Product guy in health tech. Ex-founder. Starting to build again.
New York, NY
Joined October 2009
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Chris retweeted
One pattern I find useful for working with LLMs is a nice long ramble session. Sometimes the LLM needs more bits to understand what you're trying to achieve, but you're too lazy to type them. In these cases I like to lean back, switch to /voice and just ramble for like 10 minutes, total mess, anything goes, full stream of consciousness. Sometimes I declare it up top, something like "switching to speech recognition sorry for any typos...". Sometimes I turn it into a small interview of a few turns. But I find that the LLMs are somehow very good at reconstructing long incoherent rambles and often their echo of your own tangle of thoughts comes out quite a bit cleaner than what you started with. The result is that you improve the mind meld and have to correct things less from that point on.
Chris retweeted
Morgan Stanley has again raised its capex forecasts for the five hyperscalers Amazon, Alphabet, Meta, Microsoft, and Oracle. It now expects them to spend about $805bn this year, up from a previous estimate of $765bn. For next year, the forecast has been lifted from $951bn to $1.1TRILLION. To put that into perspective, their 2026 spending alone would be roughly equal to what all non-tech companies in the S&P 500 spent combined in 2025. The expected ~$800bn for 2026 is nearly double 2025 levels and about three times what was spent in 2024.
Chris retweeted
Amazing! @NotebookLM just rocks!
New @NotebookLM: The Collected Works Of Jane Austen. Full text of all of her novels, letters, juvenilia, bio, and more. We designed this one for fan-fiction creators as much as for students and scholars. notebooklm.google.com/notebo…
The Austen Featured Notebook is a particularly compelling showcase of our new Slide Deck feature. We've got everything from a sophisticated overview of the underlying economics of Austen's plots, to a biographical account of how she effectively invented a new career path of a commercial female novelist -- all the way to a proposed graphic novel treatment for a Pride and Prejudice sequel where Mr. Darcy turns out to be a vampire.
Chris retweeted
>you open chatgpt/grok/gemini
>dump brilliant wall of text into the box
>hit enter
and stare at a mid reply that completely misses the point, or worse... sounds smart enough to fool you.
the reason is: you are used to solving problems alone, in your own head, with your own assumptions.
the real separator is not prompt engineering tricks or raw iq, but the theory of mind for ai, or in other words your ability to think from the model’s point of view and design around its blind spots.
- what does it already know
- what context is it missing
- where could it hallucinate
- what needs to be pinned down so it cannot misunderstand.
most people never ask these things, they just keep throwing bigger prompts at the same narrow channel.
quietly, a lot of people are getting mediocre outputs from top models because they treat ai like a smarter search bar, not a partner that needs clear framing and guidance.
practical shift: before you hit send, pause for one second and ask yourself: “what might this model misread or not know here?” then rewrite your prompt with that in mind.
the edge is in how clearly you can think on behalf of the model.
MIT researchers just proved that prompt engineering is a social skill, not a technical one.
and that revelation breaks everything we thought we knew about working with AI.
they analyzed 667 people solving problems with AI. used bayesian statistics to isolate two different abilities in each person. ability to solve problems alone. ability to solve problems with AI.
here's what shattered the entire framework.
the two abilities barely correlate.
being a genius problem-solver on your own tells you almost nothing about how well you'll collaborate with AI. they're separate, measurable, independently functioning skills.
which means every prompt engineering course, every mega-prompt template, every "10 hacks to get better results" thread is fundamentally misunderstanding what's actually happening when you get good results.
the templates work. but not for the reason everyone thinks.
they work because they accidentally force you to practice something else entirely.
the skill that actually predicts success with AI isn't about keywords or structure or chain-of-thought formatting.
it's theory of mind. your capacity to model what another agent knows, doesn't know, believes, needs. to anticipate their confusion before it happens. to bridge information gaps you didn't even realize existed.
and here's the part that changes the game completely: they proved it's not a static trait you either have or don't.
it's dynamic. activated. something you turn on and off.
moment-to-moment changes in how much cognitive effort you put into perspective-taking directly changed AI response quality on individual prompts.
meaning when you actually stop and think "what does this AI need to know that i'm taking for granted" on one specific question, you get measurably better answers on that question.
the skill is something you dial up and down. practice. strengthen. like a muscle you didn't know you had.
it gets better the more you treat AI like a collaborator with incomplete information instead of a search engine you're trying to hack with the right magic words.
Chris retweeted
Thrilled to release our new paper MAP: Measuring Agents in Production ⚙️🚀
2025 is the year of agents… but do they actually work in the real world? Is it just hype?
A group of 25 researchers from Berkeley, Stanford, UIUC, IBM, and Intesa Sanpaolo investigated what makes agents deployable in the wild. So…
📈 Why agents? Productivity gains
➕ How to build production agents? Simple & controllable methods
🧑💻 How to evaluate agents? Heavy human oversight
🛑 Top challenge now? Reliability remains unsolved
We surveyed 306 agent builders and ran 20 in-depth interviews across 26 agent application domains to understand the current landscape of production agents.
Check out our latest paper: MAP - more in the thread 👇
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Chris retweeted
This is one of the better takes on the AI "bubble" I've seen recently. ceodinner.substack.com/p/the…