Backlog grooming and estimation
Incoming requests are triaged, clarified and sized; a sprint proposal goes to the product owner for approval.
Backlog grooming and estimation is an agent scenario in the Software Delivery sector running on the batch, web, api channels. Trigger: Weekly batch: new requests in the "Triage" column in Jira. The Planning Supervisor coordinates 3 specialist agents (Project Manager Agent, Analyst Agent, Architect Agent) across 4 systems (Jira, Confluence, GitHub, Slack / Teams); of 10 steps, 1 write to systems and 2 are checks or approvals. Outcome: Requests sized and prioritised, sprint 42 proposal approved, Jira and Slack up to date. Approval rule: Sprint scope → product owner approval; agents only propose, never commit items to a sprint.
Backlog grooming and estimation
- Weekly triage: 27 new requests (14 features, 9 bugs, 4 tech debt)
- 3 duplicates merged (PROJ-4901 ↔ 4887), 24 requests ranked; velocity 46 points/sprint
- Plan: clarify vague requests → estimate → propose sprint → product owner approval
- PRD and prior decisions read; clarifying questions drafted for 6 requests
- 6 questions asked in #product, 5 answered; PROJ-4910 parked
- Affected modules and change frequency pulled: 4 requests touch checkout
- Estimate: 23 requests = 118 points; 2 above 13 points → split proposed
- Sprint 42 proposal: 11 requests, 44 points (velocity 46), no dependency clash
- Product owner reviewed the proposal, swapped 1 request, approved sprint 42
- Sprint 42 created, 11 requests moved with points, the rest re-prioritised
- ■completed
Simulation · derived from real agent definitions · every agent can be built by dialogue with the Autonomous Agent and validated with a test corpus
Weekly batch: new requests in the "Triage" column in Jira
Requests sized and prioritised, sprint 42 proposal approved, Jira and Slack up to date
Agents
Planning Supervisor
Decomposes the objective, delegates to agents, manages approval points, merges the result.
Project Manager Agent
Triages requests, merges duplicates, prepares the sprint proposal
list_jira_issuesdetect_duplicatesrank_by_valuepropose_sprintupdate_jira_issueAnalyst Agent
Clarifies vague requests, writes acceptance criteria
search_confluenceask_clarifying_questionwrite_acceptance_criteriaArchitect Agent
Estimates complexity and risk, proposes story points
search_codebaseestimate_complexityflag_dependenciesSteps
| # | Kind | Agent | What happens | System | ms | tok |
|---|---|---|---|---|---|---|
| 01 | ingest | Planning Supervisor | Weekly triage: 27 new requests (14 features, 9 bugs, 4 tech debt) | — | 240 | — |
| 02 | reason | Project Manager Agent | 3 duplicates merged (PROJ-4901 ↔ 4887), 24 requests ranked; velocity 46 points/sprint | — | 1,800 | 3,600 |
| 03 | plan | Planning Supervisor | Plan: clarify vague requests → estimate → propose sprint → product owner approval | — | 280 | 200 |
| 04 | retrieve | Analyst Agent | PRD and prior decisions read; clarifying questions drafted for 6 requests | Confluence | 1,400 | 2,800 |
| 05 | notify | Analyst Agent | 6 questions asked in #product, 5 answered; PROJ-4910 parked | Slack / Teams | 3,200 | 900 |
| 06 | tool | Architect Agent | Affected modules and change frequency pulled: 4 requests touch checkout | GitHub | 620 | — |
| 07 | reason | Architect Agent | Estimate: 23 requests = 118 points; 2 above 13 points → split proposed | — | 2,000 | 3,900 |
| 08 | verify | Project Manager Agent | Sprint 42 proposal: 11 requests, 44 points (velocity 46), no dependency clash | — | 900 | 1,100 |
| 09 | approval | Planning Supervisor | Product owner reviewed the proposal, swapped 1 request, approved sprint 42 | — | 4,000 | — |
| 10 | write | Project Manager Agent | Sprint 42 created, 11 requests moved with points, the rest re-prioritised | Jira | 560 | — |
Legacy module modernisation: analysis, tests, rewrite, PR
Starts from a Jira epic; the old module is read, its behaviour pinned with tests, rewritten and opened as a PR with evidence.
Feature delivery pipeline
A Jira epic turns into criteria, design, code and tests via agents; humans only review and approve the PR.
CI/CD release pipeline
Build, tests, scans and staging run unattended; production ships only on release-manager approval, via ArgoCD.
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