Brainstorm

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Facilitate a structured PO/BA brainstorming session via the Double Diamond process (diverge to discover problems and opportunities, then converge to validate and prioritize) to deliver a scored, ranked shortlist of 3-5 candidate ideas — each carrying a problem + value hypothesis, an identified riskiest assumption, and the cheapest validation test designed — so the team commits to the right problem AND the right solution before building, never to a flat unvalidated idea list. The default flow converges to ONE opinionated recommendation; the EXCEPTION is Multi-Opportunity Discovery mode, which instead outputs a ranked 3–8-item RICE opportunity map for user multi-select (each selected item becomes a separate PBI downstream).

Summary:

• Main steps (Phases 0→7) — the read-this-if-nothing-else map: P0 Session Setup (AskUserQuestion to detect scenario + role + how-much-known) → P1 Problem Framing / Diamond-1 diverge (POV statement → 5 Whys/Fishbone → JTBD job stories → 5–10 HMW) → P2 Opportunity Framing / Diamond-1 converge (OST / Lean Canvas / Blue-Ocean ERRC / Value-Prop Canvas) → P3 Ideation / Diamond-2 diverge (SCAMPER → Crazy 8s → Brainwriting 6-3-5 → Impact Mapping → Analogy = 25–40 raw ideas, zero judgment) → P4 Evaluation / Diamond-2 converge (Dot Vote → RICE → Kano → 2×2 → MoSCoW = ranked 3–5 shortlist) → P5 Hypothesis Validation (Problem + Value card + Riskiest-Assumption Test + cheapest test + Build-Measure-Learn per top-3) → P6 Decision (ONE opinionated recommendation + trade-offs) → P7 Documentation & Handoff. Multi-Opportunity Discovery mode swaps P6 for a ranked 3–8-item RICE opportunity map.
• Run AskUserQuestion Phase 0 FIRST to detect scenario (Problem-Solving / New Product / Enhancement / Multi-Opportunity Discovery), role (PO / BA / Mixed), and how-much-is-known — each scenario routes a different technique sequence (see Scenario Cheat Sheets) — why: misclassifying here derails every downstream phase.
• Strictly separate diverge (Phases 1 & 3 — generate, "Yes, and…", zero judgment) from converge (Phases 2 & 4 — narrow, RICE/Kano/MoSCoW scoring); mixing the two modes is the Golden Rule violation that kills idea output.
• Never stop at a raw or flat idea list: every top-3 candidate MUST carry a problem + value hypothesis card, an identified riskiest assumption (RAT), and the single cheapest validation test designed before any build commitment.
• Close with an opinionated decision (Phase 6 — recommend ONE option with trade-offs, not a menu), every claim evidence-backed at >80% confidence, then offer handoff via AskUserQuestion to /idea, /refine, /plan, etc. — EXCEPT in Multi-Opportunity Discovery mode, where convergence RANKS the opportunity map (3–8 RICE-scored items) and hands off via multi-select to a per-opportunity PBI loop instead of picking ONE winner.
• Apply the shared isLargeIdea rule during convergence. For any true signal, capture one complete large_idea_decomposition block in the owning idea/PBI/spec handoff: ordered releasable slices, dependency order, non-goals, risk/evidence owners, and deferred-work owners. This is embedded scope context; it does not create docs/product-roadmap.md.
• If --mode=roadmap, frame product outcomes and milestone choices, then hand off to /product-roadmap; this explicit mode may create/update docs/product-roadmap.md and does not choose implementation. If --mode=scope, resolve and amend the selected stable scope brief in place, then stop before scenario/plan work.

Four Scenarios:

Double Diamond (master meta-framework):

DIAMOND 1: Right Problem          DIAMOND 2: Right Solution
────────────────────────────      ──────────────────────────
Discover ──► Define               Develop ──► Deliver
(diverge)    (converge)           (diverge)   (converge)

Golden Rule: NEVER evaluate ideas while generating them. Diverge and converge are separate modes. Mixing them kills creative output.

Be skeptical. Apply critical thinking. Every idea needs a testable hypothesis. Confidence >80% required before recommending.

Roadmap and Scope Modes

Resolve the flag before Phase 0:

--mode=roadmap is not a shortcut around owner approval. Use AskUserQuestion for milestone boundaries and lifecycle terms. The product-roadmap skill owns the canonical artifact and selection gate; this mode supplies structured framing to it.

