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Towards Self-Driving Codebases

123 points · 100 comments · wilhelmklopp

  1. CharlieDigital · · focus · HN ↗

        > It’s actually fine if agents make a lot of boneheaded mistakes. What’s not ok is if they keep making the same mistakes. 
    
    I worked in life sciences for a bit. There is a process in clinical trials called corrective and preventative actions (CAPA). You'll also find this in other areas where failure tolerance is low (e.g. aircraft).

    It's simple: when a mistake happens, you run your CAPA process (Google CAPA form and see examples to extrapolate what that process might look like) and determine the root cause and the correction to the process that allowed the mistake to happen in the first place.

    (At least as a SaaS vendor in life sciences, when we had a CAPA (e.g. after a SEV0 failure), it would be folded into our SOPs and then we would be required to retrain on the SOP. Auditors would want to see our evidence of CAPAs, the versions of our SOPs, the records of training. All to extreme for most shops, but I add this for context/color)

    This is something most eng shops do not have the discipline for since it requires some diligence.

    Should it be fully agentic? Should there be human intervention here to approve the CAPA? Open questions to be answered.

    1. grey-area · · focus · HN ↗
      The more important question - how would you actually get LLM agents to follow the instructions in your ever-growing CAPA reliably?

      It’s all very well having a list of actions to avoid but that doesn’t help if your agents won’t reliably follow it.

      1. Ferret7446 · · focus · HN ↗
        The same way you do for humans, regular training and audits.
        1. grey-area · · focus · HN ↗
          They don’t behave like humans.
          1. Ferret7446 · · focus · HN ↗
            On the contrary, they behave exactly like moderately autistic humans
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