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Managing Tech Debt

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cnfeat
managing-tech-debt

Help users manage technical debt strategically. Use when someone is dealing with legacy code, planning refactoring work, deciding between rewrites vs. incremental fixes, trying to get buy-in for tech debt reduction, or balancing new features with maintenance.

Overview

Publishercnfeat
Repositorytop-pm-skills
Skill namemanaging-tech-debt
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 Managing Tech Debt 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/managing-tech-debt
  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 Managing Tech Debt 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 Managing Tech Debt 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 Managing Tech Debt 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.

Managing Tech Debt

Help the user manage technical debt strategically using insights from 18 product leaders.

How to Help

When the user asks for help with tech debt:

  1. Understand the situation - Ask about the nature of the debt (legacy systems, code quality, architectural limitations), how it's manifesting (slow velocity, incidents, inability to ship), and the business context
  2. Diagnose the urgency - Determine if this is blocking critical business needs or a slower-burning issue
  3. Choose the right approach - Help them decide between incremental improvement, targeted refactoring, or (rarely) a full rewrite
  4. Build the business case - Help quantify the cost of the debt and communicate value to stakeholders

Core Principles

Rewrites almost never work

Camille Fournier: "Engineers notoriously, notoriously, notoriously, massively underestimate the migration time for old system to new system. By the way, you still have to support the old system while you're working on the new system." Full rewrites are traps. Prefer incremental evolution - uplift specific components rather than starting from scratch.

Tech debt is product debt

Ebi Atawodi: "Infrastructure is the product. Period. I cannot build a skyscraper on a shaky foundation. So it is your problem too - it's not for the engineer to be barging on the door." Technical debt should be owned by PMs as "product debt," not treated as an engineering-only concern. Include it in your Top 10 Problems list.

Startups should strategically take on debt

Gaurav Misra: "As a startup your job is to take on technical debt because that is how you operate faster than a bigger company." Debt is leverage - evaluate if a problem can be solved by a future hire rather than today. But monitor the "interest" - if maintenance takes 80-90% of time, you've run out of runway.

Delete code more than you write it

Farhan Thawar: "We have a Delete Code Club. We can almost always find a million-plus lines of code to delete. Everything gets easier - the codebase loads faster, it's easier to understand." Create dedicated time or teams focused solely on removing unused code. Deletion improves velocity and clarity.

Tech debt is visible to users

Matt Mullenweg: "You can see [tech debt] in the interface or how their products integrate with themselves." Fragmented UIs and poor integration between features are user-facing symptoms of accumulated debt. Look for inconsistencies to identify where debt has accumulated.

Quantify the value of paying down debt

Casey Winters: "The most impactful projects are the hardest to measure, so they get chronically underfunded. Build custom metrics to show the value, run small tests that prove the worthwhile-ness of the investment." Create custom metrics and run experiments to demonstrate business value. Align with engineering and design to present a unified front.

Fix bugs immediately, don't backlog them

Geoff Charles: "We don't have a bug backlog. We fix every bug once they're surfaced almost." Assign bugs directly to the engineer on call to ensure immediate pain awareness. Bug backlogs become graveyards.

Debt ceilings innovation

Eeke de Milliano: "Sometimes teams are just getting bogged down by urgent work - too much tech debt, bugs, instability. There's no way they can focus on bigger, creative stuff if they're heads-down dealing with incidents all day." Diagnose when a team is stuck in a "hierarchy of needs" trap. Prioritize debt reduction to free up headspace for creative work.

Tech debt is a champagne problem

Julia Schottenstein: "We would be so lucky to have tech debt because that means people are using the product. What we didn't need at launch was a distributed scheduler - we had no users." Build the simplest, most naive version first. Accept debt as a trade-off for getting product into users' hands.

Plan for dark tunnels

Melanie Perkins: "We thought it would take six months... it took two years of not shipping any product." Major rewrites are "dark tunnels" that stall shipping. If you must do them, gamify the work to maintain team momentum during the long slog.

Design for 1-2 years out

Austin Hay: "Think one to two years down the road about what we're going to need. When setting up tools, ask: 'What happens a year from now if I don't change anything?'" Implement foundational elements like SSO or proper data schemas early to avoid catastrophic migrations later.

Questions to Help Users

  • "Is this debt blocking critical business needs, or is it a slower-burning issue?"
  • "What percentage of engineering time is going to maintenance vs. new features?"
  • "Have you tried to estimate how long a rewrite would actually take? Who made that estimate?"
  • "What would happen if you did nothing for another 6 months?"
  • "Is there a way to incrementally improve this rather than rewriting?"
  • "How would you quantify the cost of this debt to stakeholders?"

Common Mistakes to Flag

  • Planning a full rewrite - Rewrites almost never work as planned. They take 2-3x longer than estimated and you must support both systems simultaneously
  • Treating tech debt as engineering's problem - This is product debt. PMs should own it alongside engineers
  • Letting bug backlogs accumulate - Bug backlogs become graveyards. Fix immediately or decide not to fix at all
  • Over-engineering before product-market fit - Debt is a champagne problem. Build naive solutions first and accept debt as the cost of learning
  • Not quantifying the cost - Tech debt investments get underfunded because their value isn't measured. Build metrics and run experiments to prove ROI

Deep Dive

For all 20 insights from 18 guests, see references/guest-insights.md

Related Skills

  • Technical Roadmaps
  • Platform & Infrastructure
  • Engineering Culture
  • Evaluating Trade-offs

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 Managing Tech Debt AI skill do?

Help users manage technical debt strategically. Use when someone is dealing with legacy code, planning refactoring work, deciding between rewrites vs. incremental fixes, trying to get buy-in for tech debt reduction, or balancing new features with maintenance.

Why use Managing Tech Debt on TypingMind?

Because you install it once and use it with any model. Managing Tech Debt 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 Managing Tech Debt 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/managing-tech-debt. 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 Managing Tech Debt?

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 Managing Tech Debt?

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

Is the Managing Tech Debt 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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