nwave-ai/nw-jtbd-workflow-selection

JTBD Workflow Selection

Classify incoming work by job type and recommend the appropriate nWave workflow entry point. Use during Phase 1 (GATHER) to triage before crafting stories.

ODI Two-Phase Framework

Determine which phase applies before proceeding.

Phase 1: Discovery -- when you do not know what to build

[research] --> discuss --> design --> distill
    |            |           |          |
GATHER        WHAT are    HOW should  WHAT does
evidence      the needs?  it work?    "done" look like?

Phase 2: Execution Loop -- when you know what needs to change

[research] --> baseline --> roadmap --> split --> execute --> review
    |            |            |           |          |          |
GATHER        MEASURE      PLAN it     BREAK it   DO each    CHECK
evidence      first        completely  into atoms  task       quality
                                          |
                              <-----------+ (loop per task)

Key insight: research is a cross-wave capability invocable at any point for evidence-based decisions.

When to Skip Discovery

Skip discovery and enter execution loop directly when ALL hold:

• User already understands the problem domain
• Problem is identified and scoped
• No stakeholder alignment needed
• User can articulate what "done" looks like

If any fail, start with discovery (DISCUSS wave).

Five Job Types

Job 1: Build Something New (Greenfield)

"I need to create something that doesn't exist yet"

[research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review

| Step | Purpose | |------|---------| | research | (Optional) Gather domain knowledge before requirements | | discuss | Gather requirements -- you don't know what's needed yet | | design | Architecture decisions, technology selection | | diagram | (Optional) Visualize architecture for stakeholders | | distill | Define acceptance tests -- what does "done" look like? | | baseline | Measure starting point for tracking improvement | | roadmap | Comprehensive plan while context is fresh | | split | Break into atomic, self-contained tasks | | execute | Do each task with clean context | | review | Quality gate before proceeding |

Job 2: Improve Existing System (Brownfield)

"I know what needs to change in our system"

[research] -> baseline -> roadmap -> split -> execute -> review (repeat)

Skip discovery: system understood and problem identified. Baseline is blocking gate -- measure current state before planning. Prevents "optimizing the wrong thing."

Job 3: Complex Refactoring

"Code works but structure needs improvement"

Simple refactoring:

[root-why] -> mikado -> refactor (incremental)

Complex refactoring with tracking:

[research] -> baseline -> roadmap (methodology: mikado) -> split -> execute -> review

Mikado Method explores dependencies before committing. Reversible at every step.

Job 4: Investigate and Fix Issue

"Something is broken and I need to find why"

[research] -> root-why -> develop -> deliver

Minimal sequence -- focused intervention only.

Job 5: Research and Understand

"I need to gather information before deciding"

research -> [decision point: which job to pursue next]

No execution -- pure information gathering feeding into other jobs.

Quick Reference Matrix

| Job | You Know What? | Sequence | |-----|---------------|----------| | Greenfield | No | [research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review | | Brownfield | Yes | [research] -> baseline -> roadmap -> split -> execute -> review | | Refactoring | Partially | [research] -> baseline -> mikado/roadmap -> split -> execute -> review | | Bug Fix | Yes (symptom) | [research] -> root-why -> develop -> deliver | | Research | No | research -> (output informs next job) |

Items in [brackets] are optional. Cross-wave commands (usable anytime): research, diagram, root-why, git.

Baseline Type Selection

When workflow includes a baseline step, advise on which type to create.

Performance Optimization

Use when improving speed, reducing resource usage, or optimizing throughput. Required: timing measurements with breakdown | bottleneck ranking | target metrics with evidence | quick wins identified.

Process Improvement

Use when fixing workflow issues, preventing incidents, or improving reliability. Required: incident references or failure modes | simplest alternatives considered (with why insufficient).

Feature Development

Use when building new capabilities (greenfield or brownfield). Required: current state analysis | requirements source and validation.

Workflow Anti-Patterns

Operate at project/feature level, distinct from story-level anti-patterns in leanux-methodology skill.

| Anti-Pattern | Problem | Solution | |--------------|---------|----------| | Skip research | Decisions without evidence | Research when unfamiliar with domain | | Skip baseline | Optimize the wrong thing | Always baseline before roadmap | | Monolithic tasks | Context degradation | Use split for atomic tasks | | Skip review | Quality issues propagate | Review before each execute | | Architecture before measurement | Over-engineering | Baseline identifies quick wins first | | Forward references in tasks | Tasks not self-contained | Each task must have all context embedded |

Common Workflow Recipes

| Situation | Entry Point | Key Characteristic | |-----------|------------|-------------------| | New feature on existing codebase | baseline (skip discovery) | Existing system, new capability | | Performance optimization | baseline (type: performance) | Measurement-first | | Legacy system modernization | research + root-why + baseline | Deep understanding first | | Quick bug fix | root-why + develop + deliver | Minimal sequence | | Pure research task | research | Output informs next job selection | | Data-heavy project | research + baseline | Specialist agent involvement |

Job Categories Summary

| Category | Core Job | |----------|----------| | Understanding | Know what to build and why | | Planning | Break work into safe, trackable chunks | | Executing | Do work without context degradation | | Validating | Catch issues early with quality gates | | Communicating | Share understanding via diagrams and docs | | Investigating | Find truth before acting |

For deep opportunity analysis with ODI scoring, defer to product-discoverer agent. Product-owner applies simpler prioritization (MoSCoW, Value/Effort) for story-level ordering -- see leanux-methodology skill.