From idea to evolving automation
CoffeeBreakAI follows the same repeatable lifecycle on every ticket so stakeholders can trust the outcome and prove impact. Each stage is observable, auditable, and ready for reviewer input.
- 1
Plan
Ingest issues from Jira, Azure DevOps, Slack, or native forms. Task Router decomposes the work and surfaces approvals to reviewers.
Artifacts: structured plan, linked requirements, reviewer checklist.
- 2
Develop
Agent ensembles implement the plan, provision branches, and reuse domain memory so past fixes accelerate the current run.
Artifacts: commits with annotations, dependency notes, replayable commands.
- 3
Review
CoffeeBreak’s AI reviewer collaborates with humans to address feedback. Process Compliance enforces metadata, policy acknowledgements, and audit trails.
Artifacts: threaded comments, approval log, compliance checklist.
- 4
Test
CI/CD worker agents update YAML, run pipelines, capture logs, and surface failure triage recommendations. Self-healing automation retries when integrations wobble.
Artifacts: pipeline runs, retry history, remediation guidance.
- 5
Deploy
Deployment orchestration applies approvals, coordinates release steps, and logs status back to the workspace dashboard and notification hub.
Artifacts: deployment record, rollback plan, notification transcript.
- 6
Observe
Dashboards, persona KPIs, and adoption analytics highlight impact. Notification Hub routes follow-ups when SLAs or blockers emerge.
Artifacts: KPI snapshot, alert log, exportable analytics.
- 7
Evolve
Feedback ingests into reinforcement learning and marketplace-ready insights. Templates update, ensembles retrain, and the cycle restarts stronger.
Artifacts: learning dataset snapshot, template revisions, coaching insights.
Ready to see it in action?
Jump into the documentation for implementation steps or walk through the persona guides to tailor CoffeeBreak to your workflow.