Your AI Agent Doesn't Need to Be Smarter. It Needs Discipline

Описание и применение

Система Itqan внедряет дисциплину в работу ИИ‑агентов, обеспечивая утверждение спецификаций, сохранение контекста, доказательства выполнения и соблюдение стиля кода, что делает генерируемый код готовым к релизу.

Задача

AI coding agents produce code that is technically correct but not shippable because they skip essential engineering discipline—spec approval, context persistence, proof of correctness, and adherence to existing conventions.

Результат

By embedding discipline into the AI workflow, Itqan turns AI agents from code generators into reliable engineering assistants that produce shippable code with minimal rewrites and clear traceability.

Рабочий процесс

• 1. Scan repo to detect stack, patterns, and conventions.
• 2. Present findings to developer for correction and confirmation.
• 3. Store corrected conventions on disk as a persistent rule set.
• 4. Await disk‑based approval gate before any implementation begins.
• 5. Generate a spec and plan, saving them as files.
• 6. Execute tasks in lifecycle phases: define, blueprint, construct, verify, inspect, release.
• 7. Log every clarifying question and answer in a structured file.
• 8. Run tests, capture output, and verify success before marking done.
• 9. Produce a changelog entry explaining why changes were made.
• 10. Store all artifacts on disk to survive session restarts.

Доказательства

The gates were supposed to be a safety feature. They turned out to be a speed feature.

Источник

Agents skip all of that by default. Not because they can't do it, but because nobody asked them to.

Источник