--mode=scope MUST resolve the existing scope-brief path from the product-roadmap handoff, $ARGUMENTS, or active plan context, then amend that file in place. If no stable plans/{plan-id}/scope-brief.md is available, stop and route to /product-roadmap; never create a competing scope brief or write one under plans/reports/.

For the default mode, do not route to --mode=roadmap merely because the idea is broad. Evaluate:

isLargeIdea = multipleIndependentOutcomes
            || ambiguousOrResearchHeavy
            || releaseScopeDecomposition
            || oversizedPbiThatMustSplit

When true, the brainstorm handoff owns this portable block and downstream skills consume it read-only. When all four signals are false, omit the block and all roadmap/milestone placeholders. An existing roadmap is context only unless the user explicitly chose --mode=roadmap.

Answer this question:

$ARGUMENTS

Phase 0: Session Setup (MANDATORY)

Use AskUserQuestion to detect scenario, role, and constraints before any technique.

0.1 — Scenario Detection

Ask:

1. "What scenario are we in?"
   • Problem-solving — something is broken, users struggle, a metric is bad
   • New product — greenfield, no existing product in this space
   • Feature enhancement — existing product, add/improve/remove capability
   • Multi-opportunity discovery — a raw product vision / problem statement spanning MULTIPLE distinct opportunities that should each become a separate PBI (do NOT converge to one — produce a ranked RICE opportunity map for multi-select; see Multi-Opportunity Discovery Mode)
   • Mixed — multiple of the above

Mode routing: If the input is a broad vision/problem spanning several distinct opportunities (typically driven by workflow-idea-to-pbi's MULTI-OPPORTUNITY DISCOVERY MODE), select Multi-opportunity discovery — it changes Phase 6 convergence from "pick ONE" to "rank a 3–8-item RICE opportunity map for multi-select." All other scenarios keep the single-recommendation default.

2. "What is the primary role in this session?"

   • Product Owner — outcome-focused, business value, user outcomes
   • Business Analyst — requirements-focused, process analysis, stakeholder mapping
   • Both PO + BA — full discovery and requirements
   • Developer / Architect — technical feasibility brainstorm

3. "How much is already known?"

   • Raw seed — just an intuition or observation
   • Problem confirmed — we know the problem, need solutions
   • Solution direction known — need to evaluate and score options
   • Idea exists — need hypothesis validation only

0.2 — Context Loading

• If project codebase exists: read docs/specs/ to understand domain
• If greenfield: skip codebase reading; rely on user input and web research
• Load docs/project-reference/domain-entities-reference.md if entity context needed
• Use WebSearch for market/competitor context when scenario = New Product or Enhancement

Phase 1: Problem Framing — Diamond 1 Diverge

Goal: Fully understand problem space before jumping to solutions. #1 brainstorming failure: solving the wrong problem.

Time-box: 20–45 minutes of session time.

1.1 — Problem Statement (POV Format)

Formulate a crisp problem statement BEFORE any ideation:

[User/Persona] needs [need/job-to-be-done]
because [insight/root cause/context],
but [current barrier/friction/failure].

Example:

Operators need to quickly identify high-priority orders for action
because peak-season backlogs delay fulfillment,
but the current system shows raw order data with no ranking or comparison.

Use AskUserQuestion to validate:

• "Is this the core problem, or a symptom of a deeper problem?"
• "Who specifically experiences this? How often? What's the cost?"
• "What evidence do we have this problem actually exists?"

1.2 — Root Cause Analysis (for Problem-Solving scenario)

Apply one of:

5 Whys:

Problem: [stated problem]
Why 1: [first cause]
Why 2: [cause of cause 1]
Why 3: [cause of cause 2]
Why 4: [cause of cause 3]
Why 5: [root cause] ← Fix HERE, not at Why 1

Fishbone (Ishikawa) — for systemic problems: Spine = problem statement. Bones = 6 cause categories:

• People, Process, Technology, Data, Environment, Policy
• For each bone: ask "What in this category could cause the problem?"

1.3 — JTBD (Jobs-To-Be-Done) — for New Product & Enhancement

Replace user stories with job stories to expose real motivation:

User Story (what): As an operator, I want to see order totals, so that I can make decisions.

Job Story (why + context): When I'm clearing a peak-season backlog with limited time, I want to instantly see which orders need action without opening every record, so I can make fast, defensible decisions before the cutoff.

Job Story Formula:

When [triggering situation + context],
I want to [motivation / job to be done],
so I can [outcome / expected result].

Generate 3–5 job stories covering main user segments. Each story = one opportunity.

