Comment on [JS Required] How Performant are LLM Agents(AI Chatbots) on Real World Work Tasks? They Fail 70% or More of The Time.

wise_pancake@lemmy.ca ⁨19⁩ ⁨hours⁩ ago

• criss_cross@lemmy.world ⁨12⁩ ⁨hours⁩ ago

  They’re great for bootstrapping in my experience but then really fall apart when you need it to do something surgical on a larger codebase.

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  • wise_pancake@lemmy.ca ⁨8⁩ ⁨hours⁩ ago

    Mine too

    I’ve been working on an app and it was fantastic for the basics, then I decided to refactor an API and Claude code would run for hours without really getting there.

    Also a good warning: I just had to completely rewrite an mcp server I had Claude build because when I needed to update it, the whole server was one giant if/else statement and utterly unmaintainable.

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    • criss_cross@lemmy.world ⁨7⁩ ⁨hours⁩ ago

      Yeah I was trying to pull out a nested react component and styles out of a larger component that got to be almost 1500 lines. Claude and GPT both struggled to get down what styles were required and what that subcomponent was actually doing. And generating tests around just made a fuck ton of spaghetti.

      Which is fine. LLMs don’t have to be great at everything. But it’d be nice if people stopped saying I’m gonna be out of a job because of em.

      Also a good warning: I just had to completely rewrite an mcp server I had Claude build because when I needed to update it, the whole server was one giant if/else statement and utterly unmaintainable.

      I’ve noticed that in some of my bootstrapped code (also an MCP server :) ). I think it tends to bias towards single file solutions so it tends to be a lot less maintainable.

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