Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
An article for everyone who ships, buys, or signs off on software built on large language models (LLMs): engineers, product managers, and the CEO. Written in plain language, from the big picture down to the details. https://t.co/YaP414vR0u
@omarsar0 My mental model for what is happening is that 99%+ of people who are now paying attention have been onboarded to anything related to AI in <1 year. This is very confusing to the AI dinosaurs (anyone in AI for pre 2026. Or even, gasp, pre 2012).
There are two kinds of people in this world:
1) The ones who build things
2) The ones who wait to take what the builders built
Money is attracted to the first group and repelled by the second.
Worth asking yourself which one you are.
Holy shit I was going through my old books and found the book I used to brush up on Typescript from 2019, and all my highlights in it
It’s was by some random dev I never heard of back then, but remember it was a v good book
This “random dev” is @bcherny 🙃
This can sometimes be a hard thing to realize in the moment. Through future reflection, these “losses” can be seen as significant forces in your success. Choose wisely…
In a world where tools that can write faster than ever before… this is critical advice. Just because it can be done fast, doesn’t always mean it should be.
Just ask Meta and Andon Labs 😜
I’m always reminded of my mother’s words that taking time to shake the janitor’s hand is just as important as holding the door for the CEO. It can harden your soul paying attention to those that don’t, but warms the soul when this practice helps someone in a real way.
Your value as a leader is determined by how you handle lose-lose situations.
Where you know you will be criticized no matter which path you choose.
Choose lesser evil.
Take blame.
Give credit.
Repeat.
That’s the job.