5 Workflows to Extract AI Model Knowledge

1. Plant its standards: Open each project and have Fable rewrite your claude.md as the operating manual a weaker model would need: your conventions, the mistakes to prevent with the rule that stops each one, the quality bar as checkable criteria. Then have it write your 3 highest-leverage skills in full. 2. The consultant audit: Give it your projects and numbers with one prompt: "act as the consultant i can't afford, audit everything, deliver a roadmap a less capable model can execute step by step. The reasoning gets written down while the model that produced it is still flat-rate." 3. The second brain run: Fire deep research runs on your niche, your competitors, your customers' problems. Mine every run into an Obsidian vault, one insight per note. A hundred linked notes get reused, one long report gets buried. 4. /goals + dynamic workflows: Describe what done looks like, demand the proof pasted in the finish line, cap every run with a turn or time limit. The model builds unattended for hours while the tokens still cost nothing extra. 5. The recorder skill: One skill that fires after every hard problem: the approach, the judgment calls, the reusable rule, saved as a note in your repo. Wire it into your claude rules and Fable documents its own thinking all day, automatically.