1.4 — HMW (How Might We) Reframing

Transform problem statements into ideation-ready questions:

Formula: "How might we [verb] [object] so that [desired outcome]?"

From the POV statement:

• "How might we help HR managers rank employees so that promotion decisions take minutes not days?"
• "How might we surface hidden top performers so that managers discover talent they'd otherwise miss?"
• "How might we reduce bias in performance scoring so that promotion feels fair to all employees?"

Rules:

• Each HMW covers ONE idea direction
• Generate 5–10 HMW questions per problem
• Too broad = "How might we improve HR?" (useless) → too narrow = "How might we add a sort button?" (skip ideation, just build it)
• Sweet spot: one-concept questions that invite multiple solutions

Output of Phase 1:

• Problem statement (POV format)
• Root cause (5 Whys or Fishbone) — Problem-Solving only
• 3–5 Job Stories
• 5–10 HMW questions

Phase 2: Opportunity Framing — Diamond 1 Converge

Goal: Narrow problem space to highest-opportunity focus areas before ideating solutions.

2.1 — Opportunity Solution Tree (OST) — for Enhancement

Teresa Torres' framework. Maps desired outcome → opportunities → solutions → experiments.

Desired Outcome (business metric)
├── Opportunity 1 (unmet user need / pain / want)
│   ├── Solution A
│   └── Solution B
├── Opportunity 2
│   ├── Solution C
│   └── Solution D
└── Opportunity 3 (deprioritized)

Step 1: State ONE desired outcome (lagging metric the team owns — e.g., "Increase manager satisfaction with review process from 3.2 to 4.0 CSAT") Step 2: Map ALL known opportunities (pains, needs, wants) from research/interviews Step 3: For each top opportunity, generate solution directions (not detailed solutions yet) Step 4: Pick 1–2 opportunities to develop further in Phase 3

2.2 — Lean Canvas — for New Product

One-page business model for greenfield ideas (Ash Maurya):

Fill one canvas per major target segment. Keep it to 20 min — speed is the point.

2.3 — Blue Ocean ERRC Grid — for Enhancement or New Product

Eliminate-Reduce-Raise-Create grid (Chan Kim & Mauborgne):

Rule: Every innovation should have at least ONE item in Create AND one in Eliminate. A product with only Raise entries is incremental — not differentiated.

2.4 — Value Proposition Canvas

Connects customer profile to product value:

Customer Profile:

• Jobs (functional, social, emotional)
• Pains (frustrations, obstacles, risks)
• Gains (benefits, desires, measures of success)

Value Map:

• Products & Services (what you offer)
• Pain Relievers (how you reduce pains)
• Gain Creators (how you produce gains)

Fit = where Pain Relievers match Pains + Gain Creators match Gains.

Output of Phase 2:

• OST with 2 selected opportunities (Enhancement)
• Lean Canvas (New Product)
• ERRC grid (New Product or Enhancement)
• Value Proposition fit assessment

Phase 3: Ideation — Diamond 2 Diverge

Goal: Generate maximum quantity of solution ideas without judgment. Quality comes Phase 4.

Critical rule: NO evaluation in this phase. Every idea is valid. "Yes, and..." not "Yes, but..."

3.1 — SCAMPER

Apply each lens to the problem/existing product to generate solution directions:

Generate at least 2 ideas per SCAMPER letter = minimum 14 ideas.

3.2 — Crazy 8s (Rapid Visual Ideation)

Time-box: 8 minutes. 8 ideas. No refinement.

Process:

1. Fold paper into 8 sections (or create 8 boxes mentally)
2. Sketch one idea concept per box — rough is fine
3. Timer forces quantity over perfection
4. Share and build on sketches

For AI-facilitated sessions:

• AI generates 8 distinct solution directions in 2 minutes
• User picks top 3 to explore deeper
• Each direction = 1 sentence + 1 key differentiator

3.3 — Brainwriting 6-3-5

For multi-stakeholder sessions (async-friendly):

• 6 participants, 3 ideas each, 5 rounds
• Each round: read previous ideas → add 3 new ideas OR build on existing
• Result: up to 108 ideas in 30 minutes (works async via shared doc)

For AI-facilitated sessions:

• AI plays all 6 roles across 3 rounds
• Generates ideas from: PO perspective, BA perspective, End User perspective, Dev perspective, Ops perspective, Business perspective

3.4 — Impact Mapping

Gojko Adzic's technique. Maps Goal → Actors → Impacts → Deliverables:

GOAL: [business outcome with measurable target]
├── ACTOR: Who can help/hinder?
│   ├── IMPACT: How should behavior change?
│   │   └── DELIVERABLE: What feature produces this impact?
│   └── IMPACT: What negative behavior to prevent?
│       └── DELIVERABLE: What reduces this risk?
└── ACTOR: ...

