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Jeremy Howard on AI · ViralLoop

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Jeremy Howard@jeremyphoward

For the "small test" they've modified their docs to remove mention of Claude Code in Claude Pro: t.co It's been a shock to see Anthropic's integrity collapse in the face of commercial pressure. Would love a renewed commitment to straightforward honesty.

1.3K likes37 repliesPosted Apr 22, 2026

View the original on X Written by Jeremy Howard. Captured Sep 4, 2026.

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Based on absolute engagement — the platform doesn’t expose follower counts here, so large accounts score higher.

From likes, comments.

Why it worked

Short enough to read in full without expanding, which removes a step before the point lands.
Quotes someone directly, which makes the moment concrete rather than summarised.

The mechanics

Hook: Plain observation
Structure: Hook → Landing
Style: Conversational paragraphs at a steady pace.
Tone: plain, matter-of-fact
Written for: People building with AI

Analysis by ViralLoop — not written by the original author.

Topics

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More from Jeremy Howard

Wow. @Zai_org GLM 5.2 is a marvel! It is *at least* as good as Opus 4.8 and GPT 5.5. It's super fast, inexpensive, and not too verbose. It responds with nuance and judgement, & handles long context VERY well. I've never experienced an open weights model like this before.

How useful is llms.txt? It's so useful that Tailwind rejected a PR to add an llms.txt, on the basis that it would be so useful that people wouldn't need to read their docs any more! t.co

Just read through the Llama 4 release announcement. I'm really grateful they've released this with open weights. But tbh I'm also pretty disappointed. The models are both giant MoEs that can't be run on consumer GPUs, even with quant. t.co A big loss.😢

This graph (from @enricoros, based on @paulgauthier work) show's GPT-4.5's perf on (IMO) the most practical & important eval: Aider Polyglot. If this is accurate, OpenAI is in *deep* trouble! Their crown jewel, the latest GPT, is *500x* more $$$ than DeepSeek v3, yet worse!

# The *actual* LLM scaling law. Adding more compute and data to LLMs makes them: - Linearly more expensive, and - Logarithmically more useful. Therefore: - Scaling becomes less useful the more you do it (once you reach a point where cost is non-trivial).

I'm glad that ChatGPT now has a feature called "Projects" which lets you organise chats, add files, and set custom instructions. But… maybe a little credit might have been nice for Claude "Projects", which lets you organise chats, add files, and set custom instructions?