[mmasu]

I remember a very nice quote from an Amazon exec - “there is no compression algorithm for experience”. The LLM might as well do wrong things, and you still won’t know what you don’t know. But then, iterating with LLMs is a different kind of experience; and in the future people will likely do that more than just grinding through the failure of just missing semicolons Simon is describing below. It’s a different paradigm really

[visarga]

Of course there is - if you write good tests, they compress your validation work, and stand in for your experience. Write tests with AI, but validate their quality and coverage yourself.

I think the whole discussion about coding agent reliability is missing the elephant in the room - it is not vibe coding, but vibe testing. That is when you run the code a few times and say LGTM - the best recipe to shoot yourself in the foot no matter if code was hand written or made with AI. Just put the screw on the agent, let it handle a heavy test harness.

[mmasu]

this is a very good point, however the risk of writing bad or non extensive tests is still there if you don’t know what good looks like! The grind will still need to be there, but it will be a different way of gaining experience

[DANmode]

Starting to get it!

New skills, not no skills.

There will still be a wide spectrum of people that actually understand the stack - and don’t - and no matter how much easier or harder the tools get, those people aren’t going anywhere.

[barrkel]

Compression algorithms for experience are of great interest to ML practitioners and they have some practices that seem to work well. Curriculum learning, feedback from verifiable rewards. Solve problems that escalate in difficulty, are near the boundary of your capability, and ideally have a strong positive or negative feedback on actions sooner rather than later.