AI agents go brrr. ex-Meta, Zoominfo, WeWork, CTO x 4 https://nitter.gq/t.co/O2lLoSCS3p https://nitter.gq/t.co/IGKIT537sc
Israel
Joined April 2007
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Been doing it for 2+ years now, usually with both Anthropic and OpenAI frontier models challenging each other’s plans
Hear me out:
We hated "waterfall" because after Big Upfront Planning, implementation took FOREVER, and by the time we were done, the plan was out of date
But with AI, implementation is rapid (100x faster, or more, than before)
So Big Upfront Planning can now make sense?
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Dima Kuchin retweeted
The next decade won't reward tourists. It will reward people who combine audacity with discipline. Who understand that technology cycles come and go, but that building enduring companies requires clarity of purpose and consistency of execution.
Venture has always been about backing outliers. That hasn't changed. If anything, it matters more now.
Looks awfully familiar to what I do building successful AI-powered platforms in multiple verticals, reaching near-expert levels while not being an expert myself.
There’s a method taught at Y Combinator that turns 4 weeks of GTM research into 3 hrs.
And no, it’s not typing “research the market for X” into Claude.
You start by feeding it raw material:
→ 25-40 competitor websites, fully scraped (pricing pages, case studies, docs)
→ The last few earnings calls from the 3-5 biggest incumbents
→ 100+ customer reviews (G2, Capterra, Trustpilot, app stores)
→ Every Reddit or forum thread where people vent about the category
Then ask questions that force it to think, not summarize:
1. “What do the winners in this market know that their customers would never admit?”
2. “List the beliefs this whole industry takes for granted. For each one, what would need to happen for it to be false?”
In about 20 min, you’ll see where everyone agrees, where everyone is blind, and which customer pains nobody is building for.
Now flip it. Pick your best angle and tell Claude to tear it apart:
“Steelman this thesis like a top-tier VC would. Then show me exactly where it fails.”
Do a few rounds of that. 3 hours later, you’ll have a first GTM hypothesis that sounds like it came from a 10-year industry veteran.
The trick is treating Claude as a sparring partner that never gets tired and never gets defensive when it’s wrong.
But remember: it’s still just a hypothesis. The real work starts when you talk to actual buyers.
To get there fast, use Gojiberry to find and reach the right people to test it with.
Customer conversations are the only thing that matters.
Most companies don’t know how to build right AI harness engineering for their processes. It is totally possible to make AI solutions to outperform humans on complex tasks, yet it requires a lot more than prompt engineering and evals.
I think there is way too much concern expressed about verification of AI output in everyday work due to a risk of factual errors.
It used to be true, but data on more recent models suggest they beat human experts, including PhD specialists, in finding facts and checking claims.
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Dima Kuchin retweeted
The gap between an average engineer and the best engineers was never quite 10x, but it was meaningful.
AI has made the gap at least 100x.
Dima Kuchin retweeted
The only model that actually scored higher on DeepSWE when small changes were made to the task, was Opus 5.5
Most models are severely benchmaxxed.
Nice DeepSWE score! Does it survive a lowercase filename?
Introducing MaxxBench: 89 DeepSWE tasks with small changes to the instructions or starting code. Same engineering problem, slightly different requirement.
Models clustered around 74% on DeepSWE end up 23 pp apart.
Good at coding, or good at DeepSWE? 🧵
Dima Kuchin retweeted
human-in-the-loop
└ human-on-the-loop
└ human-near-the-loop
└ human-cc'd-on-the-loop
└ human-legally-liable-for-the-loop
Dima Kuchin retweeted
I met a founder today who was dreading putting slides together, probably more so than the slides, the VC conversations...
While I can't help with the VC conversations, I did help with putting together a 5 slide template to get going.
He found it super useful and then met another founder who asked me for the slide templates too. I feel like this should be "open sourced", so I'm sharing them here.
Disclaimer: yes some VCs say they don't need slides, but then they expect warm intro. The purpose of the slides is to get you the intro meeting and for them to want to learn more.
Common error: engineers like depth and detail; you don't have to cover all in your deck, I guarantee no one will look through 50 slides.
I hope this helps
current benchmarks favor “execution” agents (practical) and don’t really know how to test a depth of thought. which is why Opus trumps Fable. same story about Argon. it is clearly a big model, you can smell it.
I feel like Gemini 4 Argon is a repeat of Gemini 3 Pro
it scores extremely well on most benchmarks, but in the ones that measure reliability, hallucinations and vibes it sucks
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Dima Kuchin retweeted
💯
I highly recommend this 1999 paper from Microsoft Research where they were trying to build a model to predict if an "agent" needs to wait or intervene and make action. something like that is just one jev call today. sadly they didn't get to release it
"Principles of Mixed-Initiative User Interfaces" by Eric Horvitz
Dima Kuchin retweeted
i find it hilarious how people are making excuses for this and saying that this is all just clickbait or fearmongering
you only need to realize one thing about AI:
- if models score above 0% on any task today, then they will score close to perfect in the near future
I wholeheartedly agree, yet for most people it’s not the case. Skill issue 🤷🏻♂️
it’s clear we need to retire the term vibe coding because the models now produce better architecture & way more coherent code than an average software engineer.
perhaps even better than top software engineers too because unlike a human, ai has a much much larger context window.
this ain’t vibe coding at all. it’s precision engineering.
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Dima Kuchin retweeted
The purpose of AI is to help humanity ascend to the stars, but we shall *never* ascend if we insist on limiting AI to the upper bound of human understanding.
It is dangerous, and it is also exhilarating. It is a matter of faith. Leap forward. Accept the mystery.
"There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy."