Comment by nbardy

> but for LLM's they can instantly compose the low level tools for their use case and learn to generalize

Hard disagree; this wastes enormous amounts of tokens, and massively pollutes the context window. In addition to being a waste of resources (compute, money, time), this also significantly decreases their output quality. Manually combining painfully rudimentary tools to achieve simple, obvious things -- over and over and over -- is *not* an effective use of a human mind or an expensive LLM.

Just like humans, LLMs benefit from automating the things they need to do repeatedly so that they can reserve their computational capacity for much more interesting problems.

I've written[1] custom MCP servers to provide narrowly focused API search and code indexing, build system wrappers that filter all spurious noise and present only the material warnings and errors, "edit file" hooks that speculatively trigger builds before the LLM even has to ask for it, and a litany of other similar tools.

Due to LLM's annoying tendency to fall back on inefficient shell scripting, I also had to write a full bash syntax parser and shell script rewriting ruleset engine to allow me to silently and trivially rewrite their shell invocations to more optimal forms that use the other tools I've written, so that they don't have to do expensive, wasteful things like pipe build output through `head`/`tail`/`grep`/etc, which results in them invariably missing important information, and either wandering off into the weeds, or -- if they notice -- consuming a huge number of turns (and time) re-running the commands to get what they need.

Instead, they call build systems directly with arbitrary options, | filters, etc, and magically the command gets rewritten to something that will produce the ideal output they actually need, without eating more context and unnecessary turns.

LLMs benefit from an IDE just like humans do -- even if an "IDE" for them looks very different. The difference is night and day. They produce vastly better code, faster.

[1] And by "I've written", I mean I had an LLM do it.

Note that the Claude code LSP integration was actually broken for a while after it was released, so make sure you have a very recent version if you want to try it out.

However as parent comment said, it seems to always grep instead, unless explicitly said to use the LSP tool.

Correct. If you try to create a coding agent using the raw Codex or Claude code API and you build your own “write tool”, and don’t give the model their “native patch tool”, 70%+ of the time it’s write/ patch fails because it tries to do the operation using the write/ patch tool it was trained on.

We are back to RISC vs CISC!