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Dogfooding

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cnfeat
dogfooding

Help users implement effective dogfooding practices. Use when someone is trying to get their team to use their own product, designing internal usage programs, or building user empathy through personal product use.

Overview

Publishercnfeat
Repositorytop-pm-skills
Skill namedogfooding
Stars
55
Forks
6
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • 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 Dogfooding 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/dogfooding
  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 Dogfooding 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 Dogfooding 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 Dogfooding 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.

Dogfooding

Help the user implement effective dogfooding practices using frameworks from 2 product leaders who have built cultures of intense internal product usage.

How to Help

When the user asks for help with dogfooding:

  1. Assess current state - Determine how much the team currently uses their own product
  2. Identify the gap - Find where team members lack firsthand experience with user pain points
  3. Design the program - Help create systems that make dogfooding natural and required
  4. Measure impact - Track how dogfooding improves product decisions

Core Principles

Require team members to become users

Maya Prohovnik: "I am constantly yelling at my product team who do not have podcasts and being like, I really don't think that you can build the right things. If they talk to users all the time, they see the data, but all of them, once they finally start doing their podcast, they're like, I get it." Force the entire team to become creators/users to deeply understand user pain points.

Use the tool intensely every day

Michael Truell: "From the very start, our product development process was really about dogfooding, and using the tool intensely every day. And we never wanted to ship anything that wasn't useful to us." 'Intense' daily use provides the realism needed to build useful features, especially for AI products.

Questions to Help Users

  • "How often does each team member actually use the product as a real user?"
  • "What's preventing your team from being heavy users of your own product?"
  • "What would it take to make internal usage feel natural rather than forced?"
  • "Are you learning different things from dogfooding vs. customer feedback?"
  • "How quickly do you feel the pain of bugs or friction when using your own product?"

Common Mistakes to Flag

  • Superficial testing - Using the product only in demo mode, not for real work
  • Delegating to QA - Relying on testers instead of requiring team members to be real users
  • Ignoring non-obvious use cases - Only testing the happy path rather than edge cases
  • Not acting on findings - Dogfooding without a process to fix discovered issues
  • Excluding non-product roles - Only having engineers dogfood when designers and PMs should too

Deep Dive

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

Related Skills

  • Writing North Star Metrics
  • Defining Product Vision
  • Prioritizing Roadmap
  • Setting OKRs & Goals

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 Dogfooding AI skill do?

Help users implement effective dogfooding practices. Use when someone is trying to get their team to use their own product, designing internal usage programs, or building user empathy through personal product use.

Why use Dogfooding on TypingMind?

Because you install it once and use it with any model. Dogfooding 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 Dogfooding 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/dogfooding. 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 Dogfooding?

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 Dogfooding?

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

Is the Dogfooding 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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