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Notes -
I will point out that MoltBook had exposed it's entire production database for both reads and writes to anyone who had an API key (paywalled link, hn discussion).
And this is fairly representative of my experience with AI code on substantial new projects as well. In the process of building something, whether it's something new or something legacy, the builder will need to make thousands of tiny decisions. For a human builder, the quality of those decisions will generally be quite tightly correlated to how difficult it is for a different human to make a good decision there, and so, for the most part, if you see signs of high-thoughtfulness polish in a few different part of a human-built application that usually means that the human builder put at least some thought into all the parts of that application. Not so for "AI agents" though. One part might have a genuinely novel data structure which is a perfect fit for the needs of the project and then another part might ship all your API keys to the client or build a SQL query through string concatenation or drop and recreate tables any time a schema migration needs to happen.
That's not to say the "AI coding agent" tools are useless. I use them every day, and mostly on a janky legacy codebase at that. They're excellent for most tasks where success is difficult or time-consuming to achieve but easy to evaluate - and that's quite a lot of tasks. e.g.
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