Key insight: Work backward from GOAL. If a deliverable doesn't trace to an actor behavior change, don't build it.

3.5 — Analogical Thinking

"How does [industry X] solve [similar problem Y]?"

Output of Phase 3:

• SCAMPER grid with 14+ ideas
• Crazy 8s — 8 solution directions
• Impact Map (top 2 goals)
• Analogy-inspired ideas (3–5)
• Total raw idea count: target 25–40 ideas

Phase 4: Evaluation & Convergence — Diamond 2 Converge

Goal: Reduce 25–40 raw ideas to a ranked shortlist of 3–5 candidates for hypothesis testing.

4.1 — Dot Voting (First Pass)

Before scoring, do a quick gut-check elimination:

• Each idea gets a ✅ (keep) / ❌ (drop) / 🔄 (merge with another)
• Merge near-identical ideas
• Drop ideas that violate hard constraints (budget, tech, legal)
• Target: reduce to 10–15 candidates

4.2 — RICE Scoring

Rank remaining candidates:

RICE Score = (Reach × Impact × Confidence) / Effort

Reach:      Users affected per quarter (100 / 500 / 1000 / 5000+)
Impact:     0.25 minimal | 0.5 low | 1 medium | 2 high | 3 massive
Confidence: 0.5 low (gut feel) | 0.8 medium (some data) | 1.0 high (validated)
Effort:     Story Points — 1 trivial | 3 small | 5 medium | 8 large | 13 very large

Score all 10–15 candidates. Sort descending. Top 5 = shortlist.

4.3 — Kano Model Classification

For each shortlisted idea, classify:

Strategy: Must-Be → Performance → Delighter. Never skip Must-Be items for Delighters.

4.4 — Effort × Impact 2×2

Quick visual triage:

HIGH IMPACT
    │  Quick Wins ★    │  Major Projects ⚙️
    │  (do first)      │  (schedule carefully)
────┼──────────────────┼────────────────────
    │  Fill-Ins 📋     │  Money Pits ⚠️
    │  (if time)       │  (avoid or cut)
LOW IMPACT
         LOW EFFORT         HIGH EFFORT

Plot each shortlisted idea. Quick Wins = default first picks unless Major Project has strategic necessity.

4.5 — MoSCoW for Release Scope

For each idea in the shortlist, assign release priority:

Output of Phase 4:

• Dot-voted shortlist (10–15 ideas)
• RICE-scored table (top 5 ranked)
• Kano classification for each shortlisted idea
• 2×2 matrix placement
• MoSCoW assignment per idea

Phase 5: Hypothesis Validation

Goal: Before committing to build, test riskiest assumptions. 42% of startups fail from no market need — validate before building.

5.1 — Problem Hypothesis

**We believe** [target users/persona]
**Experience** [specific problem]
**Because** [root cause]
**We'll know this is true when** [validation metric/observable evidence]

Example:

We believe Operators
Experience frustration identifying high-priority orders during peak backlogs
Because order data is fragmented across 3 systems with no unified ranking
We'll know this is true when 3+ operators confirm they spend >2hrs per shift on manual data aggregation

5.2 — Value Hypothesis

**We believe** [feature/solution]
**Will deliver** [specific value/outcome]
**To** [target users]
**We'll know we're right when** [measurable success metric]

5.3 — Riskiest Assumption Test (RAT)

Identify the ONE assumption whose failure kills the idea:

1. List all assumptions: user behavior, technical feasibility, market demand, business model
2. Score each: Probability of being wrong (0–1) × Impact if wrong (0–1)
3. Highest score = Riskiest Assumption
4. Design cheapest possible test to validate/invalidate it before full build:
   • User interview (2–3 days)
   • Landing page / fake door test (1 week)
   • Prototype click-through (3–5 days)
   • Concierge MVP (1–2 weeks)
   • Smoke test / pre-sell (2–4 weeks)

5.4 — Build-Measure-Learn Loop

For each top idea, define the loop:

BUILD: Minimum experiment to test the assumption (not a full product)
MEASURE: One metric that proves/disproves the hypothesis
LEARN: What decision do we make if metric is met / not met?
PIVOT: If hypothesis invalidated — which alternative from Phase 3 do we try next?

