Stop Prompting, Start Designing Loops: The Infrastructure for AI Agents
atShruti · x · 2026-07-22
The author argues that as AI evolves from simple chatboxes into tool-calling agents, traditional prompt engineering is moving up a level. The new core paradigm is designing workflow loops.
A loop gives the model a job rather than a single instruction. The article breaks down the 5 essential steps of a standard loop:
- Discover: Determine what needs to be done.
- Plan: Choose the next action.
- Execute: Do the work using tools.
- Verify: Compare the result against the goal.
- Iterate: Feed the result back in and retry upon failure.
The author emphasizes that a robust loop requires state management (to avoid repeating mistakes), clear stop conditions (to prevent infinite loops draining the budget), and genuine verification checks. The piece also teases a follow-up on "Graphs"—the infrastructure needed when multiple loops start interacting.
Related event: AI Agent Engineering Shifts to Layers and Loops(5 posts)→
More from coding & agent
- huggingface_hub 2.3.0 cuts 1M-file listings to 20s, adds live Bucket following — lhoestq · 2026-10-27
- Nous Research ships Advanced Delegation plugin letting Hermes Agent route subagents to different models — NousResearch · 2026-10-27
- A dentist with a 3D printer discovered OpenAI Codex — and never looked back — gabrielchua · 2026-10-27
- Stanford's PaperFormalizer turns research papers into Lean-verified versions with author in the loop — StanfordUniversity · 2026-10-27
- Hugging Face TRL makes score centering + masked importance sampling default in async GRPO — _lewtun · 2026-10-27
- a16z: agents follow tech's oldest law — chaos first, then rein it in — a16z Newsletter · 2026-10-27