely holds up IMHO.

• How Ukraine Built a War Fighting State. Crazy anecdotes about using market mechanisms to allocate wartime resources within the military.

• Zip makes the case that the same recursive capital flows/forces buffeting smid cap stocks are coming (here) for private markets too. Good case for companies to be reorienting their long term ambitions toward buybacks and manufactured liquidity vs binary of illiquid or public. If money just naturally flows to the biggest names (passive investing), there is no capital to support anything but.

• We can’t keep doing tasteslop.

• NY Governor Kathy Hochul went on Odd Lots and I’m maybe falling for Hochulnomics? The data center moratorium (if it is a one year moratorium to give time to figure out new regs for energy and water, and not a ban) makes reasonable sense when she presented it. But more importantly the ambition around economic development, nuclear power generation, and housing are genuinely exciting. Bullish Albany?

We are on the precipice of a critical, multivariate, highly uncertain future driven by uncertainty in the path - development and deployment - of AI.

And one of the most exciting things about this moment is that there are so many viable, seemingly reasonable but deeply contradictory points of view about how it resolves.

• Inference races to zero or stays expensive forever

• Models keep getting better or they plateau

• A multi-model world or consolidation to a few frontier labs

• AI will take all the jobs or create all new jobs

There are any number of such scissor statements about AI, society, business in the air right now.

No matter what you do, you are making a bet on what the future/the steady state of the technology looks like. Any company you build has to be a reflection of that bet on the future expressed through every choice you make: your product, business model, and team/culture/org chart. It’s all one choice.

So “what do you think a valuable company looks like in the future” has to be the starting point for what kind of company you build toward and how you build it from 0.

That’s especially true for team and culture, which are upstream not just of what you can build but also how you can build it. They’re the necessary precursors to the product you build and the motion you execute.

There’s not true or absolutely path dependency. Talented people can obviously do all kinds of different things. But there is a relevant optimal path for the pieces as you’ve assembled them. Which pieces you assemble, and to what end, is hugely important and highly determining.

Last week I wrote about Phoebe and “post agent” companies with Justin, who has an extremely strong and explicit POV:

The post-agent business believes and embraces that software and cognitive/computer-based labor is going to zero. And so the post-agent business counter-positions its product, go-to-market, and strategy around that which is still scarce and valuable: context, attention, trust and brand to produce sustainably differentiated outcomes via network effects […]

Engineering and systems thinking is the means by which we build the machine that runs Phoebe. Engineering becomes the highest point of leverage and every function is engineering-assisted (our head of CX is our most active Devin user) […]

I also fundamentally believe in betting on deeply AI-native, junior talent with no prior assumptions on how businesses/products are built and no constraints on the problems they want to work on.

The point here isn’t whether his bet is correct (though I generally think may well be); it’s that a clearly articulated point of view necessarily drives every other choice for the business.

This matters more for startups than for anyone else because startups are deeply and persistently disadvantaged in almost everything; they have less/no money, access, team, or time. It’s hard for them to just say “we’re going to hire the best people or do things in the best way.” Instead, they need to find and exploit advantages, which means knowing where they are advantaged. It’s necessary to have a sense of who the best people are for you, rather than merely trying to get the best people in some generic sense. Here, local > global optima.

Almost everything in startups amounts to leverage and thrust-to-weight ratios. To hire spiky people requires having a sense of what trade-offs you are willing to accept.

There are two obvious ways to spot an inauthentic commitment to vision or a long term bet.

1. Cargo culting. Not necessarily internally incoherent, but assembled based on aesthetics and rote imitation. All signs and symbols. Think: “I want to look like Cursor, so I’m going to make choices that look like the choices Cursor makes” without understanding the thinking/bets behind them. This is the most common and the easiest to spot because it’s all external.

2. Incoherence. Your team doesn’t match the GTM, or your end state doesn’t match your roadmap. This is harder to spot, because it requires interrogating each/all.

These are both company killers. You have to make a bet in order to move quickly and decisively on all other choices.

Even claiming that you don’t have a point of view is still a perspective. It carries with it that the most important thing is to maintain optionality.

That’s a totally viable approach. Believing the future is highly uncertain, and wanting to preserve your options, has implications for how you build, just like going all in on one particular POV does. It is neither riskless nor riskier than anything else, except insofar as you don’t reflect it back to yourself through all the downstream choices you make.

But optionality is never free, you pay a premium to defer choices. You have to make a choice, and every choice is expensive, including the choice to preserve optionality and defer having an explicit point of view.

If anything, startups are advantaged here: they can afford to make choices that are irrational for other people, which lends itself to spiky choices and min-maxing. Optionality is one such advantage. Startups can hold it precisely because they have no infrastructure and no sunk costs to justify... at least for a time.

So it’s not style or “taste” but YOUR style that counts.

Choose wisely.

Programming note: I’m going on my honeymoon next week. This is my first non-laptop vacations in ≈10 years.😅 The newsletter will return in mid-July.

Editor’s note: This is a co-authored post with Justin Woodbridge, the founder and CEO of Phoebe. Phoebe is building a network of agents for healthcare labor. I mostly just added jokes. We’ll be back to our regularly schedule programming next week. Go Knicks.

White Noise

Everything feels astroturfed. Last week we were token-maxxing. Now we are token-minning. We are rolling up, we are buying out. We are taking private (funding secured), and everyone is monitoring the situation. Tech is in a DeLillo novel, with the hum of manufactured, short-lived narratives getting louder every week.

Underneath it all, everyone is trying to figure out where does this all end up? What is the end game?

Each big-bang moment gives new primitives, scrambling the core axioms around which the big winners are built. PCs gave us Apple and Microsoft, Web gave us Google and Amazon, Cloud gave us Salesforce, mobile gave us Uber. Each of these technologies came with new and unique assumptions for how to build a company for the moment; business model, GTM, and org structure are artifacts of each respective paradigm shift.

So what does the agent-shaped company look like? What is the new primitive, and what assumptions does it reset?

Vertical Market Genealogy

Historically, there have been two strategies for vertical tech companies: pure SaaS (sell the tool) and full-stack (build the tool, sell the work). This current cycle has seen the emergence and popularization of two AI-inflected archetypes built on that prior art:

Sell the tool as a “system of action”

• AI and agents power tremendous experiences and value for customers. There is a great race underway to be first to serve them by localizing horizontal workflows for their needs.

• These companies look like 2010s vertical software companies in their business models, GTMs, and teams/cultures. They bolt AI features onto stuck-in-the-mud SaaS thinking and are “AI native” only insofar as they were founded after the release of ChatGPT.

Do the work as a “neofirm” or “AI rollup”

• These companies build agents to transform traditional operating businesses and own all the upside.

• Doing the work as a neofirm or rollup (taking advantage of new intelligence) relies on commodities and does not produce the scarce resource: attention, context, and reach.

As models get cheaper and competition increases, what differentiates my agent from your agent, my firm from your firm? Without differentiation and decommodification, it’s all execution to eek out advantages; that’s not the end-game, nor the strategy to be the last-and-final mover.

The trillion dollar question: what is wave 3?

Infinite, free, on-demand cognitive labor as the new primitive

At the limit, agents represent a new building block: labor that is digital, directable, and deployable on-demand, and most importantly, free (eventually, through open source and local inference).

So the end game is not building more capabilities and applications for computers. Traditional software companies are built around assembling specific capabilities for computers, and profiting off the time and expense that it takes to do so (teaching computers what you wanted them to do was hard). Increasingly intelligent models compress all the capabilities out of the box.

The mid game trap is to get addicted to the human:agent arbitrage (sell agent labor at human prices). The end game to bet on cheaper, faster, local and open source models that make intelligence free.

The post-agent company will win this marshmallow test.

The defining post-agent company isn’t going to be horizontal, that’s for the labs. The most exciting question is not what kinds of apps and software tools can you build - it’s the new business strategies and models they enable.

Instead of “teaching computers,” the new opportunities revolve around “using computers;” - directing and deploying 24/7 intelligence to do more work (raw volume), cheaper work (cost), better work (quality), and the long-tail of tasks that never made economic sense to do before.

And the most promising places to do so are huge, fragmented, physical verticals like healthcare, logistics, and construction where fractious human labor is the critical input (not computer tasks).

Neofirms are the wrong strategy in these markets. You can’t simultaneously networkmax and controlmax. One must give way to the other as the p0, totemic belief (breadth vs depth). And control in real-world, coordinate-constrained businesses is a mirage; you are sending people you can’t observe, into locations you don’t own, to do work you can’t automate.

