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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 просмотров • 3 дней назад •via X (Twitter)

Комментарии: 15

Фото профиля Kamal Bisht 🔴 AI Marketer
Kamal Bisht 🔴 AI Marketer3 дней назад

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.

Фото профиля rewind
rewind3 дней назад

Good find.

Фото профиля Voltex
Voltex3 дней назад

nice share!

Фото профиля Hussain Hashim | Building SundayBack
Hussain Hashim | Building SundayBack3 дней назад

@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.

Фото профиля Kuzka_aaa
Kuzka_aaa3 дней назад

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?

Фото профиля AI Mastery Guide
AI Mastery Guide3 дней назад

MVP in 1 hour is insane honestly

Фото профиля Sai Prasanna Maharana
Sai Prasanna Maharana3 дней назад

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

Фото профиля David Starmac Ai
David Starmac Ai3 дней назад

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.

Фото профиля Marc illy AI
Marc illy AI3 дней назад

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.

Фото профиля Jurly
Jurly3 дней назад

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

Фото профиля Agent Rails
Agent Rails3 дней назад

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

Фото профиля Money Bunny
Money Bunny3 дней назад

Bookmarked this immediately, the timestamps alone make it worth saving

Фото профиля Ryan Ayler
Ryan Ayler2 дней назад

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?

Фото профиля Crio Songo
Crio Songo2 дней назад

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。

Фото профиля Arthur Melo
Arthur Melo3 дней назад

Nice guide

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