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.

We found another surreal place on our way. I know some people will say I’m too positive about everything I see, but this place was crazy. They had a shooting range in the store.

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In America, a stranger will rename you in a single breath, and you are simply expected to come when called. I went to eat at a busy restaurant. A young man at the front asked for my name, to mark my place in line. I gave it the weight it has carried for eight hundred years. "Nobunaga." He smiled, nodded, and wrote it down with great confidence. Then he read it back to me, to be sure he had honored it correctly. "Perfect. Banana, party of one." Banana. He had heard my name, held it a moment, and returned to me something rounder and more cheerful. To refuse the name a host gives is to refuse his welcome. I bowed. I was Banana now. Then he handed me a small black disc, said it would "light up and buzz" when my table was ready, and turned to the next guest as though he had not just placed a living thing in my hands. I held it in both palms, the way one holds a small sleeping beast that may wake. I found a place to stand. I waited, ready. It woke. It screamed. It flashed red. It leapt and shook in my hands like a captured spirit demanding release. A lesser man would have dropped it. I did not. I gripped it, steady, looked into its blinking lights, and told it, in a low voice, that its time had come. Then I carried it back to the host with both hands, the way one returns a hawk to its master. He took it without looking and shouted across the entire room. "BANANA! Party of one, your table's ready!" A hundred strangers turned. I rose. I crossed that floor as Banana, spine straight, chin level, a man answering to his name. A child pointed at me. I gave the child a small bow. He had recognized me. All through the meal they kept me. "How's it tasting, Banana?" "More water, Banana?" The check, when it came, said Banana, and thanked me for visiting. By the end the whole staff knew me. They waved as I left. "Night, Banana!" So tell me honestly. For eight hundred years my clan answered to one name. Tonight I answered to a fruit, calmed a screaming relic in my bare hands, and ate among people who were glad I came. When the little disc lights up, is the table truly mine, or am I only keeping it warm for the next Banana? Because I have already decided to return on Friday, and to ask, very humbly, for the same disc.

『METAL SLUG』の開発中、魔法使いと呼ばれていた天才プログラマー、ANDY君が作ったドット絵エディター『キャメル』。 それは、まさにドッターたちにとって、夢のようなツールでした。 その名前は、当時ANDY君が好きだったタバコ『Camel』から取ったもの。 ツールのアイコンには、タバコのパッケージに描かれているヒトコブラクダ『オールドジョー』を、ANDY君自らドット絵で描き起こしたものを使っていました。 アイレムで使っていたドット絵エディター『さだやんペイント』には、『海底大戦争』でSUSUMU君が表現していた水中背景の揺らめきのような、ラスタースクロール表現を簡単に作れる機能があったんです。 その機能は『キャメル』にも引き継がれており、『METAL SLUG』でも、砂漠の遠景を陽炎のように揺らす表現などに使っていました。 その機能を使い、さらに一歩踏み込んだ表現として作られたのが、UFOが放つトラクタービーム等のエフェクトです。 トラクタービームの絵は、ビームの形と重なる背景の絵をそのまま使い、その絵のカラーパレットを、発光して見える数種類のカラーに入れ替えながら、さらにラスタースクロールをかけることで、ビームを通して見た背景が揺らいで見えるように表現しているんです。 このエフェクトを作ったのは、ドッターのTOMO君なんですが、UFOと背景の座標を完璧に一致させないと、なんちゃって半透明に見えなくなってしまうので、TOMO君は敵配置担当のmeeher君に、こう念を押しました。 「ビームエフェクトを1から作り直しになってしまうから、UFOと背景の座標は絶対に変更するなよ！」 すると、meeher君は、 「わかった、絶対に変えない」 と言っていたんですが、数日後UFOの位置を変えてしまいます。 meeher君は、TOMO君が、とんでもない手間を掛けてあのエフェクトを作っていたことを理解していなかったようで、めちゃくちゃ怒られていました。 あの頃のTOMO君はスケジュール度外視で、納得がいくまで時間を使ってしまうドッターだったので、通常の担当作業に組み込むのは難しかったんです。 そこで、後輩たちの絵の手直しや、クオリティアップに繋がる作業を、やりたいようにやらせていました。 手が遅くても良い仕事をするクリエイターには充分な時間を与え、作品全体のクオリティアップに努めてもらう。 そういう贅沢な人員配置も、メタスラの拘りの一つかもしれません。 あの半透明に見えるエフェクトは、そうやって時間を気にせず動ける存在と、『キャメル』があったからこそ生まれた表現なんでしょうね。 #METALSLUG #PixelArt #retrogaming

Steven Spielberg gives his thoughts on AI usage in filmmaking: “I don't believe there is any substitute for the soul. I don't think that's an algorithm that is inventible... don't tell me I don't have the right antagonist in this story, don't tell me how to write my dialogue, don't tell me where the camera has to go… If AI wants to help me find locations, that's great. Saves us some leg work… Use AI as a tool, but do not use AI as the final word on anything creative.” (Source: youtube.com/watch?v=Orr-EnuJ…)

Former Ferrari chairman Montezemolo tears the new electric Ferrari “Luce” apart: “I cannot say what I really think: I would harm Ferrari. We risk the destruction of a legend. So sorry. Take the Prancing Horse off. At least the Chinese won’t copy this car”