The post-agent business believes and embraces that software and cognitive/computer-based labor is going to zero. And so the post-agent business counter-positions its product, go-to-market, and strategy around that which is still scarce and valuable: context, attention, trust and brand to produce sustainably differentiated outcomes via network effects.

Stretch the New Primitive to Its Logical Conclusion

What happens when you do the work, but take it one step further and give away most-or-all of the rote/labor/replacement-level value?

Instead of building and selling software tools, you are building digital workers to do the work?

What if instead of trying to monetize the work, you commoditize the work?

The defining opportunity is one of newly unlocked business models, strategies, highly-potent, nascent go-to-market motions.

Business models

• The post-agent company should be focused on as efficiently and swiftly as possible vacuuming up what is going to be scarce at the end-game: context, attention, trust and brand to produce sustainably differentiated outcomes via network effects.

• These companies will be asset-light attention aggregators, coordination infrastructure, and trusted clearinghouses / agent-native marketplaces. (whether monetizing through transactions, advertising, attention routing)

GTM

• The post-agent company flips the inevitable commodity-nature agents on their head and uses that as a sharp GTM strategy to penetrate quickly, efficiently, and expand from there.

• Digital workers do the work and give it away to gather context, bootstrap flywheel and build network effects. The single player mode is instantly valuable enough to attract demand and jumpstart the process.

Team

• The post agent company is deeply technical AND obsessively entrepreneurial at all levels and in all roles, transcending the iron triangle (and the “conjoined triangles of success”). To be a truly post-agent organization, a business will embrace agents in every part of its business, expecting every member to use these tools to ship and solve problems for customers.

• When intelligence is an opex line, commercially minded, entrepreneurial individuals and teams will spin up teams/pods/agents/resources on demand unbound by classical thinking about empire building and headcount.

Give away the labor, capture the network that runs through it. When your competition is built around profit from software or services, how can they respond to you doing the work for free?

The post agent company orients itself around continued, rapid improvement in the cost and performance of underlying models and intelligence. It assumes, at every level, that the future does not merely look like the past but rather sees discontinuity and a true paradigm shift, just like what PC, web, cloud, and mobile ushered in.

Phoebe

We’re putting our time and money where our mouth is with Phoebe. Phoebe is building a network of agents for in-home healthcare, the largest AND fastest growing workforce in the country:

1. digital employees for agencies to manage schedules and run their business

2. talent agents for labor to make more money from better shifts

3. care advisors for families to get the care they need

Today, Phoebe the product and Phoebe the company (Recurrence, the maker of Phoebe) are one and the same. But our real product is the engine that designs, propagates, and manages the network of agents.

As a post-agent company, we aren’t just building external workers for our customers. We build internal workers to execute all the functions of the organization. That’s why we’re building the company first and foremost around engineering; 60% of the company has a CS degree and ⅓ of the company are former founders. Everyone ships.

Engineering and systems thinking is the means by which we build the machine that runs Phoebe. Engineering becomes the highest point of leverage and every function is engineering-assisted (our head of CX is our most active Devin user)

Phoebe’s culture in practical terms

Our company runs on a stack of internal agents and tools that revolve around a central database and API (Phoebe Core). Here we fold in the raw exhaust of every system of the company: each email and call (sales, post-sales, hiring), product metrics from Posthog, agent traces, GTM data, etc. Crucially, the same harness that runs our customer-facing product also powers these company agents.

Phoebe core is explicitly designed to be a vibe-coding safe zone and allow tooling to emerge bottom up, from every corner of the company:

• In CX, Cindy and Dash built an increasingly-automatic post-sales CRM, with agents that run on schedules to monitor communication, check account health, usage metrics, and all the other core CX tasks

• In Growth, Suket and Srini run outbound and paid increasingly through a variety of automatic systems that we won’t discuss further here (no alpha leaks).

• In Engineering, our product is becoming increasingly self-healing. Our harness automatically reads and reviews its own work, looking for bugs and poor performance for customers. It’s aware of its own code, knows our customer base, and can search through all of Core (production logs, call transcripts, Posthog data), to fix bugs and gaps.

I also fundamentally believe in betting on deeply AI-native, junior talent with no prior assumptions on how businesses/products are built and no constraints on the problems they want to work on. We have early career engineers working in every org: sales, support, and of course engineering.

Skills mean very little now. Mindset, flexibility, and motivation mean everything. More than that, we look for people with Jeremy-Strong-levels of off putting, candorous love of the game. People that want to win, that are commercial minded, and treat business like the athletic game it is.

Phoebe is hungrily adding AI-native, AGI-pilled talent at every level and for every function to build toward the end game and live the real-world Factorio dream.

Stayed alive, Knicks in five

I was at MSG for game 1 of the Eastern Conference Finals when the Knicks came back from 22 down in the fourth quarter. It was the most miraculous sports moment I’ve ever seen and I didn’t think it would ever be topped... until the right hand of OG.

Wednesday night started out terribly and it seemed like the officiating would once again take the day. But, between some brilliant coaching and leadership, a legendary choke job from the 8 foot loser corn dog, and stunning late game play the Knicks took back the vibes and momentum in the series.

We are increasingly bereft of monocultural events that focus the energy and attention of the world onto a single fulcrum. This Knicks run is the single most exciting, captivating, unifying event in my life as a New Yorker (with the exception of 9/11 but that’s different).

After game 4 I saw people completely take over the streets. I saw bus drivers laying on the horns. I saw children (1000 drunk teens) dancing on cars and bodysurfing. The on court action was incredible and the off court feelings are magical. I love the bandwagoning for the same reasons I want more transplants in New York: it creates more vibrant fanbase to celebrate with. Why would I want to be alone at a party?

We’re seeing something special and I have no doubt it will birth a newly engaged generation of Knicks fans.

Dunking on VCs

Last week there was a big brouhaha on twitter dot com about the bad behavior of VCs over the years. It was not pretty. While the behavior was varied (pulling deals, falling asleep in meetings, light crimes, etc.) the theme struck a nerve and there was clearly a receptive audience to see some venture capitalists taken down a page.

Clearly there’s some simmering rage against VCs...

But none of this is new nor is it random. In 2019 during a different bout of dunking, I wrote about why VCs draw such widespread ire:

In venture capital you can’t really build a brand or reputation on performance. You can’t advertise competence via returns. It just takes too long... Instead, VCs have to cultivate brands for themselves and their firms through omnipresence: they and their takes have to be everywhere always... Venture capitalists need to look smart because it’s impossible to prove they’re smart. Perception, not returns, is reality

This is, obviously, extremely cringey and annoying.

And beyond being generally annoying, VCs are, for most people, avatars of their own failure - even successful people.

After all, the overwhelming majority of interactions between the overwhelming majority of VCs and the overwhelming majority of founders ends in rejection. For most founders, raising capital feels like a humiliation ritual.

That breeds resentment and makes people eager to take VCs as a class down to size. Venture capitalists are the living avatar and personal embodiment of your own feeling of rejection.

Other people are prolific rejectors too. But HR managers don’t gloat constantly on the internet. Because VCs are principally in the narrative business (not the returns business, at least not on any useful or measurable timeline) they do all that rejecting while crowing and bragging on the internet. As a class, it’s deeply unsympathetic and un-endearing behavior.

Worse, VCs have become emblematic of a world arbitrarily stacked against you (as you struggle against being consigned to the permanent underclass). People feel powerless in the shadow of this faceless market that blesses some and damns others, and almost overwhelmingly does not bless them. Seeing that market and that arbitrary kingmaking power personified in a small coterie of people, and then seeing those people be demonstrated to be stupid, dishonest, lazy, disrespectful, etc., is validating and vindicating.

The catch, of course, is that it’s the hopium of proving VCs wrong when, for the modal or even the 75th percentile founder, they’re not wrong.

VCs are ultimately extraordinarily privileged. We don’t work that hard. We don’t add that much. We don’t risk anything. We’re generally all very lucky to get to spend our time with brilliant, passionate people working on the single thing in the whole world about which they are the most brilliant and passionate. So on balance, I don’t think it’s bad for people to air their grievances and ask for more from their capital partners.

On the other hand, the readiness to join the dunk-a-thon is a sign of the times, and of how seemingly arbitrary the market has become, even compared to a few years ago when I first wrote this.

Scott Heiferman (a real NYC tech OG) rolled a mini app to find Knicks watch parties around the city.

I’ll see you at the Garden on Monday.

Anthropic filed its S-1 and SpaceX goes public next week. There’s ≈$3T of market cap hitting in the next few months with at least another trilly on the way (OAI). Google is selling ≈$80B of stock and it’s not much of a story.

