Earlier quoted context omitted.
It seems possible for openAI/Anthropic to rework their tools so they discard/add relevant context on the fly, but it might have some unintended behaviors. The main thing is people have already integrated AI into their workflows so the "right" way for the LLM to work is the way people expect it to. For now I expect to start multiple fresh contexts while solving a single problem until I can setup a context that gets th…
A number of agentic coding tools do this. Upon an initial request for a larger set of actions, it will write a markdown file with its "thoughts" on its plan to do something, and keep notes as it goes. They'll then automatically compact their contexts and re-read their notes to keep "focused" while still having a bit of insight on what it did previously and what the original ask was.
Context is the bottleneck for coding agents now
191–193 of 193 posts
Re: Context is the bottleneck for coding agents now
#192Earlier quoted context omitted.
I've had every single LLM I tried (Opus, Sonnet, GPT-5-(codex) and Grok light) all tell me that Go embeds[0] support relative paths UPWARDS in the tree. They all have a very specific misunderstanding. Go embeds _do_ support relative paths like: //go:embed files/hello.txt But they DO NOT support any paths with ".." in it //go:embed ../files/hello.txt is not correct. All confidently claimed that .. is correct and will…
I don’t really find that so surprising or particularly stupid. I was hoping to learn about serious issues with bad logic or reasoning not missing dots on i’s type stuff. I can’t remember the example but there was another frequent hallucination that people were submitting bug reports that it wasn’t working, so the project looked at it and realized well actually that kinda would make sense and maybe our tool should wor…
And if an LLM guesses (hallucinates) a specific method for your API, it really should have it - statistically speaking =)
Re: Context is the bottleneck for coding agents now
#193Earlier quoted context omitted.
youre projecting a deficiency of the human brain onto computers. computers have advantages that our brains dont (perfect and large memory), theres no reason to think that we should try to recreate how humans do things. why would you bother with all these summaries if you can just read and remember the code perfectly.
Because the context window of the LLM is limited similar to humans. That’s the entire point of the article. If the LLM has similar limitations to humans than we give it similar work arounds. Sure you can say that LLMs have unlimited context, but then what are you doing in this thread? The title on this page is saying that context is a bottleneck.