The problem: ad-hoc prompts don’t scale
“I use ChatGPT” or “I use Claude” is fine for one-off tasks. But when you’re iterating on product specs, drafting landing copy, or refining roadmap items, you need consistency. The same context, the same constraints, the same workflow—every time. Ad-hoc prompts in a chat window don’t get you there.
What does “AI-ready” look like when you’re serious about repeatability?
The approach: versioned, structured guidance
My setup lives in git. Not prompts in a doc—actual rules, skills, and commands that the AI reads automatically.
Domain rules —
.cursor/rules/files that tell the AI: “This folder is product docs. Use Flixup voice. Don’t mix in other domains.” When I’m inbusiness-flixup/, the AI knows the context.Skills — Step-by-step workflows. E.g. “Create a landing page from business markdown”: config file, persona, messaging, then 11ty + Tailwind. The AI follows the skill, not a vague “make a landing page.”
Commands — Slash commands.
/compare-cost "What is our positioning?"runs our RAG cost estimator and shows full vs RAG tokens and cost. No typing, no context switch.
Rules scope the AI. Skills standardize the workflow. Commands wire tools into the editor.
Why it beats “prompts in a chat”
Versioned — Change a rule, commit it. Everyone gets the update. No “which version of the prompt did you use?”
Discoverable — New team members (or future you) see the structure. Rules and skills document how we work.
Composable — A landing-page skill can call a product RAG query. Commands can chain. Ad-hoc prompts don’t compose.
Testable — Run the same command with the same input. Compare outputs. Iterate.
One concrete workflow
Product docs → roadmap items. I have the AI read our product markdown, extract features and initiatives, and draft Linear issues. The AI sees our backlog via Linear MCP. It can refine issue titles and descriptions so intent stays clear. The loop: docs define intent, AI drafts, human prioritizes. Rules keep the AI in our product domain. Skills define the extraction format. No manual copy-paste.
Takeaway
“AI-ready” isn’t about using the latest model. It’s about rules, skills, and commands in version control. Structure beats prompts. When you care about consistency and scale, put it in git.