We are witnessing the total takeover of already-concentrated financial markets by a single story; debt and equities, publics and privates, newcos and established names. This will be an entirely unprecedented wealth creation and liquidity event. The exuberance about AI the technology will have become fully overtaken by exuberance for AI the financial asset.

These are (or at least have been) obviously great stocks. Whether or not they are great businesses is the most important question in financial markets right now. I don’t know ¯\_(ツ)_/¯

The Bull Case

World-changing technology. They wind up with infinite surface area, and everyone pays them for everything. Intelligence is the most valuable market in the world (all white-collar work), and they become both an accelerant for and a tax on global GDP. LLMs either scale in other domains like they’ve done in coding or it turns out that every task is actually a coding problem after all.

And this is not even accounting for true AGI and a post-scarcity / post-economic world.

The Bear Case

Foundation models are obviously incredible products but turn out to be terrible businesses.

Training is a cost of revenue, not an R&D cost. Stop training, everyone churns and moves on to your competitor or a distilled Chinese version. The labs are perpetually investing unbelievable sums in building these fast depreciating assets (capex and training).

Every model is bigger and more expensive to run and also gets distilled faster, so these companies have to make huge up-front investments that depreciate extremely quickly. They are competing against one another and with the in-house labs of huge companies that throw off huge amounts of cash. They’ll never be able to charge enough because of competitive pressures. They will just run out of money and places to get it.

So what?

On balance, it’s almost certainly better to bet on the bull case, despite how much upside has already been sucked out / pulled forward at these prices.

If there’s any chance the bull case is right, and you have either a low enough cost of capital or are otherwise short the proliferation of intelligence, you have to get exposure here.

And everyone who works a white-collar job is structurally short. We’re all waking up every day betting that our intellect and creativity will matter. Nobody has any incentive not to be in it and every incentive to be in it, even beyond all the high-falutin’ stuff. (You just look like a fucking moron if you don’t have exposure).

So we’re definitely in a reflexive bubble. If you don’t believe the incentives/structural reflexivity just look around and use your eyes.

Is the bubble worth it?

Will it be like railroads, which ultimately produced a ton of valuable infrastructure (I think yes), or like crypto, which was basically a wash (though of course we wouldn’t have AI without all the chips and stuff from crypto)?

Here, the intelligence and capabilities are a positive externality of the bubble/exuberant build outs. And the more distillation happens, the more the frontier gets eaten by open source, the better for everyone. It does seem clear by now that as long as we don’t completely bungle the second order impacts (on society, politics, and business) that we are all going to be the winners. I mean this literally. Productivity is the main thing. It doesn’t require AGI or LLM maximalism to believe that we’ll look back on today’s standard of living (our material conditions) and standard of toil (the drudgery we accept for ourselves) the same way we look back at a pre-electrified world: impoverished, immiserated, and base.

It’s possible the labs ultimately get wiped out. I don’t know, and I’m not betting on it. But the bubble being worth it for the world and worth it for the equity are not the same question. If information wants to be free, then intelligence wants to be unbounded.

None of this answers the actual question of the business vs the stock and the bonanza won’t settle it one way or the other. A business is not a stock, and a stock is not a product; the price won’t be a verdict.

Read More

• Don’t wait for the AI shock

• Investing in the second-order effects of AI

• Sam Altman’s Endgame

  ---

It’s time to lock in (sound on).

The agony and ecstasy of Knicks fandom is profound. I fell in love with basketball around 6th grade, c. 2005, the first innings of nearly 25-year, uninterrupted run of mediocrity and pain for the franchise.

While some of the bing-bong antics today are over the top, it all comes from a place of profound love and desperation. New York is a basketball city and this team/organization/coaching staff has finally given a team worthy of our love.

Knicks in four.

Slow Takeoff

Last week in New York we hosted Takeoff our now bi-annual mini-conference for young partners, principals, and emerging managers - and our counterparts on the limited partner side.

We are betting on this cohort to be the next generation of important investors in this asset class (and I’m lucky to call many of them my friends and peers). Some of them are running funds already, some are still building careers inside larger firms, all of them are doing the work without the security of knowing they’re right. We get to follow and support them, co-invest with them, and steal their best ideas. The least we can do is buy them a drink and put them in front of each other (and LPs) once a year.

The event itself was off the record so I won’t repeat/reveal much but we had a phenomenal group of speakers:

• Emerging Managers: Taylor Greene (TwelveBelow), Finn Murphy (Nebular), Niko Bonatsos (Verdict)

• Our Thinky Boys: Aaron Harris (Magid), Jeremy Giffon (Octave), Mike Dempsey (Compound)

• Fireside chat with Hunter Walk (Homebrew / Screendoor)

• LPs: Erik Strobel (Granite) and Matt Auxier (University of Chicago)

There were a few threads and themes that really jumped out.

Heart in the game Skin in the game used to do the work of binding people to outcomes; it doesn’t anymore. Everyone trades in and out, gets paid regardless, can leave for a portco or a frontier lab. But who would make a decision that costs them in the moment because they actually give a shit and are planting a long term stake in the ground?

Firms are products You don’t get to bolt together separate decisions about fee structure, fund size, partnership composition, check size, and LP base and call it a firm. They have to cohere or you get the bootleg cassette effect: a third-generation partner playing back a model built for and around people they’ve never met, audibly degraded each copy.

What comes after the navy The alternatives world ate venture. The platforms behave less like risk-taking partnerships and more like large institutional asset managers, because that’s what most of them have become. The pirates became the navy. The interesting question, which we did not resolve, is what comes after. Almost everyone in the room is making a bet, with their career and their LPs’ money, on some version of that question.

Tremendous thanks to our supporters who help make this possible: Cooley (Slow’s law firm), JP Morgan (a very deep partner to the firm), and Sydecar (our friends and thought partners).

Ask Yoni

This week I shipped something fun: a Yoni’s 99D MCP to know what I think/have written about stuff (this newsletter). I made this for myself as a more efficient/portable way to surface relevant context for writing and investing projects after getting annoying by constantly trying to manage project memory/context. I do tons of copy and pasting links which is annoying.

I figured someone, somewhere in the world my want to read my newsletter (or have their agent read my newsletter) within chat. One step closer to Yoni GPT.

You can try the MCP server here and the github is here.

COGE

Mamdani announced the Comission On Government Efficiency, which is an obviously dumb name for what remains an obviously good idea. My immediate skepticism about DOGE (since vindicated - it was a complete a failure) came from my (correct) read that it was a bad faith effort by unserious leadership. But we shouldn’t let that poison us against the thought that government can/should/must work better.

It’s also obvious that tech/software/AI should be a big part of improving public service and delivery. Democrats, progressives, and technocratic abundists (check, check, check for me) should be rooting for ideas like this.

Cost overruns, delays, bad service, etc. all undermine faith in government and spur the death spiral of state capacity. The only way to reverse the trend is to reverse the trend. Personally, I want to be involved and supportive in any way I can.

Remember, efficiency isn’t just less money in, it’s outcomes achieved per unit of work.Mamdani announced COGE - NYC’s Commission on Government Efficiency. This is a very dumb name for a very good . I was/am on record that DOGE was/is a complete failure because it was never a serious or good faith attempt but

1. Making government work better and be cheaper is obviously good

2. Software/tech/AI should obviously be part of that

It is absolutely incumbent on democrats, progressives, and technocratic abundists (check, check, check for me) to demonstrate that government can actually deliver, not just spend more money. We have to start in places like New York which have an immense pool of talent and capital and still face dire budget problems.

I hope to support COGE and be involved in any way I can (step one is coming up with a better name).

Being Public Seems Hard

Seems basically impossible to be a public company right now.

You’re simultaneously getting the feedback that you need to be an AI leader AND that you predictable high margins but:

1. You’re spending tons of tokens, and increasingly, more than the tons you had planned on spending (“we blew our whole budget in 3 months”)

2. All the spend is highly experimental and you don’t know if the results will be there (good or bad) or how they will materialize (more growth, more profits, etc.)

Public markets love predictability (the only better than good news is the expectation of good news, and the only worse than bad news is unexpectedly bad news).

That is basically impossible to deliver right now.

From elsewhere

• Is this a new 5th job or just a new meaning to slop cannon?

• I am extremely into neighborhood restaurants getting “day jobs” as popups/coworking spaces/coffee shops. Margot/Winner has become a staple for me. I’m pretty curious about the economics since part of the appeal is low density/low turnover but hey, if it works!

We’re in the installation period of the AI supercycle where hype, speculative capital, and technological progress are rampant. The deployment period, where it becomes usefully integrated into our productive base, is just beginning and will last generation(s).

