Descriptions:
Web Dev Cody breaks down agentic loops — one of the most-discussed patterns in AI-assisted software development right now — and demonstrates how to implement them practically using Claude Code and Codex rather than just describing them abstractly.
The core pattern is straightforward: instead of prompting an AI coding assistant and manually reviewing its output, you hand it a high-level goal and let the harness handle validation automatically. Claude Code’s /goal command is the entry point — give it a task and a success condition (such as passing end-to-end tests via Playwright MCP, a unit test suite, or iterative Lighthouse score checks), and the agent loops until it satisfies the criteria without further human intervention. Cody demonstrates pointing the agent at a feature.md checklist file, using the /loop command to schedule recurring autonomous tasks like daily code cleanup and security audits, and running multiple parallel agent loops for different concerns simultaneously.
The video closes with a live example: adding DigitalOcean sandbox support to Mission Control. Cody prompts Claude Code to explore the codebase using five sub-agents in parallel and produce a phased implementation plan covering implementation, security audit, performance audit, and maintainability review as sequential stages — illustrating how structured agentic loops can enforce automated quality gates at each phase of a feature build, reducing the need for manual review checkpoints.
📺 Source: Web Dev Cody · Published June 08, 2026
🏷️ Format: Tutorial Demo
