Retention Engagement logo

Retention Engagement

OrganizationPopular
RefoundAI
retention-engagement

Help users identify the drivers of long-term retention and implement behavioral mechanics that keep customers coming back. This guide focuses on measuring the survival curve of users and optimizing the product environment for high frequency usage.

Overview

PublisherRefoundAI
Repositorylenny-skills
Skill nameretention-engagement
Stars
1.4K
Forks
175
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Retention Engagement 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/RefoundAI/lenny-skills/tree/main/skills/retention-engagement
  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/RefoundAI/lenny-skills.git /tmp/lenny-skills
mkdir -p .claude/skills
cp -r /tmp/lenny-skills/skills/retention-engagement .claude/skills/retention-engagement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Retention Engagement 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 Retention Engagement 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 Retention Engagement 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.

Retention and Engagement Mastery

Build sustainable growth by embedding products into workflows and creating compounding user value.

Help the user with retention and engagement mastery using insights from 11 guests and posts across Lenny's Podcast and Newsletter.

How to Help

  1. Define metrics - Guide the user in identifying their specific activation milestones and setting up cohort-based retention tracking.
  2. Audit friction - Analyze the onboarding process and core user flows to eliminate technical and mental hurdles that cause early drop-off.
  3. Design habits - Suggest psychological mechanics like streaks, loss aversion, or mounting value to increase switching costs.
  4. Benchmark performance - Compare current churn and retention rates against industry-specific 'Good' and 'Great' standards to prioritize interventions.

Core Principles

Retention before monetization

Albert Cheng: "User retention is gold for consumer subscription companies. If you don't retain your users, then a lot of the onus is on getting them to pay on day one."

Prioritize a foundation of high user retention over aggressive early monetization to ensure sustainable long term growth.

Onboarding as a retention driver

Crystal W: "Well, based on our data about a third of people will consider switching to another company after just one bad experience during onboarding. So if your CSV importer doesn't work right, which is super common, considering customer files are chalked full of unexpected data and formatting, they'll leave."

Treat the first experience as the most critical point for retention because users are prone to abandon a product at the first sign of friction.

Survival curve measurement

Dan Hockenmaier: "Second would be retention. So at what rate are these customers activating? And then have some kind of basic monthly retention curve. So how long are they staying around? What's the survival rate in each of these? And those kind of stack over time."

Effective retention management requires tracking the long term survival curve of user cohorts rather than just high level active user counts.

Strategic loss aversion

Jackson Shuttleworth: "Streaks is the most impactful feature. We have, right now, over 9 million users with a year plus streak. If you look at the numbers, I think it's been our biggest growth lever. What Duolingo really focuses on is, how do we help users build habits around language learning?"

Use mechanics like streaks to create a sense of progress that users want to protect, providing a powerful motivation to return daily.

The churn ceiling

Jason Cohen: "There's a maximum ceiling of how big you could ever be thanks to cancellations. And when you know what that number is, it's much more real and visceral and scary."

Acknowledge that high churn creates a mathematical limit on business size that no amount of acquisition can solve.

Mounting loss

Sarah Tavel: "The test for me, of whether you're building a product that has the ingredients to create a retentive product on a micro level, just at the user level, is that the product should get better the more you use it, and you'll have more to lose by leaving it."

Ensure the product becomes more valuable with every use, making the cost of abandoning the platform higher over time.

Questions to Help Users

  • "What is the single action a user must take to realize the core value of your product?"
  • "At what specific point in time does your cohort retention curve usually flatten out?"
  • "Does your product provide utility to a single player before a network or team is established?"
  • "What valuable data or progress would a user lose if they stopped using your product today?"
  • "Is your monthly logo churn rate currently above or below the critical 3 percent threshold?"
  • "Are your retention metrics currently masking the behavior of free users by blending them with paid customers?"

Common Mistakes to Flag

  • Relying on acquisition to fix churn - Marketing cannot overcome the mathematical growth ceiling created by a high cancellation rate.
  • Using noise events for activity - Broad metrics like app opens or screen views inflate active user counts without reflecting genuine value delivery.
  • Ignoring involuntary churn - Failing to distinguish between payment failures and product dissatisfaction leads to ineffective recovery strategies.
  • Delayed activation efforts - Waiting too long to connect a user to value allows them to drop off before they experience the product's benefits.

Deep Dive

For all 50 sourced insights from 11 guests, see references/guest-insights.md

Related Skills

  • Growth Model
  • Acquisition Channels
  • User Onboarding Activation
  • Referrals Word Of Mouth

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 Retention Engagement AI skill do?

Help users identify the drivers of long-term retention and implement behavioral mechanics that keep customers coming back. This guide focuses on measuring the survival curve of users and optimizing the product environment for high frequency usage.

Why use Retention Engagement on TypingMind?

Because you install it once and use it with any model. Retention Engagement 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 Retention Engagement in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RefoundAI/lenny-skills/tree/main/skills/retention-engagement. 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 Retention Engagement?

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 Retention Engagement?

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

Is the Retention Engagement AI skill free?

Yes. It is published on GitHub by RefoundAI 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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