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Things we learned about LLMs in 2024

simonwillison.net

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Re: Things we learned about LLMs in 2024

#231
post #198

> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…

One of the things I find most frustrating about LLMs is how resistant they are to teaching other people how to use them!

I'd love to figure this out. I've written more about them than most people at this point, and my goal has always been to help people learn what they can and cannot do - but distilling that down to a concise set of lessons continues to defeat me.

The only way to really get to grips with them is to use them, a lot. You need to try things that fail, and other things that work, and build up an intuition about their strengths and weaknesses.

The problem with intuition is it's really hard to download that into someone else's head.

I share a ton of chat conversations to show how I use them - https://simonwillison.net/tags/tools/ and https://simonwillison.net/tags/ai-assisted-programming/ have a bunch of links to my exported Claude transcripts.

Re: Things we learned about LLMs in 2024

#232
post #54

About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…

I'm a big believer in Claude. I've accomplished some huge productivity gains by leveraging it. That said, I can see places where the models are strong and weak. If you're doing react, or python. These models are incredible. C#, C++ they're not terrible. Rust though, it's not great. If your experience is exclusively trying to use it to write Rust, it doesn't matter if you're using o1, Claude or anything else. It's just not great at it yet.

Re: Things we learned about LLMs in 2024

#233
post #202
post #54

About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…

> Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. It's not as helpful as Google was ten years ago. It's more helpful than Google today, because Google search has slowly been corrupted by garbage SEO and other LLM spam, including their own suggestions.

Claude Sonnet 3.5 can write whole React applications with proper contextual clues and some minor iterations. Google has never coded for you.

I’ve written two large applications and about a dozen smaller ones using Claude as an assistant.

I’m a terrible front-end developer and almost none of that work was possible without Claude. The API and AWS deployment were sped up tremendously.

I’ve created unit tests and I’ve read through the resulting code and it’s very clean. One of my core pre-prompt requirements has always been to follow domain-driven design principles, something a novice would never understand.

I also start with design principles and a checklist that Claude is excellent at providing.

My only complaint is you only have a 3-4 hour window before you’re cutoff for a few hours.

And needing an enterprise agreement to have a walled garden for proprietary purposes.

I was not a fan in Q1. Q2 improved. Q3 was a massive leap forward.

Re: Things we learned about LLMs in 2024

#234
Great summary of highlights. Don't agree with all, but I think it's a very sound attempt at a year in review summary

>LLM prices crashed

This one has me a little spooked. The white knight on this front (DS) has both announced increases and has had staff poached. There is still Gemini free tier which is ofc basically impossible to beat (solid & functionally unlimited/free) but it's google so reluctant to trust.

Seriously worried about seeing a regression on pricing in first half of 2025. Especially with the OAI $200 price anchoring.

>“Agents” still haven’t really happened yet

Think that's largely because it's a poorly defined concept and true "agent" implies some sort of pseudo-agi autonomy. This is a definition/expectation issue rather than technical in my mind

>LLMs somehow got even harder to use

I don't think that's 100%. An explosion of options is not equal to harder to use. And the guidance for noobs is still pretty much same as always (llama.cp or one of the common frontends like text-generation-webui). It's become harder to tell what is good, but not to get going.

----

One key theme I think is missing is just how hard it has become to tell what is "good" for the average user. There is so much benchmark shenanigans going on that it's just impossible to tell. I'm literally at the "I'm just going to build my own testing framework" stage. Not because I can do better technically (I can't)...but because I can gear it towards things I care about and I can be confident my DIY sample hasn't been gamed.

Re: Things we learned about LLMs in 2024

#235
post #54

About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…

I'm surprised at the description that it's "useless" as a programming / design partner. Even if it doesn't make "elegant" code (whatever that means), it's the difference between an app existing at all, or not.

I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs.

I wouldn't describe myself as a programmer, and didn't plan to ever build an app, mostly because in the attempts I made, I'd get stuck and couldn't google my way out.

LLMs are the great un-stickers. For that reason per se, they are incredibly useful.

Re: Things we learned about LLMs in 2024

#236
post #198

> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…

[flagged]

I hadn't heard of T2Tile. The intro video https://www.youtube.com/watch?v=jreRFxN6wuM is from 5 years ago so it predates even GPT-3.

Do you know if any of the ideas from that project have crossed over into LLM world yet?

Re: Things we learned about LLMs in 2024

#237
post #198

> There’s a flipside to this too: a lot of better informed people have sworn off LLMs entirely because they can’t see how anyone could benefit from a tool with so many flaws. The key skill in getting the most out of LLMs is learning to work with tech that is both inherently unreliable and incredibly powerful at the same time. This is a decidedly non-obvious skill to acquire! I wish the author qualified this more. How…

[flagged]

Do you know who Simon is?

Re: Things we learned about LLMs in 2024

#238
post #10

> Some of those GPT-4 models run on my laptop That's an indication that most business-sized models won't need some giant data center. This is going to be a cheap technology most of the time. OpenAI is thus way overvalued.

The best models are always out of reach on desktops. You can have ok models but AGI will come in a datacenter first

Re: Things we learned about LLMs in 2024

#239
post #202
post #54

About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with L…

> Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. It's not as helpful as Google was ten years ago. It's more helpful than Google today, because Google search has slowly been corrupted by garbage SEO and other LLM spam, including their own suggestions.

comparing google to claude 3.5 is like comparing tesla s plaid with a horse
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