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ramity | 9 months ago
Yes, open source projects would be the main place where these claims could be publicly verifiable, but established open source projects aren't just code--they're usually complex, organic, and ever shifting organizations of people. I'd argue the metric of interacting with a large group of people whom have cultivated their own working process and internal communication patterns is closer to AGI than coding assistant, so maybe the goal posts we're using for AI PRs are too grand. I think it's expected to hear claims from within walled gardens, where processes and teams can be upended at will, that AI is making an unverifiable splash, because they're precisely the environments where AI could be the most disruptive.
Additionally, I think we're willfully looking in the wrong places when trying to measure AI impact by looking for AI PRs. Programmers don't flag PRs when they use IntelliJ or confer with X flavor of LLM(tm), and expecting mature open source projects to have AI PRs seems as dubious as expecting then to use blockchain or any other technology that could be construed as disruptive. It just may not be compatible or reasonable with their current process. Calculated change is often incremental and boring, where real progress is only felt by looking away.
I made a really simple project that automatically forwards browser console logs to a central server, programmatically pull the file(s) from the trace, and had an LLM consume a templated prompt + error + file. It'd make a PR with what it thought was the correct fix. Sometimes it was helpful. The problem was it needed to do more than code, because the utility of a one shot prompt to PR is low.
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