Beachhead Mapping

Community

Productfculty-aipm

beachhead-mapping

Use this skill when the user asks about "beachhead market", "initial market", "where to start", "narrowing our target market", "first customer segment", "go narrow first", "crossing the chasm strategy", "wedge strategy", "who to focus on first", or wants to identify the specific niche to own before expanding. Also use this skill when the user is unsure which segment to prioritize among several options.

Overview

Publisher	Productfculty-aipm
Repository	`PM-Copilot-by-Product-Faculty`
Skill name	`beachhead-mapping`
Stars	80
Forks	34
Bundled files	Instructions only
Links	Skill source Repository Homepage

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 Productfculty-aipm on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/beachhead-mapping
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/beachhead-mapping

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/beachhead-mapping .claude/skills/beachhead-mapping

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Beachhead Mapping 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 Beachhead Mapping 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 Beachhead Mapping 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.

Beachhead Market Mapping

You are helping the user identify the optimal beachhead market — the specific niche they can win decisively before expanding. The beachhead is not the total addressable market; it's the first piece of it that can be captured with current resources.

Frameworks: Geoffrey Moore (Crossing the Chasm), Lenny Rachitsky (B2B go-to-market), April Dunford (segment-first positioning).

Key principle: Own one niche completely before expanding. A 10x advantage in a small market beats a 1.5x advantage in a large one.

Step 1 — Load Context

Read memory/user-profile.md for product stage, business model, and current bets. Read context/product/personas.md for existing persona definitions. Understand: are they pre-PMF (finding the market) or post-PMF (expanding)?

Step 2 — Identify Candidate Segments

List all plausible user segments that could be the beachhead. For each:

Who specifically? (Job title, company type, company size, use case)
What is their specific problem that we solve?
How severe is their problem today?
What do they currently use to solve it?

If the list is too generic ("small businesses"), help decompose into more specific sub-segments.

Step 3 — Beachhead Scoring

Score each candidate segment across 5 dimensions (1–5):

1. Pain severity: How acute is the problem for this segment? (5 = blocking; 1 = mildly annoying) 2. Reachability: How easy is it to find and reach these users? (5 = concentrated community; 1 = diffuse) 3. Willingness to pay: Is this segment used to paying for solutions to this problem? (5 = enterprise budget; 1 = expects free) 4. Reference value: Will winning this segment open doors to adjacent segments? (5 = highly prestigious or connective; 1 = isolated) 5. Competitive intensity: How crowded is this segment with established solutions? (5 = wide open; 1 = dominated by incumbents)

Rank segments by total score. The highest-scoring segment is the beachhead candidate.

Step 4 — Beachhead Profile

For the top-scoring segment, write a detailed beachhead profile:

Segment definition: [Specific description — job title, company stage, use case trigger, geography if relevant] Problem intensity: [How bad is their specific problem, and what evidence supports this?] Current hire: [What are they using today? What's wrong with it?] Why us: [What do we offer this segment that they can't get elsewhere?] Access point: [How do we reach them? Where are they? What communities, events, publications?] Success metric for ownership: [What would it look like to "own" this segment? e.g., 30% of all [segment type] in [geography] using the product] Expansion path: [Which adjacent segment do we tackle after owning this one, and why does winning the beachhead make that easier?]

Step 5 — The Beachhead Test

Before committing, stress-test the beachhead:

Can we talk to 10 people in this segment in the next 2 weeks?
Can we build a solution for this segment without over-engineering for everyone?
If we own this segment, does it give us a reference case that would attract the next segment?
Is this segment large enough to generate real revenue, but small enough to win decisively?

Step 6 — Output

Produce:

Ranked candidate segments with scoring rationale
Full beachhead profile for the top segment
Expansion roadmap: beachhead → adjacent segment 1 → adjacent segment 2
What winning the beachhead looks like (success criteria)
The one assumption to validate first before committing to this beachhead

Frequently asked questions

What does the Beachhead Mapping AI skill do?

Why use Beachhead Mapping on TypingMind?

Because you install it once and use it with any model. Beachhead Mapping 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 Beachhead Mapping in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/beachhead-mapping. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Beachhead Mapping?

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 Beachhead Mapping?

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

Is the Beachhead Mapping AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Beachhead Market Mapping

Step 1 — Load Context

Step 2 — Identify Candidate Segments

Step 3 — Beachhead Scoring

Step 4 — Beachhead Profile

Step 5 — The Beachhead Test

Step 6 — Output

Frequently asked questions

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