Engineer Builds 12-Skill Framework to Fix AI Coding Agents' Process Failures

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A developer argues that today's AI coding models fail in production not due to lack of intelligence, but due to poor engineering discipline around process and workflow. Four recurring failures were identified: agents begin coding before requirements are clear, lose all context when a session ends, claim completion without running tests, and write code that clashes with an existing codebase's style and architecture. To address these, the developer built a system called Itqan — an Arabic word meaning mastery of a craft — structured around twelve skills and four core rules. A key design principle is that implementation cannot begin until the user approves a written spec, with approval recorded as a file on disk rather than a chat message, ensuring the gate holds even across resumed sessions. The project reframes AI agent improvement as a discipline problem rather than a capability one, drawing a parallel to how even a brilliant new engineer would fail without proper onboarding and process guardrails.

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