Deployment is the most important thing happening in the world right now. Acceleration and abundance vs stagnation rests in the balance.

Accordingly, there is intense, widespread interest in making bets directly on deployment. Betting not just on the beneficiaries (new AI-enabled products and services) but also on the delivery (the IT services working on AI transformation projects for legacy institutions).

System integrators and other consultants/AI services firms are/will be the connective tissues between installation and deployment.

There are three or four main flavors of AI services right now:

1. Fast moving FDEs/bodyshops: (elite) generalist teams parachuting into enterprise transformation work horizontally and on a per-engagement basis

2. The captives/joint ventures: the deployment arms and JVs being spun up by the labs and hyperscalers

3. The product companies: specialists building an internal product that delivers a specific outcome for a specific kind of customer, repeatedly. We have one company here (operating as a system integrator) and are looking for more. And of course there are a few companies selling these kinds of tools externally to other service providers (arguably the fourth).

The bodyshop approach is a rational response to the current market environment and the belief that things are moving too fast to do anything else. There’s not time to build a product; you just have to do stuff. It’s also a much better deal for a certain kind of talent. The best FDEs get to be the hero and directly monetize their skills instead of running customer success for a research team that sees deployment as overhead.

The JVs/captives are a fundamentally different proposition but also rational for their backers/creators. Their deployment JVs don’t need to create value companies directly; instead they generate EV by expanding the surface area and lock-in for their sponsors. Investing $100M to improve the odds for a $10B position is obviously rational. At $1T it becomes necessary.

Of course there is some risk of a “Hotel California” situation: once they’ve built your AI infrastructure on their stack, with their FDEs, around their models, you can’t check out. Their people aren’t working for your outcome, they’re working for their sponsor’s lock-in. The tradeoff is that they have max recognition and access, so a lot of buyers will take the deal anyway.

The most interesting version of the story is a product company delivering a service, rather than a service company delivering a product.

The internal product enables differentiated service delivery. The product might look like some combination of an agent/harness, context layer, workflow automation, etc. but in any case you’re creating a product that you consume internally in order to deliver a service externally (to your customers) better, faster, cheaper. The product companies bend the cost curve down rather than charging more because of temporal buying pressures and unique access to talent.

One of the most obvious tells is whether you’ll do anything for everyone or if you have a narrowly defined ICP. Are you trying to productize the process that delivers a specific kind of outcome in a specific context, or are you offering to do custom work and build anything your customers want? The product companies will have clear religious beliefs about what they can’t touch or won’t do.

We’re looking to back AI Accenture, not “Accenture for AI.” That is, there’s an immense opportunity for services companies to fundamentally rebuild how they deliver, not merely what they deliver.

Read more:

• The Complexity Crisis

• Implementation is the task of our time

• Modeling software after SaaS

Cliff Club

Introducing Cliff Club: a community exclusively for early employees at venture-backed companies and we’re starting with NYC first!

We’re gonna bring in great early operators and subject matter experts to talk about questions like:

• WTF is QSBS?

• How should I think about early exercising?

• How should my role evolve as the company scales?

• How should I feel about getting layered?

• Should I specialize into a role?

Really excited to work on this with my friends Charley and Leeor.

Take the dive.

Very busy week with a lot cooking include a teaser for a new project. More to come soon.

Venture Grounds

I had a lot of fun on the Rho podcast talking about the second order effects of AI (what happens AFTER we token max) and the right way to back seed founders (give them money and don’t fuck it up).

If the development and, increasingly, deployment of AI is the most important thing in the world, then the most interesting questions are what happens after we’ve done it (to the extent that it’ll ever be “done”).

I’m extremely bullish on and interested in the second order effects of AI:

AI amplifies volume until existing filtering/routing mechanisms collapse and need to be rebuilt.

• Deployment: more apps, faster releases, more integrations, etc. SIs are critical chokepoints and will become very powerful this cycle.

  • Slow company: Stealth, Stealth, Stealth

• Hiring: Applications are free to send. Volume explodes. Recruiters can’t distinguish candidates. Resume screening stops working. The whole funnel breaks.

  • Slow company: Phoebe, MeritFirst, Tofu

• Outbound sales: Sophisticated campaigns available to everyone, flooding channels. The well gets poisoned and new GTMs replace it.

  • Slow company: Memelord, Stealth

• Code collaboration: Git was built for scarce, human-written code. Whatever replaces it will be built for abundance.

  • Slow company: Atomic

• Trust and security: Everything on the internet is fake. Content, identities, credentials. Systems that assumed human-scale production and human-verifiable authenticity stop working.

  • Slow company: Outtake, Sublime Security, Stealth

But broadly speaking, there are a huge number of spaces where attention (abundant) and production (scarce) will flip to devastating effect.

And simultaneously there are greenfield opportunities that would have previously been impossible or unimportant.

Cliff Club: Take The Dive

We love getting together to hang with operators and builders early/earlier in their journeys, whether or not they wind up building companies. I find that much/most of our best network comes organically by hanging out and jamming with people months or years ahead of a transactable opportunity. But we only earn the right to your time if we can be of service.

Introducing Cliff Club: a community exclusively for early employees at venture-backed companies, starting in NYC.

We’re gonna bring in great early operators and subject matter experts to talk about questions like:

• WTF is QSBS?

• How should I think about early exercising?

• How should my role evolve as the company scales?

• How should I feel about getting layered?

• Should I specialize into a role?

Really excited to work on this with my friends Charley and Leeor.

Take the dive.

Drink the Haterade

• For all my Fallon haters: Fallon acts as the high priest of a terrified optimism, his rictus grin serving as a shield against the encroaching silence of the real. Here, in the sanitized, over-lit heart of the American culture industry, there is an inescapable horror. But it isn't a monster lurking in the shadows; it is the manic, unblinking insistence that actually, there are no shadows at all.

• For my Stephen Miller haters: Stephen Miller is surely the most powerful unelected person in America. The 40-year-old’s official roles — he currently has the dual titles of deputy chief of staff for policy and homeland security adviser — vastly understate the influence he has had in shaping Trump’s most hardline anti-immigration policies and rhetoric for the past decade. Whenever the president says something particularly inflammatory or offensive about immigrants in a speech, there’s a good chance Stephen, his director of speechwriting during the first term, told him to say it.

• For my Iran war haters: Defeat in the present confrontation with Iran will be of an entirely different character. It can neither be repaired nor ignored. There will be no return to the status quo ante, no ultimate American triumph that will undo or overcome the harm done. The Strait of Hormuz will not be “open,” as it once was. With control of the strait, Iran emerges as the key player in the region and one of the key players in the world. The roles of China and Russia, as Iran’s allies, are strengthened; the role of the United States, substantially diminished. Far from demonstrating American prowess, as supporters of the war have repeatedly claimed, the conflict has revealed an America that is unreliable and incapable of finishing what it started. That is going to set off a chain reaction around the world as friends and foes adjust to America’s failure.

For Lovers

• America is experiencing a productivity miracle and we basically don’t know why. It’s not because of AI (at least not yet) but it is really good news.

Last weekend we hosted Slop Con: an all day hackathon for slop cannons to work on personal projects and compete for (cash) prizes. We got 60+ people squirreled away all day on a gorgeous NYC saturday - extremely bullish. Big thanks to everyone who came out.

The fact that it was, by and large, some of the stupidest projects you could possibly imagine (oneshotting Mog/Chop, e.g.) reinforces the point. These are all people who came out because they wanted to have fun, try new tools, and chop it up. Crucially, they cut across technical and non-technical folks. We had AI engineers and equity research analysts. There were founders and interns.

In the weeks since I published the Four Jobs, we’re starting to see the term/idea crop up everywhere:

Even Max at Pangram, the anti-slop company, proudly refers to himself as a slop cannon.

Because there’s a difference between using slop to produce and producing slop.

The slop cannon uses janky tools and rough output as inputs to better work. The bad version mistakes the byproduct for the practice. I’ll flatter myself and say I do a good job of this in how I use (and don’t use) AI to write; bicycles for the mind vs motorcycles for the mid.

Through a willingness to go produce, go fast, and look dumb you too can reach slop nirvana.

There’s a chance that this is ultimately a distinction without a difference. It might not really matter how or why the best people produce when the modal production is both 1) bad and lazy 2) high volume.It’s very possible that, irrespective of that distinction, at least as far as it comes to communications, sales, marketing, etc., we still wind up in an age where all the channels are choked and stuffed.

And no matter what, we still reach the age of inbound where attention (abundant) and production (scarce) flip.

But what about “taste?”

I reject the idea that we need to choose between velocity and judgement, slop vs taste.

