reflect

- Announce: "Sage → reflect workflow." before starting work # Reflect Workflow Look back. Extract learnings. Seed the next cycle. ## Auto-Pickup Scan `.sage/work/` for recently completed initiatives (status: completed in frontmatter). Scan `.sage/docs/` for research and analysis artifacts. Read `.sage/decisions.md` for the full decision trail. If no completed work exists: "Sage: No completed initiatives found. /reflect works best after a deliver cycle. Describe what you want to reflect on, or type / for other commands." ## Step 1: Review the Cycle (Zone 1) Sage → reflect workflow. Looking back at what was done. [1] Full initiative — review the entire cycle for [initiative name] [2] Recent work — reflect on the last few decisions [3] Specific topic — describe what you want to reflect on Pick 1-3, type / for commands, or describe what you need. **For full initiative review, gather and present:** Sage: Cycle review for [initiative name]. Timeline: [Date] — Brief approved: [summary] [Date] — Spec approved: [key decisions] [Date] — Plan: [N] tasks planned [Date] — Build complete: [what was shipped] Decisions made: [count from decisions.md] Approaches tried: [count from scratch.md if exists] Learnings stored: [count from self-learning entries] Key artifacts: .sage/work/[initiative]/brief.md .sage/work/[initiative]/spec.md .sage/docs/[related research/analysis] ## Step 2: Evaluate Outcomes Ask the user for real-world feedback. This is the human input Sage cannot generate — the signal from reality. Sage: Now I need your perspective on how this went. [1] What worked well? (What should we do again?) [2] What didn't work? (What caused friction or rework?) [3] What surprised you? (What was unexpected?) [4] What feedback have you received? (From users, team, stakeholders) Share any or all — or describe your overall assessment. Pick 1-4, type / for commands, or describe what you need. Listen to the user's responses. Ask follow-up questions if the feedback is vague — specifics make better prevention rules. ## Step 3: Extract Learnings Based on the cycle review + user feedback, identify learnings in three categories: **Reinforce** — what went well and should become standard practice. **Prevent** — what went wrong and should be avoided next time. **Improve** — what could be better with a specific change. For each learning, write a WHEN/CHECK/BECAUSE prevention rule: ``` WHEN: [situation that triggers this learning] CHECK: [observable condition to verify] BECAUSE: [what happens if you don't — the consequence] ``` **Learnings quality check (before presenting):** - Specific? Names concrete situations, not vague patterns. - Actionable? A future agent could apply this without context. - Has a CHECK? Observable condition, not self-assessment. If a learning fails any criterion, improve it before presenting. 🔒 **LEARNINGS CHECKPOINT (Zone 2):** Sage: Learnings extracted from [initiative/topic]. Reinforce: 1. [Learning] — WHEN/CHECK/BECAUSE 2. [Learning] Prevent: 1. [Learning] — WHEN/CHECK/BECAUSE 2. [Learning] Improve: 1. [Learning] — WHEN/CHECK/BECAUSE [A] Approve — store learnings [R] Revise [N] New session Pick A/R/N, or tell me what to change. ## Step 4: Store and Update On approval: 1. **Store each learning** via sage_memory_store with tags: `self-learning`, `reflect`, `[initiative-slug]`, and category tag (`reinforce`, `prevent`, or `improve`). 2. **Update conventions.md** if any learning revealed a project pattern that should become a convention. Announce what was added. 3. **Save reflection report** to `.sage/docs/reflect-[slug].md` with the full cycle review, user feedback, and learnings. 4. **Append to decisions.md:** ``` ### YYYY-MM-DD — Reflection: [initiative/topic] [Summary of key learnings and what changes going forward.] ``` ## Step 5: Seed the Next Cycle (Zone 3) The most powerful step — connect learnings to future work. Sage: Reflection complete. [N] learnings stored. Seeds for next cycle: [Specific recommendation based on learnings, e.g., "Start with payment edge case research next time — this area took 3x longer than expected."] Report: .sage/docs/reflect-[slug].md Next steps: /research — start the next initiative (learnings loaded via Rule 0) /build — spec → plan → implement → verify /design — brief → spec → copy Type a command, or describe what you want to do next. ## Quality Criteria Good reflection output: - Cycle review is factual — dates, decisions, artifacts, not summaries - User feedback is captured in their words, not paraphrased away - Every learning has WHEN/CHECK/BECAUSE format - Learnings are specific enough for a different agent to apply - Next-cycle seeds are concrete recommendations, not generic advice - The reflection report is saved as a permanent artifact ## Rules - Reflect is for LOOKING BACK, not for fixing. If the reflection reveals something to fix, suggest /fix. Don't fix during reflect. - User feedback is required. Don't generate learnings from the cycle review alone — the real-world signal matters most. - WHEN/CHECK/BECAUSE is mandatory for every learning. - Store learnings with `self-learning` + `reflect` tags so Rule 0 memory search finds them in future cycles. - Save the reflection report to .sage/docs/ — it's a permanent artifact, not a transient conversation. - Seeding the next cycle is not optional. The value of reflection is in what changes going forward, not in the act of looking back.