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Roadmap Planning

Community
shawnpang
roadmap-planning

When the user needs to organize product initiatives into a prioritized, time-sequenced plan with outcomes and dependencies.

Overview

Publishershawnpang
Repositorystartup-founder-skills
Skill nameroadmap-planning
Stars
368
Forks
43
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by shawnpang on GitHub. Read the source before you install it.

Installation

Install the Roadmap Planning AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/shawnpang/startup-founder-skills/tree/main/skills/roadmap-planning
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/shawnpang/startup-founder-skills.git /tmp/startup-founder-skills
mkdir -p .claude/skills
cp -r /tmp/startup-founder-skills/skills/roadmap-planning .claude/skills/roadmap-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Roadmap Planning in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Roadmap Planning on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Roadmap Planning is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Roadmap Planning

When to Use

Activate when a founder or PM has a set of product ideas, feature requests, or strategic bets and needs to organize them into a coherent roadmap. This includes situations like "help me plan our Q2 roadmap," "prioritize this feature backlog," "what should we build next," or "create a roadmap for the next 6 months." Also activate when an existing roadmap needs restructuring from output-focused (feature lists) to outcome-focused (customer and business impact).

Context Required

  • From startup-context: company stage, team size and composition, current product state, business model, key metrics, strategic goals, company OKRs.
  • From the user: current roadmap or list of candidate initiatives, known customer needs, resource constraints, hard deadlines, strategy documents or company objectives for alignment, and any committed work already in progress.

Workflow

  1. Gather the current state -- Collect the existing roadmap or feature list. If the user provides strategy documents or company objectives, review them to understand how the roadmap should align with broader goals.
  2. Transform outputs to outcomes -- For each initiative, ask: What customer problem are we solving? What business metric will improve? Is there a better way to achieve the same outcome? Rewrite each item as an outcome statement.
  3. Apply outcome statement format -- Use: "Enable [customer segment] to [desired customer outcome] so that [business impact]." Every roadmap item must pass this test.
  4. Score and prioritize -- Apply RICE scoring (Reach, Impact, Confidence, Effort) to rank initiatives. Adjust for strategic alignment with company objectives and OKRs.
  5. Identify dependencies and sequencing -- Map which initiatives depend on others. Note technical, data, design, and business dependencies.
  6. Sequence into time horizons -- Place initiatives into Now (0-6 weeks), Next (6-12 weeks), and Later (12+ weeks). Use flexible release windows (quarters, not specific dates) for Later items.
  7. Validate capacity -- Cross-check the plan against team capacity. A roadmap that requires 3x your engineering bandwidth is a wishlist, not a plan.
  8. Add strategic context -- Document how outcomes align with company strategy, key assumptions about customer needs, and review cadence.

Output Format

Strategic Context

One paragraph restating the company's current strategic priorities and how this roadmap serves them. Include key assumptions about customer needs.

Outcome-Focused Roadmap

Now (0-6 weeks) -- Committed
InitiativeOutcome StatementKey MetricOwnerDependencies
Original feature/projectEnable [segment] to [outcome] so that [impact]Metric + targetTeamList
Next (6-12 weeks) -- High Confidence

Same table format. Items here are planned but may shift based on learnings from Now.

Later (12+ weeks) -- Exploratory

Same table format. Items here are directional. Flexible time windows, no owners assigned yet.

Not Doing (and Why)

Initiatives explicitly excluded with reasoning. This section is as important as the roadmap itself.

Dependency Map

Visual or textual representation of which initiatives block or enable others.

Capacity Check

Summary of estimated effort vs. available capacity per time horizon.

Key Assumptions and Risks

Numbered list of what must be true for this roadmap to succeed.

