Ai

An agent that gets better on its own has to change something about itself, and something has to check the change. This post walks the six things it can change, the checker that decides whether any of it worked, the ceiling it runs into, the ways it breaks, and the loop teams actually run in production.

What graph engineering is, how it differs from loops and workflow engines, when to build one, a refund approval worked through end to end, and the failure modes to watch for.

Why AI work moved from single prompts to loops, the main types of loops, and examples of goal-driven loops in practice.

Build your own Claude Code extensions from scratch: skills with SKILL.md, custom subagents, and lifecycle hooks. Copy-paste examples, a combined worked workflow, and a tour of the most popular skill repos on GitHub.

A practical field guide to the systems that wrap an LLM and turn it into a reliable agent — with patterns, worked examples, real deployments, and where the field is heading (mid-2026).