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Why Software Factories Fail (or: harness engineering is not enough)

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Why This Matters

This article highlights the risks and challenges of rapidly adopting AI-driven software factories, emphasizing that over-reliance on automation can lead to increased bugs, outages, and declining code quality. For the tech industry and consumers, it underscores the importance of balanced engineering practices and cautious integration of AI tools to maintain reliability and safety in software development.

Key Takeaways

Why Software Factories Fail

or: harness engineering is not enough

Note I run a company (HumanLayer) building tools in the human/agent collaboration space, so what I'm gonna say below may be a tad biased. Perhaps in spite of that, I hope you find the subject helpful or at the very least that you find it as interesting as I do. -Dex

i guess we doin loops now

We're all racing to put AI coding into production. A lot has been said about loop engineering, and the prevailing wisdom is that we should probably write more loops.1

StrongDM wrote about their lights-off software factory where no human reads code and no human writes code.

The narrative goes something like this:

You are the bottleneck. The models are good enough. Code is free. Just ship more stuff.

Ryan Lopopolo of OpenAI wrote about this in February and gave a talk in April about OpenAI's software factory, Symphony.

These people are all really dang smart and I have a ton of respect for them. But the most cynical take here would be to call this yet another excuse to pump more VC money into the slop cannon.

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