1. The whole organization needs intuition and judgement (more meaningful and measurable than “taste”). And the organization as a whole needs to move fast, when the moment calls for it. Gotta walk and chew gum, lads.

2. Taste in the common tech parlance is a meaningless, ineffable meme. It’s a cultural signifier rather than a specific attribute or skill. See also: “tasteslop.”

Slop cannons need to be product- and commercially-oriented to effectively harness their gifts and the blessings of our new AI age. But they need intuition and judgement to point themselves in the right direction, otherwise they’ll run really fast off a cliff.

So remember kids, slop ‘em up.

Slop Cannons Wanted

We have some great companies building fast and looking to add slop cannons.

• An ex-One Medical, ex-Bridgewater founder backed by a16z, Slow Ventures, and 100+ leading angels is building a stealth health tech company in New York - physical AI applied to medicine, vertically integrated from software to clinics. Looking for engineers who think in systems, physicians who ship product, and a Chief of Staff who lives in Claude Code. Email stealth@rungravity.com

• Michael Rado and Sam Kotlove are building Smoke: an agent workspace that runs sales, marketing, and ops for small teams. Set up a dozen agents in minutes, no code, no connectors, enterprise tools included. The core loop is prospecting, outbound, and content marketing. Nothing goes out without your say. Hiring GTM Engineers, Product Engineers, AI Wonks, and Product Designers.

• Justin Woodbridge is building Phoebe: a self-driving network of agents aggregating and directing worker attention in home care. Replacing coordinators inside agencies with agents that never sleep, never churn, and never forget. Looking for a Product Ops lead who wants to be the human in the loop for hundreds of agents running real workflows in production. This is a young team where everyone ships. (NYC)

• Goodlane is a repeat-founder team building an AI-native parent brokerage for freight agents in Brooklyn. Independent agents own shipper relationships and run their own mini-businesses; the parent brokerage automates everything else. Looking for an Agent Services Lead to own the relationship with the agents themselves: recruiting them, onboarding them, and making them successful. Part GM, part founding GTM, part product. If you want to run a business inside a business, this is for you. (Brooklyn)

In other news: AI Deployment

OpenAI and Anthropic have now both launched big consulting joint ventures to do enterprise AI transformation and create a new channel to sell tokens.

My bet is that most companies aren’t really ready for full scale transformation so big deployments will keep failing at high rates. The underlying data infrastructure isn’t there yet in many orgs, to say nothing of the culture.

Remember, I am long system integrators and services-led businesses where you own the outcome.

Read more:

• The Complexity Crisis

• Deployment is the task of our time

I wish I were more interesting, but I generally take the modal view that AI will wind up being a job creator, not a job destroyer, with two caveats:

1. In the short term, it’s almost impossible to imagine a scenario in which there’s not a ton of labor market displacement and economic churn.

2. In the long term, I could be wrong.

Either of those scenarios is good justification for some kind of insurance.

Everyone basically expects some kind of shock to occur, even if only temporarily. Whether that’s job loss, energy prices, a wave of cyber incidents, who can say. What we know is that if Something Big happens, there is almost certainly going to be a period of displacement and torque. We don’t know what it’ll look like but it feels inevitable that it will happen. So it seems obvious to take out / issue some insurance.

The default answer in this conversation tends to be UBI. But UBI is dumb and bad. It’s both too expensive AND doesn’t go far enough because it’s not productive. It creates a permanent underclass of government subsistence vs developing human capital. If people leave the workforce during the tumult, their path back into the workforce is hazy at best and their tendency to become antisocial is high.

Sam writes a lot about AI as a meaning crisis, not a job crisis. Even if we solve the income problem, we’re still left with video games, porn, and nihilism as a 24-hour job.

Better to develop human and physical capital through a public works project that encourages social cohesion and human flourishing.

We should be prepared for massive investments in physical infrastructure, human capital, and human flourishing:

• There’s a huge amount of shovel-ready projects in the country, and no amount of AI job displacement will solve the fact that all of our bridges are falling down.

• Human capital investments (health and education/childcare) increase the productive capacity of the economy over the long term

• And human flourishing (arts and culture) is a necessary condition for social cohesion. If we’re a rich society that’s going to become an ultra-rich society, we should engender the conditions for arts and culture. Otherwise, what was it all for?

Treating AI insurance as a jobs program vs pure redistribution is also a great hedge. If I’m wrong and there’s no risk of crisis, we’re still investing productively in human and physical capital AND it’d be much easier to end a jobs program than to undo an entitlement program like UBI.

Note: There’s also a very real possibility of other kinds of shocks that merit insurance and investment. Think biosecurity and cybersecurity. We are sticking our heads in the sand on this.

Not having insurance for something we think might happen and might be really bad if it does, on ideological grounds is just dumb.

If we don’t have smart stuff ready to go with broad buy-in we’ll do dumb stuff or we’ll do nothing at all and history will happen TO America.

Stray thoughts from my feed:

• Moral leadership requires moral authority and courage. You don’t get to whine about cultural/moral decay while actively promoting it. It’s fine to make money but maybe just shut up and dribble.

• The real American dynamism is not buying low grade cashmere from Quince. We can all do better than the same grey, made in China crew neck.x

As the difficulty to produce/create software goes down and the lack of true moats in most software companies becomes more apparent, the unique value of network effects as a truly defensible position will reprice.

Chris Dixon gave us “come for the tool, stay for the network.” James Currier gave us “market networks.” I want to add a third: agent networks. Self-driving software that starts useful to one user, then backflips into multiplayer coordination as those users’ agents start transacting with each other. Build the tool, acquire the network.

AI will actively create more and new opportunities to build network effects, even if the playbook and form factor diverge wildly from web 2.0 marketplaces.

Platform shifts and primitives

Historically, marketplace and NFX businesses were built on a set of primitives: payments, identity, messaging, and risk/compliance. With each new platform shift (internet, then mobile) these businesses have added/relied on new primitives as the base metal powering the network, beneath the interface and UI.

The first marketplace businesses (think eBay) were built on a hugely important and newly possible set of primitives enabled by the internet as a platform. Payments and messaging made those web 1.0 businesses work. Finding, talking to, and paying strangers was a hugely valuable new capability made possible by the internet and powered a new trillion dollar economy of online commerce.

The next platform shift (mobile) spawned a wider array of 2- and 3-sided businesses (Uber, Airbnb, Doordash, targeted ads, etc.) that added identity and risk/compliance, allowing NFX businesses to extend deeper into the messy real world of people and services. These (mostly) locally constrained services companies were brutally expensive to build because of the requirements for density and the cold start problem BUT they could address bigger markets.

For a brief time, it seemed like “market networks” would be the next evolution here: companies like AngelList and HoneyBook would start as software companies to attract one side of the market and then power connectivity to create NFX and lock-in with the other. But there was no meaningful platform shift powering these businesses and no new primitives; the single player utility wasn’t high enough or new enough at the start. While they didn’t fail (those companies still exist after all), there are no IMPORTANT companies to emerge from this hypothesis.

Now with the AI platform shift, context will be the fifth primitive for marketplaces and agent-networks are the emergent NFX paradigm. Even if it’s self-driving and has no conventional interface it functions on the same basic metal.

With each new platform shift, NFX businesses tend to monetize at a higher rate. As you add new primitives, you creates new monetization pathways, which ultimately drives take rates and viable category sizes. Context as a primitive powers the addition of a SaaS-like business model, which obviously opens up new sizes of categories.

Agent networks

Agents finally make the single-player tool valuable enough to stand on its own. You can build in sequence and grow revenue while in pure single-player mode because the utility of agents is so high. With obvious, out of the box utility you get cheaper acquisition and avoid the cold start (kind of one thing), and the shape of the network changes.

The user’s agent is a way to acquire context and serve them in single-player mode. My agent does stuff for me, part of which might be talking to you, which sets up the company to sell an agent to you. Then our agents talk together / to each other (you know, business).

There are a handful of companies cropping up and starting to run some version of this idea already.

• Phoebe does this in home care. Scheduler agent for agencies, talent agent for caregivers, family agent for clients. Three sides, one network. More in the announcement post.

• Ando does this in restaurant staffing. Forecasting and scheduling for operators, Ando Passport for workers (a verified identity that compounds across shifts and is portable across employers).

• Hero and Nas.com do this for sellers. Take a photo, the agent identifies the item, prices it, writes the listing, posts it. Acquire sellers now, run the marketplace later.

• TruckSmarter does this in freight. Owner-operator truckers pay for an agent that aggregates loads, handles scheduling and paperwork. The talent agent is the wedge into a network nobody has been able to consolidate. Notably TruckSmarter is pivoted into this; it’s not a new company.

