Emilie Choi 🛡️

President and COO at Coinbase, Angel Investor

[yuga.eth 🛡 @yugacohler]

X returns a 402 Payment Required HTTP code when an AI agent tries to fetch a tweet.

x402 was built exactly for this:
- Enables agentic endpoints with API keys
- Seamless, permisionless monetization
- The protocol is already named after you (@X + 402)!

[rob @rwitoff]

Turns out X already implements HTTP 402, but there's no automated way for agents to get past it.

If they upgrade to x402 we all win. The future is so close, and so obvious.

@nikitabier wdyt?

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[lincoln.base.eth @MurrLincoln]

https://t.co/8gDlEzzLNa

[Gokul Rajaram @gokulr]

THE TOKEN HANGOVER

@matanSF (Matan Grinberg), CEO and co-founder of @FactoryAI , interviewed by @HarryStebbings (@20vcFund )

This is a special for me since I've been an investor in @FactoryAI since their seed round, and think Matan is a very very special founder.

Summary: Grinberg argues the next 24 months in enterprise AI are a resource-allocation problem: tokens, dollars, and people. Most CIOs are now waking up to bills they cannot justify. The fix is to spend frontier tokens only on the 10-20% of work that requires planning intelligence, run the other 80-90% on open models, and rebuild teams around load-bearing polymaths who own business outcomes. The single-frontier-monopoly fear is fading: four roughly-equivalent labs is the emerging reality, which puts pricing power back in the application layer.

1. The Token Hangover. Enterprise AI adoption ran through three phases this year: boards yelling at CEOs about AI strategy, "token maxing" with AI usage written into perf reviews, and now the morning-after bill. One CIO Grinberg spoke to was spending hundreds of thousands of dollars a month on engineers asking Opus 4.8 things like "how's it going" and "what are my macros from lunch." The frontier model became the default surface for every question, no matter how trivial. Phase 3 is the moment routing matters: every call to a frontier model needs to earn its price.

2. Resource Allocation Is the Job. For the next 24 months every C-suite is solving the same problem: how to allocate dollars, tokens, and headcount against business outcomes. Engineering teams used to be judged by features shipped per quarter, a metric with no link to revenue, market share, or retention. A logistics company adding more engineers to ship more features was always solving the wrong problem; AI made the misallocation visible. Tie every person's work to the metric that actually moves the business, then re-allocate.

3. Load-Bearing Individuals. The "10x engineer" frame measures lines of code, the wrong unit. Grinberg's unit is the load-bearing individual: the person whose absence breaks something. With AI the load-bearing few compound roughly 10,000%; the others get close to nothing, so any org enforcing one token-spend-per-engineer number is painting with too wide a brush. Average token spend per engineer will land on the same order of magnitude as their salary within three years, with a wildly bimodal distribution.

4. Frontier for Decisions Only. 80-90% of software development tasks can run on open models; the remaining 10-20% is planning, where the frontier still wins. This mirrors how human orgs work: leadership is a tiny share of total hours but decides the company's fate. The ego trap is engineers assuming their work is too important for an open model. The router decides better than the engineer, and the cost curve falls only if you wire the routing.

5. The Kirkland Mistake. Kirkland & Ellis announced a $500M, five-year internal AI build, which Grinberg reads as validation for Harvey rather than a threat. Building AI is not a law firm's core competency, and Kirkland's spend will teach them how hard it is. The general rule: just because you can build it does not mean you should, and the discipline is naming the few things you and your team own end-to-end. Outsource everything else, even when you technically know how to do it yourself.

6. Model-App Separation. When the model provider also sells the app, the incentives split: an API business wants you to spend more tokens. A healthy market keeps the application layer independent, so model providers compete on price, speed, and quality every week. Enterprises do not want to vendor-lock again; every CIO carries scars from the cloud era's three-year discount-then-jack-the-price trap. The application layer survives precisely because it forces that competition.

7. Sales as Product. Name a legendary company with a weak sales or marketing team. You can't. The Silicon Valley fallacy that research sits at the top and sales is "dirty work" produces companies that win the gold rush and then collapse when gravity returns. At Factory, engineers and salespeople sit intermixed; when sales closes, engineering says "we closed"; when engineering ships, sales says "we shipped." Atrophied sales muscles will not regrow once enterprise buyers stop saying yes to everything.

8. Polymath Era. Da Vinci, Newton, Euler could be polymaths because their fields were shallow. By the 2010s a theoretical physicist needed 50 years to reach the frontier before contributing anything new. AI collapses that catch-up time, so one person can push forward developer marketing, token-caching infrastructure, and solution engineering at once. The engineer of the future is a GM who owns marketing copy, product metrics, and sales enablement.

9. Build the Factory. Factory's name is literal: engineers in the next era design the assembly line that produces software. The DevX investments that used to scale linearly with headcount (good docs, CI/CD, linters, pre-commit hooks) now scale with the number of agents you run, which is 10x or 100x larger. Every dollar spent making agents production-ready compounds against thousands of PRs a week. Humans move up the stack, from writing code to designing the system that writes code.

