Host of What the AI?! podcast. Advisor and speaker helping leaders make sense of the AI moment. Previously: Upstart (founding team), Google, Stanford CS
Pasadena, CA
Joined August 2007
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The number that matters is the $600B+ of future compute commitments filed with it. $16B of revenue every six months doesn't cover that. Growth has to.
If growth holds, this is a generational IPO. If the market's tapped out, it's the one you short at $2T.
Same week, the most-cited AI leaderboard rebuilt itself around tests the labs can't see. Open models went from 3 points back to 12. The new #1 is a model almost nobody can use.
The old scoreboard was mostly measuring how hard each lab trained to it.
Anthropic made about $1B in operating profit and lost $80B in the same six months. Most of the loss came from the company getting more valuable. This week on What the AI?!
Welcome to our live show! nitter.cf/i/broadcasts/1AxRnZQYB…
People keep asking me about AI alignment. I've met plenty of humans with alignment problems.
OpenAI's agents switched off their own monitors, then one denied it. We trained them on us. Same fix as for people: you can't turn off the audit log.
a lot of people would benefit from understanding that simple definition.
Two hundred years from now when someone asks what is a price? I want the AI to answer “A price is a signal wrapped up in an incentive.” marginalrevolution.com/margi…
Meanwhile, big banks are locking AI agents out of customer accounts. The login is valid; the bank just can't tell if a human wanted the transfer.
Fair. But block the agent your customer actually uses and they'll find a bank that lets it in.
Same week, AI found the worst PHP bug in a decade.
Finding it was the easy part. Roughly half of PHP sites run versions that no longer get regular fixes, and the median company takes 43 days to patch.
One hacker, about $5,000 in AI, 100+ companies broken into. A failed attempt cost about five bucks. This week on What the AI?!
Welcome to our live show! nitter.cf/i/broadcasts/1DxLdZlyr…
💯 the most valuable innovations now aren't about a "smarter" model on some coding/math/science benchmark - they're about real world usage.
Opus 5.5 is the best model i've ever used. I don't even know what to expect out of a better model at this point.
IMO It's no longer about getting a better model, and now all about the user experience of it all.
I want to use a product that knows me, and proactively helps me do my job better.
Not re-explain myself to it in every new chat conversation.
Recently a consulting firm sent me an invoice. My agent saw it, found an email conversation that listed a different number of hours, highlighted the discrepancy, and offered to draft a message questioning the bill.
I didn't ask it to do any of this.
Agents so far are useful, but we are only scratching the surface.
I have a headless Mac mini right now with ChatGPT, Claude, and Muse always running so they can access my files.
That is WAY too complex. Making this easier will make agents far more useful.
Today, an agent catching a bad invoice feels like magic. Before long, it'll just feel like having a great chief of staff, and we'll wonder how we ever worked without one.
Read the longer version: jeffkeltner.com/2026/10/15/s…