Across these verticals (and many more) the pattern is/will be the same: Pay a single-player agent to absorb grunt work on the side of the market that is hardest to acquire. The network follows.

Self-driving networks have to drive themselves, after all.

Where to build

The pattern selects for different TAM and acquisition cost profiles than web 2.0 marketplaces. What to look for:

• Coordination and memory is the grunt work on the acquirable side. Middle-of-the-curve tasks. Not physical, not skilled, not requiring personal agency to get started.

• Buying propensity (not P2P). It’s too hard get normal people to pay for a single-player agent (normal people don’t buy lots of software for themselves). B2B or B2C where one side can absorb a SaaS-like agent, or P2P close to a transaction where one side has prosumer-level coordination load (Hero, Nas.com).

• Sneaky big TAMs: context makes the TAM’s bigger but you still can’t do it anywhere that’s micro, or you at least have to have a point of view on long-term category size.

The two places it doesn’t work:

• Networkable but not agent-acquirable. You still can’t do Uber from scratch. There’s no market creation opportunity if you need existing people to benefit from an agent, and there’s no good case for single-player Uber as an AI agent that a driver would have paid for. Riders obviously aren’t gonna pay for a ride booking agent.

• Agent-acquirable but not networkable. Vertical AI that works like SaaS. Real single-player utility but no multiplayer layer to lean on. If external coordination can’t/won’t be on the roadmap, it obviously can’t work in multiplayer mode.

Conclusion

I’m not convinced lots of standalone, non-NFX driven agents will have a lot of long term value, at least not unless they can move past SaaS-like experiences, business models, and GTMs. Switching is easy and you have to sprint to stay in the same place because of model improvements.

Agent networks are different. The NFX drives utility you can’t recreate in single-player mode even if you perfectly exfiltrate data and infra. The data and infra make the system better, of course. So it’s networks, then data, then infra, in order of importance. The infra is the least important because it’s the most replicable; anyone can build good software on their own but you can’t just produce the data, and even if you could it would be useless without a network.

The graph is the moat and context is the new primitive driving a business model shift for marketplaces.

Read More

• Life on Autopilot: on on what agents can, can't, and shouldn’t do

• Don’t call it a moat: on why software moats mostly aren't

• The phone company always wins: on the durability and appeal of NFX-business

Slop Con

On Saturday, May 2nd, we’re hosting NYC Slopcon, a hackathon for product engineers, vibe coders, commercially minded engineers, technically minded sales people, high velocity operators, etc..

We are convinced that the world is reorganizing around four archetypes and ways of working: slop cannons (non derogatory), SREs, adults, and hot people.

The best AI native companies are increasingly recruiting commercially minded engineers regardless of the role. They explicitly want people who are comfortable using tools AND thinking about product AND thinking about customers. The salespeople are shipping (at least internal tools and automations for themselves) and the engineers are relentlessly focused on customer value.

The highest performing companies will have ‘product engineers’ and slop cannons in every role (product/eng, sales, ops, talent, finance, CX, marketing, etc); it is a multi-hyphenate skill set crucial to accelerate each area of the business.

We’ll have prizes and credits from OpenAI, Vercel, Pangram, and Memelord. Join us. Slop em up.

There’s a meme war going on right now between “it’s all about SBC” and “it’s all about terminal value.” The obvious answer is that it’s both. But the important is *why* it’s both, and what that tells you about where the SoftWars™ are headed.

The market has decided that >95% of software is an annuity (fixed life) with $0 terminal value. If you’re running an income stream, you need to care about income and constrain SBC (a cost). If you’re accelerating/have TV (building a perpetuity/compounder), you don’t. That’s the basic dichotomy of the market right now.

If you are one of the happy few companies that the market believes not only has INCOME/earning potential but the potential to be a perpetuity (has terminal value), then it doesn’t matter because nothing matters. 25% of revenue as SBC is merely the price to pay for acceleration. The problem is that your low growth, moderate adjusted-EBITDA SaaS name is not one of them. Cutting SBC will make that business more attractive to a value-oriented financial acquirer but doesn’t give you a future.

Running the badly run middling software companies a little (or even a lot) better won’t change the narrative albatross weighing them down, except perhaps to the extent that running them better means just going all in on AI and acceleration.

From Matt Slotnick:

So how does software fight back?

You build.

But not in the measured, incremental, multi-year roadmap manner that they’re used to. The frontier shifts too fast for a multi year roadmap.

Take a portion of free cash flow and stand up a small, empowered labs group, with a real, honest to god mandate supported by the CEO. A mandate to build new solutions for your install base, unencumbered by existing offerings, pricing, messaging, or value props. You have to build, and you have to build fast. Because AI is moving fast, and prevent defense never works.

Do everything you can to instill this entrepreneurial DNA within your company. Hire and promote people who truly get it. And part with those who don’t Compensation structures probably have to change. Talent assessment very likely has to change.

Strong endorse.

Now to make this about ME. This matters as much or more at seed than anywhere else.

Basically the only questions that you can really even ask are:

1. Do I love this guy/gal

2. Is there a story that matters

3. Is there something convex/interesting to spend money on today

4. Is there terminal value

This often gets muddled by asking “what’s your moat” which doesn’t make sense and has no good answer. You of course can’t have a moat early. If you could, you probably couldn’t start. (Some notable exceptions include things like regulatory capture through political connections, but those are rare).

What you can (must) is a point of view on the long term margins, earning power, defensibility. A thesis about where the moat comes from and what the business looks like over time. If nothing else it’s a more interesting/revealing conversation to have early.

And if you can’t/don’t have a strong POV on terminal values in 10 years you shouldn’t be investing in a category with 10+ year hold periods. This goes for founders and investors alike.

I increasingly find myself saying “I don’t doubt you can do X reasonably well and earn a bunch of revenue but let’s both accept there’s no TV in that so what’s it for?” Obviously things are hard and you can only make those claims in a narrow set of companies but the point stands. And I it’s not an academic question; it winds up really impacting what you build and prioritize today (capital allocation).

Counterintuitively, predicting the long term is actually easier/higher confidence than predicting the medium term. If Trump had lost in 2024 the world today would be very different but the world in 2040 might be largely the same either way because the forces/stories propelling the world are broad and deep. It’s variance around durable trend lines.

We are not traders. We’re investors who, as a bug or feature, have no liquidity. All we have is terminal value - hopefully our companies will too.

We Co-led Prefix’s Seed Round

A couple years ago I wrote about why repair and maintenance is a super elegant way to get into industrial workflows efficiently and build a many-armed tentacle monster:

• Many shots on goal to make a sale; something is always broken unlike equipment sales which is infrequent.

• Motivated buyers: repairs are urgent. When something breaks it needs to get fixed right now because uptime drives revenue.

• High value: unlike single use supplies, machinery and heavy equipment is high value and fixing it is high skill - not just a question of price.

That was a preview of Prefix (and Heave).

Prefix is a marketplace for restaurant and retail facilities maintenance. Independent technicians on one side, big multi-site operators on the other. The company makes repair and maintenance better, faster, and cheaper for some of the most demanding brands in the country, including Chipotle, Raising Cane’s, and Bojangles, across thousands of locations.

Restaurants are a great place to start because they’re large but highly federated accounts. A national chain has hundreds or thousands of locations, each depending on local technicians for HVAC, refrigeration, plumbing, and electrical. These are big customers that don’t want to deal with rinky dink procurement across every market they operate in.

Prefix lets big brands interact with small, local service providers on more of a like-to-like basis: buy from Prefix, get service fulfilled by the best local players. Best of both worlds. And on the other side, it makes those big accounts winnable for small businesses that would otherwise never get in the door.

By starting with repairs (recurring, urgent, valuable) Prefix can profitably earn the right to start building relationships with customers on both sides. Over time there’s obvious expansion opportunities into equipment purchase, capex financing, single use supplies, software, and self service offerings for small independent brands.

We co-led a $7.5M seed round with Collide Capital to help Prefix keep scaling. The company is expanding aggressively beyond QSR chains into retail and other multi-site verticals, and over time we’re excited to see them go deeper on both sides of the marketplace.

Prefix is a revenue driver and sales orchestration opportunity for the supply side, and a coordination layer that keeps getting more valuable for the demand side. This is how useful technology gets into the real economy and makes long tail entrepreneurship more possible and profitable.

Prefix is hiring AEs and senior salespeople around the US.

Slop Con

On Saturday, May 2nd, we’re hosting NYC Slopcon, a hackathon for product engineers, vibe coders, commercially minded engineers, technically minded sales people, high velocity operators, etc..