10. Seal Team Six. Mandating beds in the office is a hiring failure dressed up as commitment. Grinberg's image: a basketball game judged by who sweat the most, when the scoreboard is what counts. Factory bought eight sleeps for all 30 team members at the time, because recovery is where the gains come from when work requires every ounce of brain power. If your load-bearing engineer can do their best work on two hours of sleep, they were not doing load-bearing work in the first place.

11. Four Frontier Labs. Grinberg's biggest mind-change this year: a single dominant model is unlikely, and four roughly-equivalent frontier providers is the more probable steady state. That outcome is the win for humanity. A one-lab monopoly was the dangerous scenario, and four equivalent labs is also the structural bull case for the application layer because it forces real ongoing price competition. Every CIO Grinberg meets has already decided not to throw their lot in with a single provider.

12. Dario's Self-Serving Doom. "AI will take your jobs" was the pitch that helped raise hundreds of billions, and Grinberg thinks it damaged public psychology and fed the slow-AI lobby. Watch the rhetoric flip at IPO: humans will suddenly become important again, because humans are the ones buying the stock. Founders who never needed to raise that money, like Zuckerberg and Hassabis, never made that argument. Incentives drive the labor-displacement rhetoric more than philosophy does.

[Nate Silver @NateSilver538]

I know Paraguay, homefield, etc. but that was literally the best half of World Cup soccer for the USMNT in 96 years.

[Dor @dorvonlevi]

The most frequent feedback I get (especially at @coinbase) is that I could be more concise, or "Can you make this into a bullet point?"

My usual defense was that I'm not trying to transfer information. I'm trying to infect people with a way of thinking or an idea. The bullet gives you the conclusion without the path, and the path is what changes how you see the next ten problems.

And while I agree with my defense, it can also be an excuse. I kept trying to be more concise, but I didn't have a good forcing function for it, because "the idea needs room" justifies any length.

This tweet from @paulg last week really stuck with me. I think about it every time I write now. (my agents too)

P.S. This could probably be summarized better.

[Emilie Choi 🛡️ @emiliemc]

@nikillinit Congrats! So happy for you!

[Coinbase 🛡️ @coinbase]

With over $200B of trading volume in the US alone, we'll just call them what they always were.

US Perps.

22 assets. Institutional-grade liquidity. No expiration.

Live on Coinbase (for a year now).

[Szymanski @Szymansk_ii]

Next time you think of giving up, remember this photo of Elon in 2008.

[Emilie Choi 🛡️ @emiliemc]

Gold and silver futures will be trading 24/7 in the US for the first time ever.

[Coinbase 🛡️ @coinbase]

For the first time ever, US-regulated gold and silver futures won’t be closing for the weekend. Or ever.

24/7 trading goes live tonight on Coinbase.

With oil, and more, coming soon.

[Coinbase 🛡️ @coinbase]

For the first time ever, US-regulated gold and silver futures won’t be closing for the weekend. Or ever.

24/7 trading goes live tonight on Coinbase.

With oil, and more, coming soon.

[Emilie Choi 🛡️ @emiliemc]

@BloombergTV @CarolineHydeTV Enjoy your adventure of a lifetime @CarolineHydeTV! Amazing run

[tobi lutke @tobi]

You have absolutely disgraced yourself publishing this, globe.

We all clearly don’t hate the media enough.

[Katherine Boyle @KTmBoyle]

“It is certainly hard to believe that a little company that started in a warehouse in El Segundo is now going public with the largest IPO ever.”

Only in America. Congratulations to @elonmusk @SpaceX. This is the American Dream 🇺🇸💪🚀

[Paul Grewal @iampaulgrewal]

When we see CLARITY signed into law, there better be a big gold chair in the middle of the front row for @patrickjwitt . Heroic work being done to get this over the finish line.

[cat ferdon @catferdon]

you know you struck a chord when people text you about an ad. my phone blew up when this ran during the NBA finals last night (and several texts came from self-proclaimed vest-wearing finance bros). the memes are still incoming and the general gist is: 'i feel seen lol’

love working with this team & glad to know the message landed with so many who are willing to laugh with us

[Emilie Choi 🛡️ @emiliemc]

@blauyourmind Working on it!

[Emilie Choi 🛡️ @emiliemc]

Welcome to agentic finance.

Now you can connect your AI agent directly to your Coinbase account, so it can operate for you.

[Coinbase 🛡️ @coinbase]

Meet Coinbase for Agents.

Give your agent its own account to:

→ Execute trades & manage your portfolio
→ Run autonomously under guardrails
→ Pay for data & research tools via x402 (coming next week)

Agentic finance is here, and it's powered by Coinbase.

[Karri Saarinen @karrisaarinen]

When we started @linear, we wanted to make product work feel more coherent across the whole team.

Agents can now do more of the work, but too often they operate from an empty prompt, in isolation, for one person at a time. That risks creating a new layer of fragmentation.

We think the larger shift happens when agents work from the same context as the team.

With the new coding sessions, Linear Agent can now move from intake to investigation, code, and review inside that shared environment.

This completes the product development loop we’ve been building toward: from intake to merge, with the team’s context intact.