> workflow / continuous-improvement
Continuous Improvement
Convert incidents, retros, and metrics into updated prompts, skills, evals, and debt paydown — then feed the next idea cycle.
What should I do next?
Complete the steps and evidence below, clear the human gates, then loop improvements back into prompts, skills, and evals.
When to use
- A release or incident produced learnings that must not stay in chat
- Eval golden sets or prompts drifted from production reality
- Technical debt from AI velocity needs scheduled paydown
- You are preparing the next initiative with better harness defaults
Step-by-step
- Collect inputs: incident actions, retro notes, cost/quality metrics, review themes.
- Run knowledge-capture.prompt; land updates in skills/prompts/docs — not wikis alone.
- Prioritize technical-debt.prompt items with expiry; schedule paydown slices.
- Improve evals that missed real failures; version prompts with regression suites.
- For legacy drag, apply legacy-modernization or migration patterns deliberately.
- Propose standard/harness changes via PR; pilot before org-wide rollout.
- Close the loop by feeding the next Idea brief with constraints learned.
Decisions to make
- What becomes a standard vs a team-local convention
- Debt paydown vs new feature capacity split
- Prompt/skill version bump policy
- Whether a migration initiative is warranted
Evidence to collect
- Merged updates to skills/prompts/evals
- Debt backlog with owners and dates
- Eval regression results on prompt changes
- Retro actions closed or explicitly deferred
Role-specific next actions
- PM: Reserve capacity for debt and harness improvements — not only features.
- Architect: Promote cross-cutting learnings into ADRs and platform defaults.
- Engineer: Land skill/prompt/eval PRs; refuse tribal knowledge.
- Engineering Manager: Run the pilot → adopt cycle for new patterns.
Inputs
- Incidents and PIR actions
- Retro notes and review themes
- Production quality/cost metrics
Outputs
- Updated skills, prompts, and docs
- Debt and eval improvement backlog
- Candidate standard changes for pilot
Required prompts
- Technical debt
Structures debt with cost, risk, and expiry.
- Knowledge capture
Turns incidents/retros into durable artifacts.
- Migration
When improvement requires a deliberate migration program.
Required skills
- Documentation
Keeps learnings in-repo and reviewable.
- Evaluation
Evolves golden sets and gates from production misses.
Required MCP servers
- GitHub MCP
Land improvement PRs and track harness changes.
- Jira MCP
Optional: track debt paydown work.
Tooling & handbook
- Legacy modernization pattern
Incremental strangler for inherited systems.
- Migration pattern
Safe data/service transitions.
- knowledge-capture hook
Remind/enforce capture after incidents.
- Org playbook
Org-level adoption of improvements.
Recommended agents & patterns
- Migration pattern
When improvement is a migration.
- Legacy modernization pattern
When improvement is strangling legacy.
- Knowledge agent
Assists capture into the corpus.
- Migration agent
Assists migration planning under architect ownership.
Human approval gates
- Standard/harness changes reviewed before org-wide rollout
- Eval/prompt changes require regression green before merge
Automation opportunities
- Prompt version bumps tracked in git
- Eval regression on prompt/skill changes
- knowledge-capture.hook.sh after SEV close
Enterprise best practices
- Pilot → adopt cycle for new patterns
- Contribute proven improvements back to AIES / internal standards
- Measure harness ROI (defect escape, token cost, lead time)
Common mistakes
- Tribal knowledge only in chat
- Never updating golden evals after production misses
- Declaring "process improvements" without merged artifacts