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It's interesting that you mention C# and null checks.
I also work C# here and there, as well as a language that is a relatively verbose, garbage collected, class based, statically typed, single dispatch, object oriented language with single implementation inheritance and multiple interface inheritance. Like you, I'm seeing unimpressive results that do not justify the spend necessary for agentic coding.
Every time I've mentioned it here, I'm told the following:
Nobody seems to want to offer the sane take, which seems to be that there can be real efficiency gains for small, well-specified projects, provided you are already an expert in the domain and are willing spend a considerable amount of time beating it into submission whenever it so much as coughs.
If you're working on a small (or perhaps exquisitely modularized) codebase, and it's chock full of documentation written in a way that the LLM can comfortably consume it without getting confused, and it's using only the happy path architecture and library set for your language, and it's in one of the "favored" languages (like python), and you have a robust set of preexisting end to end tests that can help keep the LLM on the rails, then this technology is probably pretty great.
Outside of FAANG and a few startups, however, I'm not sure how often that's the case. Legacy code is real. Enterprise customers can have upgrade cycles that are measured in years. Backwards compatibility is worth more than features. Regulatory compliance issues might end up a court summons instead of a JIRA ticket. That's not a world that does well with disposable code. Unless startups can outcompete every established player in every industry with those characteristics, I'm not sure how that changes. I can't rule out that such a future might happen, but given the moats around those industries, it'll be a tough row to hoe.
In our internal pilots, AI-generated PRs from frontier models make it through our test suite on the first try about 15% of the time. Another 30% never pass at all because they spiral out into schizophrenic fantasy lands, trying to call libraries that don't exist or attempting to rewrite a two million line codebase in "modern python". Of the ones that do make it through, about three quarters of them end up failing code review, even as we update and refine our agent instructions. At this point, dependabot has a better track record, and it doesn't even have Dario Amodei crying at night about how terrifyingly capable it is.
It pisses me off. The technology clearly has some uses, but fuck me if it doesn't feel like it's been wildly oversold. We still use it internally, but the mania is starting to die down. Management thinks it's the best thing ever because it can automatically spam LinkedIn for them. Development uses it as a more accessible StackOverflow. But we've given up on agentic coding for the time being. We'll probably look at it again in six months, assuming nothing bizarre happens between now and then.
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