JTBD Workflow Selection

SkillDev tools

JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the JTBD Workflow Selection skill

What this skill tells your AI

The instructions your AI receives, as published by nwave-ai/nwave in nWave/skills/nw-jtbd-workflow-selection/SKILL.md and read by ahel’s review.

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
StepPurpose
research(Optional) Gather domain knowledge before requirements
discussGather requirements -- you don't know what's needed yet
designArchitecture decisions, technology selection
diagram(Optional) Visualize architecture for stakeholders
distillDefine acceptance tests -- what does "done" look like?
baselineMeasure starting point for tracking improvement
roadmapComprehensive plan while context is fresh
splitBreak into atomic, self-contained tasks
executeDo each task with clean context
reviewQuality 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

JobYou Know What?Sequence
GreenfieldNo[research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review
BrownfieldYes[research] -> baseline -> roadmap -> split -> execute -> review
RefactoringPartially[research] -> baseline -> mikado/roadmap -> split -> execute -> review
Bug FixYes (symptom)[research] -> root-why -> develop -> deliver
ResearchNoresearch -> (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-PatternProblemSolution
Skip researchDecisions without evidenceResearch when unfamiliar with domain
Skip baselineOptimize the wrong thingAlways baseline before roadmap
Monolithic tasksContext degradationUse split for atomic tasks
Skip reviewQuality issues propagateReview before each execute
Architecture before measurementOver-engineeringBaseline identifies quick wins first
Forward references in tasksTasks not self-containedEach task must have all context embedded

Common Workflow Recipes

SituationEntry PointKey Characteristic
New feature on existing codebasebaseline (skip discovery)Existing system, new capability
Performance optimizationbaseline (type: performance)Measurement-first
Legacy system modernizationresearch + root-why + baselineDeep understanding first
Quick bug fixroot-why + develop + deliverMinimal sequence
Pure research taskresearchOutput informs next job selection
Data-heavy projectresearch + baselineSpecialist agent involvement

Job Categories Summary

CategoryCore Job
UnderstandingKnow what to build and why
PlanningBreak work into safe, trackable chunks
ExecutingDo work without context degradation
ValidatingCatch issues early with quality gates
CommunicatingShare understanding via diagrams and docs
InvestigatingFind 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.

Signals

GitHub stars
610
Forks
64
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
nw-jtbd-workflow-selection
Source
github.com/nwave-ai/nwave