Built a skill-driven AI workflow that takes projects from idea and scope discovery through runbook execution and durable documentation
I use reusable AI skills rather than relying on one long prompt or previous chat history. I start by describing the project in plain English and invoking a **project-kickoff skill**. It creates a live project specification containing the objective, scope, constraints, acceptance criteria, concerns, and next actions. For larger or more ambiguous work, I can opt into a **scope-discovery skill**. AI guides me through one important decision at a time, explains the trade-offs, recommends a sensible default, and records each accepted decision until the project is ready to implement. When delivery involves several dependent or risky steps, I can use a **runbook-design skill**. AI converts the agreed scope into a checkpointed implementation plan with validation, rollback, and clear points where my approval or testing is required. AI then executes the runbook, builds the solution, performs automated checks, and records what actually happened. I mainly provide direction, answer business or product questions, and complete the human acceptance checks that AI cannot genuinely perform itself. The skills live inside the project repository alongside the code, decisions, runbooks, and documentation. Codex only links to them at runtime, so the repository remains self-contained and does not depend on my local setup or previous conversations. This also makes the workflow portable. Another capable AI agent or a human engineer can read the repository, understand how the project should be managed, and continue the work without reconstructing everything from chat history. 1. I describe the project in plain English and invoke the **project-kickoff skill**. 2. I use the **scope-discovery skill** for larger or more ambiguous work, working through one decision at a time until the project is ready to implement. 3. I use the **runbook-design skill** when delivery involves dependent or risky steps, creating a checkpointed plan with validation, rollback, and approval or testing points. 4. AI executes the runbook, builds the solution, performs automated checks, and records what actually happened. 5. I provide direction, answer business or product questions, and complete the human acceptance checks AI cannot genuinely perform. 6. I keep the skills, code, decisions, runbooks, and documentation together in the project repository so the workflow remains self-contained and portable.
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