Comment by lmeyerov

1 month ago

That's the failure to automate. The AI isn't telepathic, so agentic engineers not automating this stuff is skipping out on the engineering part.

You setup the environment and then you do the work. Unless you are switching employers every week, you invest in writing that stuff down so the generation is right-ish and generate validation tooling so it auto-detects the mistakes and self-repairs.

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lmeyerov

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mittensc  1 month ago

sometimes you write the feature and write it well so it's reusable.

imagine you have to implement a specific algorithm for a quantum computer.

There's no value setting up AI to do the writing for you. That might be orders of magnitude harder then writing the algorithm directly.

For highly specialized one-off features, it doesn't always pay off.

On the other hand, if all you do are some generic items that AI can do well... then I'm not sure you're going to have a job long term, your prompts and automation will be useful for the new junior hires that will be specialized in using these and cost effective.

  • lmeyerov  1 month ago

    That feels like true in theory, but in practice, we see the reverse for advanced projects where AI is helping us a lot. A decent chunk of our core IP falls into the bucket you're describing:

    We have been building a GPU-accelerated graph investigation platform that has grown over 10+ years with fancy stuff all over the place - think accelerated query languages, layout kernels, distribution, etc. R&D-grade high performance engineering projects and kernels end up needing a lot of iterations to make a prototype and initial release. Likewise, they're more devilish to maintain when they need a small tweak later because of the sophistication and bus factor. Both phases benefit.

    AI coding helps automate investigation, testing, measurement, patching, etc. The immediate effect is we can squeeze in many more experimental iterations with more fidelity and reach. Having an AI help automatically explore the design space and the details helps a LOT. And later, maintaining a wide surface area of code here that is delicate to touch and infrequently edited is traditionally stressful for teammates, and AI editing + AI-generated automation is helping destress that a LOT. We very much invest in upgrading our team, processes, and tooling here.