Outcome Roadmap Expert

The agent transforms output-based roadmaps ("build feature X") into outcome-driven roadmaps ("enable customers to achieve Y") using the "so what?" technique and Now/Next/Later framing. It produces roadmaps that communicate strategy and measurable impact, not just feature lists and dates.

Core Capabilities

• Output → outcome transformation — applies the formula "Enable [segment] to [outcome] so that [impact]" via a "so what?" chain that drills from feature to business metric.
• Now/Next/Later classification — sorts initiatives into horizons whose detail and commitment level match certainty.
• Metric definition — primary, secondary, and counter-metrics for Now/Next items.
• Dependency capture — technical, organizational, and market prerequisites per item.
• Stakeholder-ready output — text, JSON, and markdown reports grouped by horizon for alignment review.

When to Use

• Converting a feature-list / date-driven roadmap into outcome-driven format.
• Communicating product strategy to executives or customers.
• Running quarterly planning and aligning teams around impact rather than deliverables.
• Anchoring roadmap items to customer value and OKRs.

Clarify First

Before transforming the roadmap, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Customer segment + business impact per item — fills the "Enable [segment] to [outcome] so that [impact]" statement; without it the tool only emits placeholder templates
• Target quarter per initiative — drives Now/Next/Later horizon placement and the detail/commitment level
• Initiative type — feature / improvement / infrastructure drives the strategic-question and metric suggestions
• Success metric per Now/Next item — the primary/secondary/counter-metrics; Later items intentionally stay metric-light to avoid false precision

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

python scripts/roadmap_transformer.py --input roadmap.json            # transform a roadmap
python scripts/roadmap_transformer.py --input roadmap.json --format markdown
python scripts/roadmap_transformer.py --demo                          # run on built-in demo data

Each input initiative needs title, description, quarter (format "Q[1-4] YYYY"), and type (feature/improvement/infrastructure). The tool emits outcome-statement templates — fill the placeholders with real customer and business data.

References

• references/outcome-roadmap-workflow.md — read this when transforming a roadmap: the 6-step workflow with validation checkpoints, the "so what?" technique, Now/Next/Later detail levels, a full worked example, why output roadmaps fail, output structure, tool flags, troubleshooting, and success criteria.
• references/outcome-roadmap-guide.md — read this for the deeper guide: output-vs-outcome comparison, outcome formulas, and stakeholder communication strategies.
• references/red-flags.md — read this to spot the common ways outcome roadmaps go wrong (false precision, mechanical templates, too many Now items) before sharing.
• assets/outcome_roadmap_template.md — roadmap document template with Now/Next/Later sections.

Scope & Limitations

In Scope: transforming output-based feature lists into outcome-driven items, Now/Next/Later classification by quarter-to-current-date distance, "so what?" chain generation, strategic-question and metric suggestions by initiative type, markdown/text/JSON report output grouped by horizon.

Out of Scope: feature prioritization or scoring (execution/prioritization-frameworks/), sprint-level planning or capacity allocation (scrum-master/), product strategy or vision definition (roadmaps communicate strategy, they don't create it), cross-team dependency management (program-manager/).

Important Caveats: outcome roadmaps require a cultural shift — teams used to date-driven lists need coaching on commitment levels; the tool generates outcome-statement templates, not finished outcomes; Later items intentionally lack detailed metrics, and adding false precision undermines credibility.

Integration Points