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Startup Pivoting

Community
cnfeat
startup-pivoting

Help users decide when and how to pivot their startup. Use when someone is questioning their current direction, seeing poor traction, considering a major strategy change, or stuck in the pre-PMF stage.

Overview

Publishercnfeat
Repositorytop-pm-skills
Skill namestartup-pivoting
Stars
55
Forks
6
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Startup Pivoting 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/cnfeat/top-pm-skills/tree/main/参考skill/lenny-skills-main%20(2)/lenny-skills-main/skills/startup-pivoting
  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.

Use it in TypingMind

Enable Startup Pivoting 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 Startup Pivoting 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 Startup Pivoting 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.

Startup Pivoting

Help the user decide when and how to pivot their startup using frameworks and insights from 2 product leaders.

How to Help

When the user asks for help with pivoting:

  1. Assess the current state - Ask about their traction, how long they've been trying, and what they've learned
  2. Evaluate if possibilities are exhausted - Determine if they've truly tried everything or just one version of the idea
  3. Challenge pivot magnitude - Most founders pivot too little; help them consider if they need a 200% pivot, not 10%
  4. Apply the Four Ps framework - Evaluate changes across Problem, Persona, Product, and Positioning

Core Principles

Have you exhausted the possibilities?

Stewart Butterfield: "The decision is about have you exhausted the possibilities?" A pivot should come from rational analysis of what's been tried, not emotional attachment to a failing idea. Create distance between yourself and the current approach to evaluate honestly.

Most pivots are too small

Todd Jackson: "Most founders do a 10% pivot, and what they need to be doing is a 200% pivot." When stuck in pre-PMF, small adjustments rarely break through. Consider whether you need to fundamentally change your approach rather than tweak the existing one.

Use the Four Ps framework

Evaluate pivots across four dimensions: Problem (are you solving the right problem?), Persona (are you targeting the right customer?), Product (is your solution the right approach?), and Positioning (are you framing this correctly?). Often the issue is not one but a combination.

Maintain rational distance

Emotional attachment to an idea can prevent founders from seeing clearly. The best pivot decisions come from treating your company like an outside investor would evaluate it.

Questions to Help Users

  • "What have you tried so far, and what did you learn from each attempt?"
  • "If you were an outside investor looking at this company, what would you conclude?"
  • "Is this a tweak to your current approach or a fundamental rethink?"
  • "Which of the Four Ps (Problem, Persona, Product, Positioning) might be wrong?"
  • "What would a 200% pivot look like compared to what you're considering?"
  • "Have you truly exhausted the possibilities, or just gotten tired of trying?"

Common Mistakes to Flag

  • Pivoting too small - Making 10% changes when 200% changes are needed to find PMF
  • Emotional attachment - Continuing because of sunk cost rather than evidence of potential
  • Pivoting too quickly - Changing direction before truly learning why the current approach isn't working
  • Only changing one P - Often multiple dimensions (problem, persona, product, positioning) need to change together
  • Pivoting without a thesis - Random pivots don't help; you need a specific hypothesis about what was wrong

Deep Dive

For all 2 insights from 2 guests, see references/guest-insights.md

Related Skills

  • Startup Ideation
  • Measuring Product-Market Fit
  • Defining Product Vision
  • Customer Research

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Startup Pivoting AI skill do?

Help users decide when and how to pivot their startup. Use when someone is questioning their current direction, seeing poor traction, considering a major strategy change, or stuck in the pre-PMF stage.

Why use Startup Pivoting on TypingMind?

Because you install it once and use it with any model. Startup Pivoting 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 Startup Pivoting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cnfeat/top-pm-skills/tree/main/参考skill/lenny-skills-main%20(2)/lenny-skills-main/skills/startup-pivoting. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Startup Pivoting?

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 Startup Pivoting?

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

Is the Startup Pivoting AI skill free?

Yes. It is published on GitHub by cnfeat 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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