NW-DIVERGE: Structured Divergent Thinking Before Convergence

Wave: DIVERGE (between DISCOVER and DISCUSS, optional) | Agent: Flux (nw-diverger) | Command: /nw-diverge

Overview

Execute DIVERGE wave through Flux's 4-phase workflow: JTBD analysis|competitive research|structured brainstorming|taste-filtered evaluation. Transforms a validated problem into 3-5 concrete, taste-scored design directions so DISCUSS can converge on one with confidence.

DIVERGE is optional. Brownfield features with a clear direction may skip it (see skip checklist in design spec). New products and pivot decisions benefit most from structured divergence.

Interactive Decision Points

Decision 1: Work Type

Question: What type of work is this? Options:

1. New product -- no prior solution exists, full divergence needed
2. Brownfield feature -- existing product, exploring approach alternatives
3. Pivot / redesign -- existing feature being reconsidered from scratch
4. Other -- user provides custom context

Decision 2: Research Depth

Question: How deep should competitive research go? Options:

1. Lightweight -- 3 competitors, known market
2. Comprehensive -- 5+ competitors including non-obvious alternatives
3. Deep-dive -- cross-category research, adjacent markets, academic references

Prior Wave Consultation

Before beginning DIVERGE work, read SSOT and prior wave artifacts:

1. SSOT (if docs/product/ exists):
   • docs/product/jobs.yaml -- validated jobs and opportunity scores
   • docs/product/vision.md -- product vision and strategic context
2. Project context: docs/project-brief.md | docs/stakeholders.yaml (if available)
3. DISCOVER artifacts: Read docs/feature/{feature-id}/discover/ (if present)
   • wave-decisions.md -- validated assumptions and key decisions
   • problem-validation.md -- customer evidence grounding the problem

Migration gate: If docs/product/ does not exist but docs/feature/ has existing features, STOP. Guide the user to docs/guides/migrating-to-ssot-model/README.md and complete the migration first. If greenfield, DIVERGE will bootstrap docs/product/jobs.yaml with the validated job.

READING ENFORCEMENT: You MUST read every file listed in Prior Wave Consultation above using the Read tool before proceeding. After reading, output a confirmation checklist. Do NOT skip files that exist -- skipping causes options disconnected from evidence.

Agent Invocation

@nw-diverger

Execute *diverge for {feature-id}.

Context Files: see Prior Wave Consultation above + project context files.

Configuration:

• work_type: {Decision 1}
• research_depth: {Decision 2}
• output_directory: docs/feature/{feature-id}/

SKILL_LOADING: Before starting work, load your skill files using the Read tool from ~/.claude/skills/nw-{skill-name}/SKILL.md. Skills encode your methodology -- without them you operate with generic knowledge only.

At the start of execution, create these tasks using TaskCreate and follow them in order:

1. JTBD Analysis — Load jtbd-analysis skill. Extract and elevate the job from the raw request or DISCOVER evidence. Produce job statements (functional + emotional + social) and ODI outcome statements. Gate: job at strategic or physical level (not tactical), minimum 3 ODI outcome statements produced.
2. Competitive Research — Invoke nw-researcher sub-agent for evidence-grounded competitive research. Map how existing products serve the validated job. Identify non-obvious alternatives. Gate: 3+ real competitors named, at least one non-obvious alternative, evidence quality confirmed.
3. Brainstorming — Load brainstorming skill. Frame HMW question, apply SCAMPER lenses, generate structurally diverse options. Gate: 6 options generated with diversity confirmed (mechanism, assumption, and cost structure differ across options).
4. Taste Evaluation — Load taste-evaluation skill. Apply DVF filter, score surviving options on 4 taste criteria with locked weights, produce weighted ranking and recommendation with dissenting case. Gate: all surviving options scored on all 4 criteria, recommendation traceable to scoring matrix, dissenting case documented.
5. Peer Review — Invoke nw-diverger-reviewer (Prism) to validate all 5 dimensions. Revise if needed (max 2 iterations). Gate: reviewer approval confirmed, handoff accepted by nw-product-owner.

Success Criteria

• Job extracted at strategic or physical level (not tactical, not a feature description)
• Minimum 3 ODI outcome statements produced
• 3+ real competitors researched, at least one non-obvious alternative
• 6 structurally diverse options generated (different mechanism, assumption, cost)
• All surviving options scored on all 4 taste criteria with locked weights
• Recommendation traceable to scoring matrix (no "feels right" overrides)
• Dissenting case documented for second-place option
• Peer review approved by nw-diverger-reviewer
• Handoff accepted by nw-product-owner (DISCUSS wave)

Next Wave

Handoff To: nw-product-owner (DISCUSS wave) Deliverables: recommendation.md with explicit decision statement + supporting DIVERGE artifacts

Wave Decisions Summary

Before completing DIVERGE, produce (or append to) docs/feature/{feature-id}/wave-decisions.md:

# DIVERGE Decisions -- {feature-id}

## Key Decisions
- [D1] {decision}: {rationale} (see: {source-file})

## Job Summary
- Validated job: {job statement at strategic/physical level}
- ODI outcomes: {count} outcome statements

## Options Evaluated
- {count} options generated, {count} survived DVF filter
- Recommended: {option name} -- {one-line rationale}
- Dissent: {second-place option} -- {why it might be better under different assumptions}

## SSOT Updates
- jobs.yaml: {created|updated} with job JOB-{NNN}

SSOT Update

After producing feature-level artifacts, update the product-level SSOT:

1. Jobs SSOT: Create or update docs/product/jobs.yaml with the validated job from Phase 1. Add changelog entry referencing this feature-id.
2. If docs/product/ does not exist, create the directory. This is the SSOT bootstrap.

SSOT files use schema_version and changelog fields. See canonical schema in the design spec.

Expected Outputs

Feature delta (in docs/feature/{feature-id}/)

  recommendation.md             (top 3 options, dissenting case, decision for DISCUSS)
  wave-decisions.md             (DIVERGE section appended)

Internal artifacts (in docs/feature/{feature-id}/diverge/)

  job-analysis.md               (validated job + ODI outcome statements)
  competitive-research.md       (prior art, competitor analysis, non-obvious alternatives)
  options-raw.md                (all generated options, unfiltered, no evaluation)
  taste-evaluation.md           (DVF filter, locked weights, scoring matrix)
  review.yaml                   (peer review result from nw-diverger-reviewer)

SSOT updates (in docs/product/)

  jobs.yaml                     (created or updated with validated job + changelog entry)

Examples

Example 1: New product divergence

/nw-diverge notification-system

DISCOVER artifacts present with validated problem. Flux reads problem-validation.md, extracts job ("minimize likelihood of developers missing critical failure signals"), researches 5 notification tools including non-obvious alternatives (ambient light signals, IDE annotations), generates 6 structurally diverse options, scores with taste evaluation, recommends proactive push with Slack integration. Updates jobs.yaml with validated job.

Example 2: Brownfield feature without DISCOVER

/nw-diverge rate-limiting

No DISCOVER artifacts. Flux works from project-brief.md and direct conversation. Extracts job via 5 Whys from "we need rate limiting" to strategic level. Creates docs/product/jobs.yaml (SSOT bootstrap). Proceeds