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Anthropic just reliesed the best 1-hour workshop on Loop engineering: from one prompt to a Loop that improves itself 5:31 - loop memory 11:02 - check, build, commit 13:06 - one feature per loop 33:03 - MVP in 1 hour Free, the best thing on Loop engineering I've come... show more
15 条评论

Honestly this sounds like the kind of workshop where you watch it at 2x speed and still feel like you need a nap. But the "one feature per loop" thing is genuinely smart — most people try to boil the ocean in a single prompt.

Good find.

nice share!

@Mahaximus_ that 33:03 section on MVP in 1 hour is gold. been there trying to cram everything in way too soon. simpler loops make a massive difference.

Loop memory at 5:31 is the part most people skip. What actually gets written back into the next loop — the full trace, a summary, or only the failed checks?

MVP in 1 hour is insane honestly

What if the agent will never come out of loop and never took its stopping condition.

The self-improving agent part is the interesting bit. In practice it works until it silently drifts from what you meant, so the check/commit discipline matters more than the prompt itself.

The useful part is the loop’s feedback discipline, not the fact that it runs forever. If the system can’t define success, capture failures, and change one thing at a time, a 24/7 loop just scales noise. Check, build, commit is the part operators should steal.

the one-feature-per-loop constraint is a great way to keep agent experiments from sprawling.

The check/build/commit part is the whole thing. A loop that can revert its own mistakes is easy to trust. Once it starts paying for things there's no revert, and scoping isn't optional

Bookmarked this immediately, the timestamps alone make it worth saving

Loop engineering is the piece most agent demos skip. I treat each loop as observe, act, verify, then write the failure into the next prompt. Which step in that workshop mapped cleanest onto your real stack?

我一直对Loop engineering挺感兴趣,刚好这个工作坊内容实用还免费,我这就去看视频跟着操作练手。

Nice guide
