Short Leash AI Coding Method: Beat Fable by Keeping Control

Greg Slepak, maintainer of security-critical software, distills over a year of research into AI coding agents into the short leash method. It's designed for expert developers who want AI to boost output without sacrificing quality — and claims to beat Fable 5 results even without frontier models.

The core problem Slepak identifies: AI agents regularly "go off the rails," produce ugly/inefficient code, or require YouTuber-style orchestration systems that remove the developer from the loop. His method keeps you in control at every step.

Short Leash Rules

• Plan the task, optionally using something like tasks skill to break large tasks into steps.
• Never use "YOLO" mode (aka "dangerously skip permissions").
• The AI only works while you are watching — no "vibe coding" while you play video games.
• Use a coding agent that displays a diff in the permissions prompt before making changes.
• Analyze each proposed diff — deny permissions whenever the AI is about to do something you don't want.
• Keep yourself in the loop to maintain up-to-date understanding of the codebase.
• Intervene frequently to prevent the AI from going off the rails.
• Commit after every subtask to protect against the AI deleting previous work (Slepak has seen Opus do this).

AI Reviews

Slepak recommends treating AI as a linter for PR reviews. The AI catches common mistakes, the human catches high-level issues. Both together outperform either alone. The AI needs sufficient context (issue, PR description).

He also notes that he built custom AI review tools performing as well as multi-billion-dollar systems, and maintains a fork of an agent called Crush.