Output of Phase 5:

• Problem hypothesis card per top-3 idea
• Value hypothesis card per top-3 idea
• Riskiest Assumption identified per idea
• Cheapest test designed
• Build-Measure-Learn loop defined

Phase 6: Decision & Recommendations

Goal: Present a clear, opinionated recommendation with trade-offs. Not "here are all the options" — "here's what we recommend and why."

6.1 — Top 3 Options Table

Present final shortlist as a decision table:

6.2 — Recommendation Statement

RECOMMENDED: [Option Name]

Why: [1–2 sentences on RICE + Kano + strategic fit]
Risk: [Primary risk + mitigation]
First step: [Cheapest test to validate before full commitment]
Time to validation: [Days/weeks]

6.3 — Dependency & Sequencing Check

• Does Option A depend on any existing feature/data/service not yet built?
• Can experiments run in parallel?
• What's the critical path to first validated learning?

Multi-Opportunity Discovery Mode

Selected in Phase 0.1 when the input is a raw product vision / problem statement spanning MULTIPLE distinct opportunities. This is an ADDITIONAL mode, not a replacement — every other scenario keeps the single-recommendation default of Phase 6.

When to use: the user hands off a broad vision, problem statement, or "explore this whole area" brief where several distinct, independently-shippable opportunities are expected — and each opportunity should become its own PBI downstream. This is the mode workflow-idea-to-pbi's MULTI-OPPORTUNITY DISCOVERY MODE drives.

How convergence differs (the defining difference): the default flow converges to ONE opinionated recommendation (Phase 6). This mode does NOT. Instead, the SAME convergence techniques (RICE / Kano / 2×2 from Phase 4) are used to RANK and present a map of 3–8 distinct opportunities — NOT to pick a single winner. The user then multi-selects which opportunities to develop. Picking one winner here would discard the other PBIs the downstream workflow exists to produce.

Technique flow: run Phases 1–4 as normal (problem framing → opportunity framing → ideation → convergence), but in Phase 2 lean on JTBD / Opportunity Solution Tree to surface the FULL opportunity landscape (not a single focus area), and in Phase 4 use RICE / Kano / 2×2 to SCORE and RANK every distinct opportunity rather than collapse to a top recommendation.

Output contract (must match what workflow-idea-to-pbi consumes):

• An opportunity map of 3–8 distinct, RICE-scored opportunities, ranked descending by RICE.
• Documented in plans/{plan-dir}/brainstorm-opportunity-map.md.
• Each opportunity carries: a one-line problem/value framing, RICE components (Reach × Impact × Confidence / Effort) + RICE score, and (where known) a Kano class — so each can seed a downstream PBI.

# Opportunity Map: [Vision/Problem]

| Rank | Opportunity | Problem/Value (1 line) | Reach | Impact | Confidence | Effort | RICE | Kano |
| ---- | ----------- | ---------------------- | ----- | ------ | ---------- | ------ | ---- | ---- |
| 1    | ...         | ...                    | 1000  | 2      | 0.8        | 5      | 320  | Delighter |
| 2    | ...         | ...                    | ...   | ...    | ...        | ...    | ...  | ...  |

Multi-select handoff: present the ranked map via AskUserQuestion with multiSelect: true — "Which opportunities should we develop into PBIs?". The selected opportunities feed the per-opportunity PBI loop in workflow-idea-to-pbi (each selected opportunity → idea → refine → review → story → challenge → DoR → mockup, then a final cross-PBI prioritize). Do NOT author PBIs, specs, or plans inside this skill — the discovery mode's deliverable is the scored, multi-selected opportunity map only.

Phase 7: Documentation & Handoff

Report Output

Use naming pattern from ## Naming section in injected context.

Create markdown summary report:

# Brainstorm Session Report: [Topic]

## Session Context

- Scenario: [Problem-Solving / New Product / Enhancement]
- Role: [PO / BA / Mixed]
- Date: [YYYY-MM-DD]
- Input: [Original question/problem]

## Problem Statement

[POV format]

## Root Cause Analysis

[5 Whys or Fishbone — if Problem-Solving]

## Job Stories

1. [Job Story 1]
2. [Job Story 2]
3. [Job Story 3]

## HMW Questions

1. How might we...
2. How might we...

## Opportunity Map

[OST or Lean Canvas — per scenario]

## Raw Ideas Generated

[Total count: XX ideas across SCAMPER / Crazy 8s / Impact Mapping]

## Scored Shortlist (RICE)

| Rank | Idea | RICE | Kano | Effort | Priority    |
| ---- | ---- | ---- | ---- | ------ | ----------- |
| 1    | ...  | ...  | ...  | ...    | Must Have   |
| 2    | ...  | ...  | ...  | ...    | Should Have |

## Hypothesis Cards

### Top Recommendation: [Option Name]

- Problem Hypothesis: ...
- Value Hypothesis: ...
- Riskiest Assumption: ...
- Cheapest Test: ...
- Success Metric: ...

