AI Builder Shares Thoughts On Emerging Loop Engineering Trend

Had so many thoughts on the "loop engineering" trend.

I spent a few minutes with my writer agent to summarize some of my research, notes, and discussions with students, founders, and startups.

Very early, but new ways of working with agents will start to emerge with a step-change in capabilities.

@omarsar0 It is very important to define what success means - just like lots of things in real life

@omarsar0 Watched $12 burn through API calls because my agent kept retrying a dead browser tab. That's the real loop engineering lesson, knowing when to stop.

@omarsar0 Isn't this what everybody has been doing for the past year and a half?

@malakhovdm damn! loop engineering is not for everything/everyone

@omarsar0 Definitely bookmarked

because your articles always helpful

@omarsar0 @omarsar0 thinking about all the time I wasted prompting instead of setting up loops. feels like I've been doing it wrong this whole time 😂

@omarsar0 The key word is surface. Loops need places to leave evidence: decisions, checks, failures, repairs, and what should be reused. Without that surface, “loop engineering” becomes just another prompt style.

@omarsar0 Saved!) Very helpful

@leozc Yup! Strongly agree. It's the part that's the most challenging IMO to define to the agents when using things like the /goal feature.

@omarsar0 Loop Engineering trend in AI of summer 2026

@omarsar0 Loops are the easy 10%. The other 90% is what happens when your agent loops on a 3am API reject.

@omarsar0 this is so good. love your content. keep it coming 🫡

@omarsar0 Loop engineering is where it gets real. The key isn't more iterations, it's agents self-correcting and pivoting. That's the step-change! But who's building the open-source tooling for this?

@omarsar0 ICRL is finally in fashion

Excellent breakdown, Elvis — this is the clearest explanation I’ve seen of why ‘loop engineering’ is the real shift. The PR babysitter + /goal examples make it immediately actionable. One thing I’m experimenting with: using a cheaper/faster model for the verifier (like DeepSeek or Qwen) while keeping the main coder on Opus/Claude. Has that been reliable in your runs, or do you see too many false negatives? Also bookmarking for the crabfleet mention — looks like the missing infrastructure layer. Great stuff.

@omarsar0 been seeing this shift too - feels like we're moving from "prompt once and pray" to actually iterating with the agent like a real collab

curious what patterns you're seeing work best in practice?

@omarsar0 融资可以讲情怀，但产品必须讲逻辑。用户不关心你的技术多先进，只关心能不能解决他的问题。 「Had so many thoughts on the "loop engineering" trend」

The prompt-to-loop shift is right, but the underexplained part is what the loop carries between turns — not just re-prompting but state: what's been tried, what's open, what it knows. A loop without durable state just relives the same mistakes faster. Control flow is the easy part.