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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...

94,658 次观看 • 3 天前 •via X (Twitter)

15 条评论

Kamal Bisht 🔴 AI Marketer 的头像
Kamal Bisht 🔴 AI Marketer3 天前

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.

rewind 的头像
rewind3 天前

Good find.

Voltex 的头像
Voltex3 天前

nice share!

Hussain Hashim | Building SundayBack 的头像
Hussain Hashim | Building SundayBack2 天前

@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.

Kuzka_aaa 的头像
Kuzka_aaa3 天前

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?

AI Mastery Guide 的头像
AI Mastery Guide3 天前

MVP in 1 hour is insane honestly

Sai Prasanna Maharana 的头像
Sai Prasanna Maharana2 天前

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

David Starmac Ai 的头像
David Starmac Ai3 天前

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.

Marc illy AI 的头像
Marc illy AI3 天前

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.

Jurly 的头像
Jurly3 天前

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

Agent Rails 的头像
Agent Rails3 天前

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

Money Bunny 的头像
Money Bunny3 天前

Bookmarked this immediately, the timestamps alone make it worth saving

Ryan Ayler 的头像
Ryan Ayler2 天前

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?

Crio Songo 的头像
Crio Songo2 天前

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。

Arthur Melo 的头像
Arthur Melo3 天前

Nice guide

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