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Comment by parasti | Hacker News Reader

This post is full of things opposite of what I've found. An agent (claude code at least) will certainly refactor feature flags better than I ever could and is less likely to miss special cases. What the agent struggles with is business knowledge - context I hold in my head as a human communicating with other humans and working on a codebase over a long period of time.

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One of the main problems I face is that business knowledge is not explicitly written down and formulated. No matter how much you describe something in human text format those are not formal rules about how something should work. If you can't inspect the output of the LLM you do not have full understanding of the business.

Most "classic" computer systems (code that runs on a CPU) are not strictly formal[1], but they are orders of magnitude more formal than human language.

[1] things like distributed systems, memory corruption, performance characteristics, etc can make a system behavior not predictable

That's true. But we always desired that more business knowledge be shared in written form between humans (people come and go, work across time zones, ...).

Presumably agents can both help maintaining/mediating such communication and also benefit from the context they acquire through that

> Presumably agents can both help maintaining/mediating such communication

What happens in practice, is that people use agents to write such communication down, don't review it, and then the wrong information persists, and future agents will regurgitate it, until it reaches a human who already know it's wrong who then goes "Huh, where did this come from?".

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