Frameworks & Best Practices

  • Outcomes over outputs. "Build advanced search filters" is an output. "Enable customers to find products 50% faster through intuitive discovery" is an outcome. Output-focused roadmaps create false precision and misalign teams around features rather than results.
  • The outcome statement format. "Enable [customer segment] to [desired customer outcome] so that [business impact]." This forces clarity on who benefits, what changes, and why it matters.
  • The "So What?" test. If you cannot articulate the outcome a feature drives, keep asking "So what?" until you reach real customer or business value. Multiple outputs may achieve one outcome -- focus on the outcome.
  • RICE scoring.
    • Reach: How many users/accounts will this affect per quarter?
    • Impact: On a scale of 0.25 (minimal) to 3 (massive), how much will this move the target metric?
    • Confidence: As a percentage, how sure are you about reach and impact estimates?
    • Effort: Person-weeks required.
    • Score: (Reach x Impact x Confidence) / Effort.
  • Three-horizon structure. Now/Next/Later avoids the false precision of Gantt charts. Commit to Now, plan for Next, explore Later.
  • Outcome roadmaps are resilient to change. Because they describe the "why" rather than the "what," they survive strategy pivots and new information better than feature roadmaps.
  • Say no explicitly. A roadmap is defined as much by what it excludes. Maintain a "Not Doing" list and share the reasoning.
  • Align with OKRs. Every outcome statement should map to a company or product OKR. Orphan initiatives signal misalignment.
  • Revisit quarterly. Roadmaps older than one quarter are stale. Build in review cadences.
  • Stage-appropriate planning.
    • Pre-PMF: Roadmaps should be 4-6 week sprints focused on learning. No 12-month plans.
    • Post-PMF: Quarterly roadmaps tied to OKRs. Balance growth features with infrastructure and debt.
    • Scaling: Semi-annual roadmaps with cross-team coordination. Dependencies become the hard problem.
  • Avoid roadmap theater. Do not create elaborate roadmaps to appease stakeholders if the team lacks the capacity or conviction to execute.

Related Skills

  • prd-writing -- Once an initiative is committed in the Now horizon, write a PRD to spec it out.
  • mvp-scoping -- Before placing an initiative on the roadmap, scope its MVP to get a realistic effort estimate.
  • user-research-synthesis -- Use customer insights to validate which outcomes matter most to your target segments.

Examples

Example 1: Output-to-outcome transformation

User: "Our Q2 plan says: build advanced search filters, implement AI recommendations, redesign dashboard. Help me turn this into an outcome roadmap."

Good output excerpt:

Transformation:

  • Output: "Build advanced search filters" --> Outcome: "Enable customers to find products 50% faster through intuitive discovery"
  • Output: "Implement AI recommendations" --> Outcome: "Increase average order value by 20% through personalized discovery"
  • Output: "Redesign dashboard" --> Outcome: "Help operators monitor all systems with 80% reduction in dashboard load time"

Each outcome is now testable, measurable, and opens the door to alternative solutions beyond the originally specified feature.

Example 2: Feature backlog to roadmap

User: "Here's our feature backlog: Slack integration, SSO, reporting dashboard, mobile app, API v2, onboarding wizard. Help me build a roadmap."

Good output excerpt:

Now (0-6 weeks): | Onboarding Wizard | Enable new signups to reach first value within 10 minutes so that activation rate increases from 35% to 55% | Activation rate | Growth team | None |

Not Doing This Quarter:

  • Mobile app -- Current usage data shows <5% of sessions are mobile. Revisit when mobile demand signal is stronger. Asking "So what?" reveals no compelling customer outcome today.

Frequently asked questions

What does the Roadmap Planning AI skill do?

When the user needs to organize product initiatives into a prioritized, time-sequenced plan with outcomes and dependencies.

Why use Roadmap Planning on TypingMind?

Because you install it once and use it with any model. Roadmap Planning is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Roadmap Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shawnpang/startup-founder-skills/tree/main/skills/roadmap-planning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Roadmap Planning?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Roadmap Planning?

As many as you like. As long as a model supports skills, you can use Roadmap Planning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Roadmap Planning AI skill free?

Yes. It is published on GitHub by shawnpang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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