We are convinced that the world is reorganizing around four archetypes and ways of working: slop cannons (non derogatory), SREs, adults, and hot people.

The best AI native companies are increasingly recruiting commercially minded engineers regardless of the role. They explicitly want people who are comfortable using tools AND thinking about product AND thinking about customers. The salespeople are shipping (at least internal tools and automations for themselves) and the engineers are relentlessly focused on customer value.

The highest performing companies will have ‘product engineers’ and slop cannons in every role (product/eng, sales, ops, talent, finance, CX, marketing, etc); it is a multi-hyphenate skill set crucial to accelerate each area of the business.

We’ll have prizes and credits from OpenAI, Vercel, Pangram, and Memelord. Join us. Slop em up.

The world needs attorney client privilege for AI

Messages to LLMs are not privileged/are discoverable. We’re starting to see them show up in litigation along with the advice for regular people not to ask Claude about the law.

This is a gift to the legal cartel and it’s bad for everyone else.

Consulting LLMs about legal matters in parallel to lawyers, before lawyers, and instead of lawyers is pro-social behavior. The alternative to an LLM reading your employment contract is not having a fancy lawyer read it; it’s signing it blind. Same goes for leases, demand letters, non-competes, etc.

Worse, the genie can’t go back in the bottle. The landlords, employers, corporations, and scammers will use AI to drop the cost of contracts and litigation threats to zero. Consumers will get screwed.

Someone should build the product that serves the behavior and protects the user.

The shape is probably something like: minimum viable pretense for attorney-client privilege over LLM conversations. You sign up, you sign an engagement letter, there’s a licensed attorney on the other end blessing the channel, and your conversations with the AI happen under that umbrella. I’m sure there’s nuance here, but the broad strokes seem solvable by a good lawyer and a good product person working together.

The business model is either standalone consumer AI and/or PLG for a consumer neofirm.

On one hand this is “safety driver in the Waymo” which is dumb. On the other, it’ll ultimately be good for people, which is good.

I had a conversation with an investor managing a large institution and many billions of dollars this week. This guy is, by any measure, orders of magnitude more successful than I am and pushed hard/called bullshit on some of my usual talking points.

He’s not gonna read this but I’d still like to state my case a little more eloquently than I did IRL, especially in light of “the group chat” essay which is cynical, distasteful, and completely true.

Cheap like expensive is neither inherently good nor bad. A business is just a business, and price at seed is mostly a reflection of the market, not inherent worth. Remember, any reasonable DCF/the true FMV of every early-stage investment is approximately zero.

Believing that something being out of favor makes it good is just as specious and lazy as the opposite belief: that something being expensive makes it good. In either case, you’re outsourcing judgment to others.

Is there any objective measure of (non-) consenus? Obviously yes but also no, not really.

“Non consensus” can either be an input (price) or process (judgement).

In the former, you’re agknowledging/claiming that only way for something to be non-consensus is for it to be cheap. The idea of being a “contrarian” while paying top quartile prices is obviously insane nonsense.

Conversely/in the latter, you’re focused deriving a judgement/value of a business irrespective of what others think (how hot-or-not it is). That will sometimes mean paying up!

With enough companies/a big enough sample, the two ideas should converge at the median and diverge at the average (you might independently conclude Anthropic really is that good and be right!).

In an industry/asset class with power law outcomes, it’s totally reasonable to pay multiples more for the 99th percentile than the 90th percentile of quality opportunities, but caveat emptor. Distinguishing between those without real meaningful data beyond what others think is basically impossible or, at the very least, approximates to a random walk.

If I have one core insight and belief at seed/pre-seed, it’s this: there’s a huge amount of false precision and unreasonable confidence in assessing the best, the worst, and the median opportunities.

What “everybody knows,” what “the group chat decides,” and what’s actually true are not a perfect circle even if it feels really good to believe that they are.

From Kingmaking and the limits of external conviction:

King making is permission-based; it only works on the basis of elite buy-in/consensus […]

At Slow, we believe deeply in founder-led/internal paths to conviction. Whether that happens heads-down in a notebook (calling your shot) or heads-up in the market (calling your customer) doesn’t matter. We can fund you to conviction/insight or meet you once you have it. But it has to come from you, not us.

“The group chat” is externally derived conviction and is highly permissioned and better suited to those who need permission to build and buy.

A New York financier reviews New York Review of Finance

This morning I got the second edition of NYRF delivered in print to my door. It’s great and I like the un-accredited writing in the style of The Economist. It creates the impression that you’re peaking behind the curtain of what folks are ~~really~~ saying but can’t say...

A lot of reads a bit too skeptical and incurious about tech (a preemptive elegy for AI is a bit on the nose) but that is probably the perfect center of the venn diagram between NY financiers living in Brooklyn and harboring literary/cultural ambitions and leftists-cum-Odd-Lots-fans who are reading and writing this (guilty as charged). Excited to see the next quarterly edition.

The art direction is great down to the partners they’ve chosen to work with as advertisers.

Notes

• This is a really fantastic slide from Redpoint’s market update deck/post.

• YC quietly removed delve from its directory without issuing a public statement. I really don’t get who that’s for/that seems like the most mealy-mouthed, worst version of a comms strategy. Stand by your guy or don’t, especially if you want to be the self-proclaimed moral voice of tech, as Garry does. ICYMI Delve did a big fraud on a bunch of other startups (allegedly) and might be at least partially responsible for the Mercor hack... bad!

• GLP-1s are a bigger business than AI. Continue to watch this space. Were it not for AI, they would be widely viewed as the most important thing in the world right now.

• One of my favorite posters posits that maybe only 3 jobs: innovators, marketers, and context carriers. Personally I prefer my four jobs but he makes good points 😉

A note on competition/conflicts:

Here’s an email I wrote to a founder on how we think about investing in competitive companies (which, in fairness, we basically never do). Some people got Big Mad at me online which felt fairly performative - just another salvo in the fight to prove (to whom idk) that you’re The Most Founder Friendly...

To me the takeaway is actually fairly positive sum: companies don’t really succeed and fail on the basis of some competitor, at least not until they’re much further along. We don’t need to kill the other crabs to escape from the bucket.

Slow Security

Super stoked for this: we’re hosting founders, operators, security leaders for a ≈100 person cyber security mini conference in NY next month.

We’ll have Anthropic’s head cyber and NatSec policy for a fireside chat and panels with some excellent security operators and investors.

Sign up to join us. Space is limited and we want to prioritize builders and buyers.

There are only four jobs.

A few weeks ago I wrote this aside about how companies/jobs/functions are reorienting toward a new organizing principle. Then this week it went tragically/comically viral for no good reason (my linkedin is broken now). So it’s now worth restating the case.

There’s a very real possibility that the only jobs in tech companies are going to be:

1. product eng/vibe coder/PM/slop cannon: self explanatory. This is the high velocity, high tool use generalist. they are obviously not restricted to product and eng roles. Anyone can be commercial and product minded.

2. SREs/infra/security/systems: we’re going to be producing so much STUFF across every org that there’s going to need to be really really good people stitching it together, making it stable, secure, and robust.

3. Adults: sometimes you need a grown up in the room to just say “hey, come on.” They are effectively a much needed governor on an otherwise accelerating organization. You will find them across roles but there are obvious places like legal and finance where you’re NGMI without an adult in charge.

4. Hot people: You will find hot people in roles ranging from sales, to people, to CX. There will always be an important place for those who present an easy UX to the world and are pleasant to be around. Remember, there are many ways to be hot.

First, these are working styles and archetypes, not job descriptions. The latent traits have always cut across job titles and orgs. To ask “what about design” or “where does my job fit” is the wrong question/fails to comprehend what’s going on. The right question is how do you approach your job irrespective of the title.

Second, it’s probably not possible to be all of these. It may not even really be possible to be more than one or two. To be spiky in all things is to be smooth. If you’re saying you’re all four you’re probably a) wrong and/or b) misunderstanding my point.

Third, this new quartet very well may replace the classic trifecta of product/design/eng. That iron triangle was organized around categories of output. When anyone can produce code, designs, and specs, organizing around what you produce is meaningless. Instead the highest velocity teams will organize around how they produce.

The best AI native companies are increasingly recruiting commercially minded engineers regardless of the role. They explicitly want people who are comfortable using tools AND thinking about product AND thinking about customers. The salespeople are shipping (at least internal tools and automations for themselves) and the engineers are relentlessly focused on customer value.

The highest performing companies will have ‘product engineers’ and slop cannons in every role (product/eng, sales, ops, talent, finance, CX, marketing, etc); it is a multi-hyphenate skill set crucial to accelerate each area of the business.

