I don’t agree with the statement about indexing codebase: it works pretty well for IDEs like PHPstorm or other jetbrains IDEs
PHPStorm's indexing is incredible. Aside from a scant few times it's been corrupted, which is easily corrected, I've never gotten stale results. Although if you've ever used Claude's search tool, you'll be unsurprised that the team knows nothing about indexing. How a company, whose primary product is text-based chat, doesn't allow users to easily perform text search on said chat is beyond comprehension.
How Claude Code works in large codebases
121–130 of 191 posts
Re: How Claude Code works in large codebases
#122I use Claude Code quite a bit and quite enjoy it, so I'm a bit confused by how often it's mentioned that you should have CLAUDE.md. I mean: If there was something you could add to the prompt to consistently increase performance why isn't it in the system prompt already? If it's all about clarifying a couple of local idiosyncrasies, shouldn't it be able to quickly get them by looking through the repo? Does anyone have…
Re: How Claude Code works in large codebases
#123I use Claude Code quite a bit and quite enjoy it, so I'm a bit confused by how often it's mentioned that you should have CLAUDE.md. I mean: If there was something you could add to the prompt to consistently increase performance why isn't it in the system prompt already? If it's all about clarifying a couple of local idiosyncrasies, shouldn't it be able to quickly get them by looking through the repo? Does anyone have…
A specific example in another project is the testing/verification procedure. It's a wasm/WebGPU and the test harness is fairly complex. There are scripts to handle it, but by default Claude will churn for a while to figure it out and sometimes just give up. It definitely saves a lot of tokens/speeds things up.
Re: How Claude Code works in large codebases
#124Earlier quoted context omitted.
This is the pain point that existed for years now and its still not solved at all. "If A, do X. Do B,C,D. Do A" - and it just never uses X because "it forgot". You just cant trust that the time you spend building rules will actually pay off, in fact you can trust that it will fail you sooner or later. RAG, Harness, Skills... all was supposed to fix this, but in reality it never had.
Harnesses do fix it IMO - it’s why Claude code and Codex had a massive jump in alleged productivity on release and then seems to have flatlined. But a custom harness _would_ allow you to do things like “on every message, run lint validation and tests”. That in and of itself would be wildly useful.
Re: How Claude Code works in large codebases
#125Earlier quoted context omitted.
The problem with agents is they regularly sidestep the guardrails and do what they want with a script anyway. The number of times I’ve seen Claude try to escape the folder it’s working in, and then for it to write a python script that does exactly what I told it it’s not allowed do supports that. If you use SSO and have an AWS config that Claude is allowed to see to get the correct role in the first place, it will ju…
And this is why it is the height of irresponsibility to run LLMs on your system. We know they are unreliable and just make things up; it's extremely foolish to go "yeah I'm going to let that run commands".
I think the model we've got now is wrong, and the harnesses should be OS-level sandboxed, and the agents should be running in harness managed sandboxes.
Re: How Claude Code works in large codebases
#126> Claude Code navigates a codebase the way a software engineer would: it traverses the file system, reads files, uses grep to find exactly what it needs, and follows references across the codebase. It operates locally on the developer’s machine and doesn’t require a codebase index to be built, maintained, or uploaded to a server.... > Agentic search avoids those failure modes. There's no embedding pipeline or central…
The answer is in the introduction: > Claude Code is running in production across multi-million-line monorepos, decades-old legacy systems, distributed architectures spanning dozens of repositories (…) So it is optimized for the general case, using robust tooling that works everywhere, especially when large & messy. That being said, your remark is right and for well organised smaller repo’s there’s better tooing it ca…
Where "robust tooling" is "grep with various regexes while completely missing the big picture even in small codebases"
Re: How Claude Code works in large codebases
#127What a strange comment for them to make. Why wouldn't I expect CC to work well with those languages? What languages would I associated it with? Python and Javascript?
Re: How Claude Code works in large codebases
#128Earlier quoted context omitted.
you shoouldn't expect a corpo blog to read like an engineering one try this instead: https://anthropic.com/engineering
Perhaps, but I'm commenting on a blog post called "How Claude Code works in large codebases". That's an interesting question to me. I had hoped there was a more interesting answer.
replying to the question introduced with your edit at the root: mcp servers tend to inject too many tokens into the context, that might not be relevant for the task at hand. ex: sentry's mcp is useful if you are collecting context for a bug in production, but is hardly useful later when fixing the bug, at that point you'd probably want treesitter, or if you are working on a new feature you might want to pull details from github issues, or jira tickets.
the consensus seems to land on making the right tools available to the agent, and let it pick which ones to use for the task, this typically means cli tools like git, gh, linters, a cli for your cloud/hosting provider, etc.
that is where skills come in: they bootstrap some context about a task the operator wants to complete. skills use progressive disclosure — each Read() adds more context, but the agent controls what to load-up and what to ignore, and skills can also come with scripts that facilitate actions relevant to the task.
Re: How Claude Code works in large codebases
#129Earlier quoted context omitted.
If your codebase can’t fit on a single developer dev machine it’s too big.
You mean like Teslas multi terabyte repo is not normal?
Re: How Claude Code works in large codebases
#130Earlier quoted context omitted.
Sounds like they're still giving the model the keys to the kingdom, which is my point, stop giving the model the avenue to do catastrophic mistakes, it makes no sense.
If you’re message is in response to me, which I think it is, I deliberately don’t give access to credentials and env variables. I’ve worked to create restrictions and seen AI models use very interesting methods to bypass them. Even now my prompt says the AI must verify the path of the files it intends to edit, and get permission before editing one file at a time and only after permission. I stop it from ignoring thos…