Categories
AI

Keep That Thread Running

Full disclosure, same as last time: Instinct helped draft this post about working with Instinct. That was the honest way to do it with Leif, and it’s the honest way now.

Instinct is the other AI assistant in my life (see my earlier post about Muse). It lives in my iMessage, a thread like any other — no app, no dashboard. I text it the way I’d text a person, in short bursts between other things. The first message was September 13: “Hey Instinct!” Two days later I gave it the book.

I’m writing a history of Interstate 280, and inside the first hour we had the shape of the research: the personalities behind the routing decisions, the archives worth calling, a working list of what I call “side shows” — the statue, the water temple, the 22-foot median, button-copy signs. When it offered to keep digging on its own and check in weekly, I gave it the three words that defined the arrangement: “Yes keep that thread running.”

It does. Last week the thread came back with a 1964 issue of California Highways and Public Works crediting architect Mario Ciampi with the first I-280 contract — the curved deck edges, the varied piers, the railings drawn to avoid metal guardrails. Same issue, same gift: the median I’d been describing as a fixed 22 feet was actually built variable-width across the watershed. That’s the correction that saves a chapter from carrying a bad fact.

The on-demand dives go all the way down. I found the audio of a Caltrans engineer’s oral history on archive.org — an hour and forty minutes, no transcript anywhere — and it worked straight from the audio. I sent it two days of AI-conference livestreams asking for transcripts, community notes, the whole nine yards, and it came back with a report, a source ledger, and an honest negative finding: the community-notes document I wanted doesn’t exist. When I asked for the freeway’s 1973 opening brochure, it reported that no cataloged copy exists anywhere — then handed me the leads to work anyway. Sourced absence is an answer. I’d rather hear that than a confident maybe.

When the book thread got long, it pulled everything — people, side shows, archive routes, open questions — into a single research page I can hold in my head. I told it thank you and meant it.

It’s also my markets desk and my magazine desk. A profile I’m circling started at 4:48 in the morning with “Someone should do a profile of Dylan Patel,” followed by “Yes. Go for it.” Minutes later: “What about citrini” — which turned out to be the same story, since SemiAnalysis had acquired Citrini the week before. It fields my investor-day puzzles (the stock slides while management presents — which explains which?), gives me its best bet when I ask for one, and labels inference as inference so I don’t have to.

The small stuff adds up too. When was the last US oil refinery built? 1977 for the big kind, 2022 if you count the small ones — EIA’s answer, in under a minute. Five cash-secured put candidates, screened the tastytrade way. My New Balances — the model I re-buy, in just my size — at a discount: it researched, shortlisted, and then waited, because purchases happen when I say so and not before.

The strangest moment so far: I sent it a Loom of Sequoia’s Pat Grady giving an AI talk and asked for the highlights. It read the full caption track instead of the page summary — and there in the highlights was Grady name-checking Instinct itself as one of the “magical apps.” I watched a Sequoia partner praise the assistant I was using to watch him.

How I work it: terse. “Sure.” “Wow.” “New subject:” — announced or not, and it keeps up either way. It flags what it can’t verify instead of papering over it, and for anything going out under my name I read every word first. Same arrangement as with Leif: the tool is fast and tireless and mostly right. I’m the judgment.

What’s different is the division of labor. Leif runs the standing operation — the briefings, the audits, the daily drumbeat. Instinct is the research desk: it works in bursts, the way I do, and keeps a thread running in the background in between. Two weeks ago I’d never heard of Mario Ciampi. Now he’s in the book.

If you want to try Instinct yourself, I have a handful of invites, first come first served: https://app.instinct.com/invite?t=7qmw2a3u2vjz4nkvi235hhqloy&preview=imessage

Categories
AI Anthropic Business Google

The Weight of the Bill

Jordi Visser has been making the case for months — in his weekly YouTube commentary and on his Substack — that we are living through an exponential transition that most people are measuring with the wrong instruments. I think he’s right. I found two data points this week that suggest why.

I was somewhere in the middle of an Invest Like the Best episode when Dylan Patel said it — almost as an aside, the kind of thing you drop to establish context before moving on to the point you actually came to make. His firm, SemiAnalysis, analyzes the semiconductor and AI industries for a living. And their usage of Claude, he noted, has been growing. The costs have been growing too.

Exponentially.

He moved on. I didn’t.

I think Patel’s API bill might be one of the more honest documents in the current AI moment — more honest than the analyst reports his firm produces, more honest than the earnings calls where every public company performs its AI fluency for shareholders.

Surveys bend. When you ask someone whether they’re using AI in their work, you’re asking them to self-report on a technology that has become a proxy for relevance, for not being left behind. The incentive to say yes is enormous. And even when the yes is genuine, it tells you nothing about depth — whether AI has become load-bearing in how someone actually works, or whether it’s an impressive thing they do occasionally.

Nobody pays exponentially growing API costs for show. Money is the honest witness.

What makes Patel’s situation quietly strange is the recursion in it. SemiAnalysis exists to help sophisticated investors and technologists understand this industry — and they cannot predict their own consumption curve. They are inside the exponential the same way everyone else is. They just happen to be watching their bill.

Then this morning, a different number arrived. Google announced it will invest up to $40 billion in Anthropic — $10 billion committed now, another $30 billion contingent on performance milestones. This follows a separate $5 billion from Amazon, part of a broader arrangement under which Anthropic is expected to spend up to $100 billion on compute over time.

The temptation with numbers like these is to treat them as spectacle. Forty billion dollars is so large it becomes almost aesthetic — a statement about ambition, about the kind of bets that define eras. You feel the weight of the zeros and move on.

But I keep coming back to Patel’s API bill.

Because Google’s $40 billion and SemiAnalysis’s compounding monthly costs are saying the same thing, expressed at scales so different they almost don’t seem related. One is a research firm noticing that their tool usage has quietly escaped prediction. The other is one of the most sophisticated capital allocators on earth making a bet that strains comprehension. But both are pointing at the same reality: that this technology, wherever it takes hold, does not plateau. It compounds.

We have been waiting, I think, for the moment when AI adoption becomes legibly real — some threshold event that separates the signal from the noise, the press release from the actual change. The surveys were supposed to mark that moment. The enterprise announcements. The benchmark numbers.

Patel’s aside suggests we’ve been waiting for the wrong thing. You don’t arrive at the exponential. You just eventually notice you’re already in it — in an aside on a podcast, before moving on to the point you actually came to make.