Comment by gbnwl
11 hours ago
Cheaper? Loading every bit of documentation into context every time, regardless of whether it’s relevant to the task the agent is working on? How? I’d much rather call out the location of relevant docs in Claude.md or Agents.md and tell the agent to read them only when needed.
As they point out in the article, that approach is fragile.
Cheaper because it has the right context from the start instead of faffing about trying to find it, which uses tokens and ironically bloats context.
It doesn't have to be every bit of documentation, but putting the most salient bits in context makes LLMs perform much more efficiently and accurately in my experience. You can also use the trick of asking an LLM to extract the most useful parts from the documentation into a file, which you then re-use across projects.
https://github.com/chr15m/ai-context
> Extracting the most useful parts of documentation into a file
Yes, and this file becomes: also documentation. I didn’t mean throw entire unabridged docs at it, I should’ve been more clear. All of my docs for agents are written by agents themselves. Either way once the project becomes sufficiently complex it’s just not going to be feasible to add a useful level of detail of every part of it into context by default, the context window will remain fixed as your project grows. You will have to deal with this limit eventually.
I DO include a broad overview of the project in Agents or Claude.md by default, but have supplemental docs I point the agent to when they’re working on a particular aspect of the project.
> sufficiently complex
Sounds like we are working on different types of projects. I avoid complexity at almost all cost and ruthlessly minimise LoC and infrastructure. I realise that's a privilege, and many programmers can't.