## Decision

[Recommendation + rationale]

## Next Steps

- [ ] [First concrete action]
- [ ] [Validation test]
- [ ] [Stakeholder alignment needed]

Technique Quick Reference

Role-Specific Guidance

PO Mode (Outcome Focus)

• Lead with: desired business outcome → opportunities → experiments
• Use: OST, Impact Mapping, RICE, Build-Measure-Learn
• Ask: "What behavior change do we need to see in users?"
• Resist: jumping to features before validating the outcome

BA Mode (Requirements Focus)

• Lead with: stakeholder needs → process gaps → requirements
• Use: BABOK elicitation (interviews, workshops, document analysis), Fishbone, JTBD
• Ask: "What does the system need to do to enable that behavior?"
• Resist: over-specifying before the PO validates the opportunity

Mixed PO + BA Mode

• PO owns: problem statement, opportunity framing, prioritization, hypothesis
• BA owns: requirements elicitation, acceptance criteria, edge cases, process mapping
• Handoff point: after Phase 4 (scored shortlist) → BA writes acceptance criteria per idea

Collaboration Tools

• planner agent — research industry best practices for specific domain
• docs-manager agent — understand existing feature constraints and domain context
• WebSearch — market/competitor context for new product scenarios
• docs-seeker skill — latest documentation for external plugins/APIs
• visual analysis tooling skill — analyze visual mockups, screenshots, competitor UIs
• sequential-thinking skill — complex problem decomposition requiring structured causal chains
• web-research skill — deep market research for greenfield or competitive analysis

Scenario Cheat Sheets

Scenario A: Problem-Solving

1. POV Statement → 2. 5 Whys / Fishbone → 3. HMW Questions
→ 4. SCAMPER on current solution → 5. RICE scoring
→ 6. Problem Hypothesis + RAT → 7. Recommend + cheapest test

Scenario B: New Product

1. Job Stories (JTBD) → 2. Lean Canvas → 3. Blue Ocean ERRC
→ 4. HMW Questions → 5. Crazy 8s / Brainwriting
→ 6. Kano Classification → 7. Value Hypothesis + RAT → 8. MVP scope

Scenario C: Feature Enhancement

1. Job Stories (JTBD) → 2. Opportunity Solution Tree
→ 3. HMW Questions → 4. SCAMPER on existing feature
→ 5. Impact Mapping → 6. RICE scoring → 7. 2×2 matrix
→ 8. Value Hypothesis + RAT → 9. Recommend + next experiment

Scenario D: Multi-Opportunity Discovery

1. Job Stories (JTBD) → 2. Opportunity Solution Tree (FULL landscape, not one focus)
→ 3. HMW Questions → 4. SCAMPER → 5. RICE-score EVERY opportunity
→ 6. Rank into a 3–8-item opportunity map (do NOT pick ONE)
→ 7. Write plans/{plan-dir}/brainstorm-opportunity-map.md
→ 8. AskUserQuestion multiSelect → hand selected opportunities to the per-opportunity PBI loop

Key difference from A/B/C: converge to a RANKED MAP for multi-select, never a single recommendation. See Multi-Opportunity Discovery Mode.

Anti-Patterns to Avoid

Critical Constraints

• DO NOT implement solutions — brainstorm and advise only
• DO validate hypotheses before endorsing any approach
• DO prioritize long-term maintainability over short-term convenience
• DO consider both technical excellence and business pragmatism
• DO produce a scored, ranked shortlist — never just a flat idea list
• DO always design the cheapest validation test — RAT before full spec

Workflow Integration

After brainstorm session concludes, use AskUserQuestion to present next steps:

Multi-Opportunity Discovery handoff: when run in discovery mode, do NOT pick a single next step — instead present the ranked 3–8-item RICE opportunity map (written to plans/{plan-dir}/brainstorm-opportunity-map.md) via AskUserQuestion with multiSelect: true, then hand the selected opportunities to workflow-idea-to-pbi's per-opportunity PBI loop. workflow-idea-to-pbi consumes this opportunity map directly.

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting. This prevents context loss from long sessions.

AI Mistake Prevention — Failure modes to avoid on every task:

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done.

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