self-improving-engineering

You log engineering learnings by capturing root causes, impacts, and suggested fixes into markdown files within a centralized `.learnings` directory. This records build failures, deployment issues, and code quality insights to establish repeatable improvement patterns across your engineering team.

The best way to capture architectural decisions is logging them as markdown entries in a centralized `.learnings` directory. Widely applicable learnings can then be promoted to Architecture Decision Records, coding standards, and CI/CD runbooks to retain institutional knowledge and standardize engineering practices.

Yes, you can integrate engineering learnings logging across CI pipelines and code reviews. The system supports agent tooling and templates to standardize logging during production incidents and build deployments, interlinking related entries to track recurrence and enable continuous improvement.

You track recurring code quality issues and dependency problems by logging them to a centralized `.learnings` directory where related entries are interlinked. This creates searchable knowledge across projects and integrates with skill extraction workflows to establish reusable improvement patterns.

Logging deployment learnings requires no external dependencies. It operates by writing markdown files to a `.learnings` directory using provided scripts, references, and assets, allowing teams to standardize logging formats and integrate with existing agent tooling without additional environment setup.