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Joined 6 months ago
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Cake day: April 13th, 2026

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  • Agents is just the LLM prompting itself with subtasks. This can be helpful to compartmentalize larger and more complex tasks. I find the tool calls most important. An agent that can compile and test its own code will make fewer mistakes (assuming the tests weren’t also written by LLMs but even then).

    So there’s a self-correcting feedback loop that will improve quality, but is also a lot more expensive. The problem is that the temptation is huge to give more and more complex tasks to the agents and then they go off for 30min or longer and may or may not create complete and utter bullshit because something led them astray or they forgot something one agent did wrong and never fixed it. The end result may work, but it may be less efficient or come with a share of dead code that’s never called etc.

    You end up with hundreds of lines to verify. You could just ask an agent to do it, but at some point adding more agents to the pile is not going to help… and probably takes longer than just reading it yourself.











  • I read a retrospective from another team yesterday. They were preparing a demo for leadership and apparently it didn’t go so well. There were many reasons like last minute changes in requirements but one line was interesting for this discussion: The use of the LLM agents caused confusion about who is fixing which bug and taking on which tasks. The agents act like they’re alone in the codebase and keep adding and changing code broadly whenever they see an opportunity for improvement. And that often without specifically being prompted to do so. Now if you have multiple team members collaborating on a project with each their agents, chaos ensues because the agents are not coordinating and the diffs/commits become insane and the team doesn’t fully understand them.

    This actually results in a necessity to test more and longer because nobody knows which bugs have really been fixed now and rapidly preparing for a release or a demo becomes more difficult than before.

    In my opinion an LLM can be very useful to rapidly prototype something. Especially with an API or language you’re not familiar with. But for Production it’s still a huge risk to push code you don’t understand.