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Comment by xnorswap | Hacker News Reader

> steer Claude away from over-engineering parts of the system in response to hypothetical concerns.

This is my biggest problem with opus 5.5.

It's absolutely incredible in many ways, but it has no sense of "good enough".

It will go around in circles polishing something so to resolve edge-cases on edge-cases.

"Someone could create a class that calls your public method in such a way, that under 3 other race-condition properties, there might be stale data read".

It has no sense that it isn't appropriate to add a half dozen classes just to close that kind of hole, especially when there isn't even such a caller or possible conditions at present.

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My problem isn't that it can identify such conditions, the record on cybersecurity lately shows these things are quite good at finding real faults. But the annoyance is that they always want to fix it by adding more things that open cracks. It's possible, sort of, to drive it to fix by removing things instead but it's a battle.

I'm not claiming that anyone is doing this on purpose, but overly engineered codebases are a good thing for a company like Anthropic. If your code is so bloated that it is pretty much unreadable without an LLM they win on both sides.

The cliche “AI solves that” response to everything is even more annoying when it’s a problem that AI created.

and did you notice the explanations when you review the code with it.. its english, but somehow I don't undestand anything..

silly as it sounds but its often much faster for me to skim the code and understand it then to read it's summary of the code

Some of this stems from the idea that everything can be reduced to logic, so as long as we solve for all logical states, the end result will be perfect.

Of course, the second you start interacting with the real world and with humans, that doesn't really apply anymore and you have to get to 'good enough' much earlier than a generator would be able to predict.

Even if you steer a model to a very specific goal with an easy to validate end state, it will do things that within the scope and context of the goal a human would not really do. In theory if you put the context of the entirety of a human into a model, you might be able to get much closer, but we don't even have enough power generation on the planet to process that (unless someone has a secret ten orders of magnitude more efficient way of doing that).

This also sounds a bit like an underspecified interface. If the class spec clearly states under which conditions it is thread safe then the agent can take that into account, but if it doesn't then the agent has to assume that it should guarantee thread safety in all contexts.

Yeah, a pressure relief clause and it should fire visibly.

I didn't mean another clause in CLAUDE.MD, but that one has to actually specify what they want instead of expecting the LLM to read minds

Yeah, I had this issue with Claude since the v5, it’s a real pain to get the model to not create its own goals and spend all its time on it. Switching to Deepseek 4.1 flash is so refreshing, it does what I ask for, mostly, even if things take more time and guidance. At least I don't feel I’m wasting all that processing on stuff I do not care about

One thing to keep in mind though is that "someone calls your public method" more often could be an agent, and that agent will try to explore the edge cases.

> It's absolutely incredible in many ways, but it has no sense of "good enough".

100%

And I have a nasty idea that it is by design. "Use me, use me more!"

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