Created by Wyatt Brocato
Every AI post right now says the same thing. Stop prompting. Build loops. Graphs are next.
None of them hand you a single working example.
I spent two weeks digging through the transcripts, the threads, and the demos behind the hype. I found some real signal buried under a lot of noise. I also found something embarrassing: the "loop" I'd been using in my own prompts wasn't a loop at all.
This guide is the six prompts I came out with. Three loops. Three graphs. Copy, paste, fill in the brackets, run today.
No new tools. No agent frameworks. Just prompts that know when they're done.
<aside>
You've been working 5-15 years. You use ChatGPT or Claude regularly. You've probably written something like "keep going until you're confident this is right" into a prompt and watched it either stop after one pass or spiral into nowhere.
This guide is for that person.
Nothing to install. Nothing to buy. Just six prompts with real exit conditions, and an honest map of where loops and graphs actually fit in a normal job.
</aside>
The AI conversation has moved on to "loop engineering" and "graph engineering" without ever explaining either one.
Here's the short version, because it's genuinely simpler than the buzzwords make it sound:
A loop is a prompt that repeats until a specific condition is met. Not "until it's good." Until a checkable, written-down condition is met. A loop without an exit condition isn't a loop. It's a vibe.
A graph is what you get when one loop isn't enough. Instead of one agent doing everything, you split the work into steps (nodes), define how output moves between them (edges), and let the state carry forward. A loop is just a graph with one node and an edge back to itself.
That's it. That's the whole taxonomy. The rest is application.
If you can't write down what "done" means, don't loop.