Conversely, there are “SREs” everywhere for those with the eyes to see them. The basic function within their org is the same: to provide scaffolding that lets other people move fast and cleans up behind them. Whether that happens in marketing (QA and copy editing) or engineering is irrelevant, the value to their org, and by extension the company, is the same.

In a world of rapid acceleration and internal decentralization (everyone can autonomously execute everywhere simultaneously), you need adults who can rely on judgement and earned intuition. Sometimes that means saying no with authority to prevent catastrophic errors and acceleration off a cliff. Remember, velocity is a vector (it requires direction) and momentum requires mass (the work needs to matter). Adults can help keep you on the golden path. This is self evident.

You cannot win without hot people. Hot people are the interface layer. Externally they make the thing legible and attractive. Internally they make the org cohere. They’re the reason people want to show up to work and the reason people want to buy from you. Remember, there are many ways to be hot and I will not elaborate on this further.

I'm not an employment doomer. The biggest companies will get more efficient (lower headcount) but there will be lots more companies and the boundaries of "tech" get fuzzier every year. And to the extent that there are fewer engineers (objectively wrong at this point) it’ll only be because many of them get subsumed into other “non-technical” roles.

Some Stray Notes

• I’m not the first to point this out but the OpenAI/TBPN deal is clear proof of the immense value of hot people. Jordi and Coogan are equivalent to AI engineers.

• The NYT reported on what purports to be a ≈$1B revenue, one person GLP-1 company. It seems to be a fraud and the numbers are probably either fake or misleading. This is what happens when a slop cannon builds a HC company without an adult in the room.

• This is all orthogonal to agency which is important for everyone in every role in a highly performant, accelerating company.

Slow Security

Super stoked for this: we’re hosting founders, operators, security leaders for a ≈100 person cyber security mini conference in NY next month

We’ll have Anthropic’s head cyber and NatSec policy for a fireside chat along with panels with people building and backing security companies. More to come soon.

Sign up to join us. Space is limited and we want to prioritize builders and buyers.

Read on for internet drama about agency, my plea for more positive sum thinking in healthcare “innovation,” and a plug for our Slow Security mini conference ft. Anthropic.

People were mad online

Last week I tweeted and people got very mad at me for being insufficiently deferential to their very special relationship with claude…

Here’s why I’m right, and here’s what’s at stake.

What an agent is, and where agents are useful

An agent takes action on your behalf where you are the principal. An app does not. We know what apps are. We’ve been using apps for a long time, and there are lots of good AI features that can make apps work a lot better, which is a far cry from saying that the AI will proactively organize your life for you...

There is a reasonable argument that by now ALL AI products are “agentics” or have “agentic” qualities/features: browsing the web, deciding what modality in which to respond to a prompt, etc. are all actions taken on behalf of users. But if every product with AI is an “agent,” it’s a meaningless term and the whole argument reduces down to “is AI useful” which it obviously is.

The important debate is what it’s useful for, and where it hits natural limits that have nothing to do with scaling laws or inference costs - at least short of physical AGI.

AI agents are nascent but the overall concept is not so new that we already know where they can/will be useful: the middle ground of complexity between purely rote tasks (can do, maybe not necessary) and highly effortful/intentional personal endeavors (can’t do).

I totally believe that things that require a measure of coordination and memory are useful surface area for agents. That can include things in the real world. Finding service providers, doing your taxes, scheduling appointments: that’s the middle of the curve where an agent with sufficient context can probably make your life a little better around the margins.

But there are hard limits here. If it takes a little bit of agency you can make gains by handing off to an agent (price compare a bunch of stuff vs. buying the first result on Google). But if it takes a lot of agency (cleaning your apartment or reading a book) the agent is useless. Going to the gym with AI that helps plan a workout only matters if you get yourself to the gym and claiming that an AI that makes you a workout plan is “agentically getting you into shape” is just baby talk.

Things that require agency require YOUR agency to work.

Of course life contains work. Sometimes that’s a problem to solve but sometimes that’s just life. And when it is a problem to solve it may not be solvable by AI, let alone an agent specifically.

AI may be able to help you even if it’s not primarily an agent. AI features inside apps can be useful across the whole spectrum. The agent question is overly narrow and specific.

The confusion in the discourse is collapsing “AI is useful” into “agents are the future of consumer,” and those are completely different claims.

Real life doesn’t happen via command line

Of course people do work in their lives but most of it (the hard stuff) does not look anything like the work they do at work. Real life is rarely accessible via the command line.

This list is... something. It mashes together completely different categories of life as though they’re all the same kind of problem.

Maxis hear “agents can’t do X” and get butthurt about “doomerism” ignoring that what you can do and what you should do are not 1:1. There are limits to each of possibility and desirability, largely unrelated to one another.

On desirability: you can already outsource gift-giving with a gift card, a corporate gifting program, or an assistant. But doing that misunderstands the rich culture and history of gift giving. To give a gift is to say something about yourself, the recipient, and your relationship together through an item. An agent-chosen gift is impersonal and cold like a gift card.

On possibility: there are problems that are just beyond the capability of agents because they’re not defined by coordination and memory at all. Sometimes they come down to skills and physical manipulation, where the coordination of that process is limited in its effectuation of the outcome.

An agent can find you a handyman, but it isn’t going to oversee that entire process: noticing the problem, explaining it aloud, clearing out the space so they can work, making time in your schedule, being home, opening the door, showing them where the problem is, answering their follow-up questions, pointing out the part they missed, noticing they scratched your floor, checking that it’s actually fixed, deciding you don’t like how it looks and asking them to redo it.

It will still take work from you to do a good job even if you outsource to a handyman via an agent. And the agent certainly can’t just fix the shelf itself.

And anyone who thinks agents will make parenting or running a household easier should read More Work For Mother.

What’s at stake

I will never bet against laziness. But outsourcing your social and emotional life to an agent is bloodless at best and demonic at worst.

Having a machine take over your life to smooth out all its inconveniences and to view all life’s friction as surface area to optimize is both profoundly bleak and wrongly technomaximalist. Claude cannot give you the will to change yourself. Not all struggle is suffering.

The only way to make agents work for most of that list is to profoundly change yourself to live for the AI instead of the other way around. We already do this in small ways (saying things aloud to ensure Granola hears it, etc). In darker terms it will mean avoiding paths inaccessible to the agents: only buying what can be delivered is an atomized, limited life.

I empathize with the optimization view. I often treat things that way and wish others would take care of things for me/that I could outsource every hassle. But it’s not something to be proud of.

Planning a trip together is an opportunity for connection and collaboration. We should strive for that even when it costs us convenience. The friction is part of the experience - sometimes a really valuable part.

The point isn’t asking what an agent can do (some stuff) or how useful AI is in general (very) or even what an agent is (who knows). The point is asking what is good and desirable: a life of rich connection where technology serves you and you exercise agency to be the person you want to become.

Thanks for Chris Melamed for reading and shaping.

Positive Sum HC

Most healthcare “innovation” is zero-sum at best, negative-sum at worst. I want more positive sum HC ideas

Basically every HC idea boils down to:

• Pay providers more(drives up premiums, bad for patients)

• Cover more care (drives up premiums, bad for patients)

• Deny more care / pay less (bad for providers and patients)

Lots of shifting money around, very little to expand the pie. Much of this is just a reflection of the fact that “health insurance” isn’t really insurance; it’s catastrophic care insurance bundled with a rate card and a provider directory.

Prior auth automation/arms race is exemplary of the problem. You automate getting through hoops so payers build new hoops. Both sides spend more on admin despite the “efficiency.”

Positive-sum ideas I want to see/am rooting for:

• Gold carding/eliminating prior auth entirely.

• ICHRAs: an intermediate step to decoupling insurance and employment

• AI for low-acuity care: 80% solution at 10% of the cost; improves outcomes per dollar vs “expanding access” which just increases volume/premiums

• Care coordination: investment with a return on adherence lower readmissions

• VBC: right in theory, but admin overhead recreates the disease and blocks out small providers

• Pharma/new drugs: outside my purview but the purest positive-sum play. GLP-1s are the most important thing in the world after AI.

My personal blackpill: there are very few novel ideas for positive-sum systemic change in the biggest market in the biggest economy in the world.

Slow Security

Super stoked for this: we’re hosting founders, operators, security leaders for a ≈100 person cyber security mini conference in NY next month

We’ll have Anthropic’s head cyber and NatSec policy for a fireside chat along with panels with people building and backing security companies. More to come soon.

Sign up to join us. Space is limited and we want to prioritize builders and buyers.