Comment by pron
5 hours ago
They're not productive for any workflow is my point because they don't produce sustainable software, yet that's exactly what Armstrong is calling for. They don't work, and people experienced with AI workflows already know that.
If you review the code and tell the agent to revert when it gets things wrong (not functionally but architecturally) you're fine. That's not what I was responding to.
You're just wrong on this though, and I don't know why you aren't realizing it's a skill issue on your part
Nah, it's a skill issue on the part of those who believe in "agent swarms" (in fact, that's how I recognise AI noobs; they think swarms work). Studies (like this [1]) and Anthropic's experiements have told us they don't. We do experiments with software correctness and formal methods experts who actually dive deep into "swarm outputs" and try to put evolutionary pressure on them. Swarms simply cannot (yet) produce viable software. They do, however, produce software that for a while passes tests. What I think is happening is that people who believe swarms work just look at test results. But obviously, every software engineer has known for decades that tests can only tell you if your software works today; they can't tell you that it will work tomorrow. And the people who say that unreviewed agent output will work tomorrow are those who didn't review it closely enough, so they have no idea, either.
[1]: https://arxiv.org/abs/2603.03823
You're successfully beating the shit out of the strawman you've created. People are using LLMs to see massive productivity benefits and ship production code right now.
If you aren't, it's a skill issue on your part
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