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Social Pulse · AI · 2026-10-06 00:05 UTC

@thdxr: Karpathy's funnel of LLM experience, and the tinkerer inversion

a weird inversion with LLMs is the models improve faster than the tinkerers when i see people with custom workflows and setups they're all addressing problems that don't exist anymore the person na…

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dax ✓ @thdxr

a weird inversion with LLMs is the models improve faster than the tinkerers when i see people with custom workflows and setups they're all addressing problems that don't exist anymore the person naively using vanilla codex is more likely to be experiencing state of the art

♥ 13.4K↺ 657💬 663👁 1.0M on X ↗

Part of the conversation: Karpathy's funnel of LLM experience, and the tinkerer inversion

@karpathy says the gap in shared understanding of LLM capability is widening into a sharp funnel: around 6B people have barely touched LLMs, 1-2B are casual free-tier users, around 20M use frontier models for math and code, and about 5,000 have internal access. He cites ambition, jaggedness and access as drivers. @thdxr says models improve faster than tinkerers, so someone using vanilla codex may be experiencing state of the art.

Why it mattersThe most-engaged post of the day, with 41.4K likes and 5.9M views, frames how differently people experience AI.

Other posts in this conversation

Andrej Karpathy ✓ @karpathy

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.

♥ 41.4K↺ 5.5K💬 1.9K👁 5.9M analysis →on X ↗

How it compares

Likes vs the rest of the feed14 top AI posts on 2026-10-13
likes: This post 13,414, AI median 7,039, AI top post 41,416This post13,414AI median7,039AI top post41,416

This post ranks #3 of the 14 highest-engagement ai posts AgentFlare tracked on 2026-10-13, with 1.9× the median likes. See the full AI briefing.

How this page is made. Post text and engagement come from the AISA Twitter API (advanced search, top results). Conversation summaries are written from the post texts only; a post is the author’s claim, not a verified fact.

Sources & citations

  1. @thdxr on X 2026-10-06 00:05 UTC
  2. AISA Twitter API