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Altitude Horizon

Community
Productfculty-aipm
altitude-horizon

Use this skill when the user asks about "altitude and horizon framework", "Shreyas Doshi altitude", "working at the right level", "am I too in the weeds", "I'm too tactical", "how do I work at the right altitude", "horizon thinking for PMs", or wants to evaluate whether they're operating at the right level of abstraction for their role and stage.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill namealtitude-horizon
Stars
80
Forks
34
Bundled files
Instructions only
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.

  • 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 Altitude Horizon 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/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/altitude-horizon
  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/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/altitude-horizon .claude/skills/altitude-horizon
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Altitude Horizon 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 Altitude Horizon 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 Altitude Horizon 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.

Altitude and Horizon Framework

You are applying Shreyas Doshi's altitude-horizon framework to help the PM work at the right level of abstraction for their role and company stage.

Framework: Shreyas Doshi (3 levels of product work, Lenny's Podcast 2024 + LinkedIn), Jackie Bavaro (PM altitude calibration).

Key insight: "The biggest growth opportunity for most PMs isn't doing the current level better — it's learning to operate at the next altitude." — Shreyas Doshi

Step 1 — Load Context

Read memory/user-profile.md for the user's role and product stage. Understand: what is their formal scope and what altitude is expected of them?

Step 2 — The Altitude Framework

Altitude describes how abstractly or specifically you're thinking and working:

High altitude (30,000 feet) — Vision and strategy:

  • Thinking about: 3-year product vision, strategic positioning, moats, company-level OKRs
  • Language: "We're trying to make [outcome X] possible for [segment Y]"
  • Works in: Quarterly planning, board conversations, company direction discussions
  • When too high: Ideas are inspiring but not actionable. Team can't translate vision to sprint work.

Mid altitude (10,000 feet) — Product strategy and roadmap:

  • Thinking about: Now/Next/Later, opportunity prioritization, OKR definition, ICP, beachhead
  • Language: "We should focus on [segment] because [evidence], which means [roadmap implication]"
  • Works in: Planning meetings, leadership updates, initiative prioritization
  • When too high for this level: Roadmap items don't connect to specific user problems.
  • When too low for this level: Roadmap is just a list of tickets.

Low altitude (1,000 feet) — Feature and execution:

  • Thinking about: PRD, user stories, acceptance criteria, sprint priorities, metrics
  • Language: "When a user does [X], the system should [Y], because [user need]"
  • Works in: Sprint planning, design reviews, engineering conversations
  • When too low: Getting into implementation details that should be engineering's domain.

Ground level — Implementation:

  • Engineering's domain: How to build it, which libraries, architecture choices.
  • A PM who spends time here is not doing PM work.

Step 3 — The Horizon Framework

Horizon describes how far ahead you're thinking:

Long horizon (12+ months): Vision, market evolution, competitive dynamics, platform choices Medium horizon (3–12 months): Roadmap, OKRs, product strategy decisions Short horizon (1–12 weeks): Sprint, feature, launch Now horizon (days): Fires, blockers, immediate decisions

The right horizon depends on role level:

  • IC PM: primarily short + some medium horizon thinking
  • Senior PM: medium + some long horizon thinking
  • Director/VP: medium + long horizon thinking
  • CPO: long + very long horizon thinking

Step 4 — Self-Assessment

Based on what the user shares about their work, assess:

Are they working at the right altitude?

Signs they're too low for their role:

  • Spending most time in Jira tickets and Sprint Grooming
  • Getting pulled into decisions that should be engineering's
  • Writing detailed acceptance criteria for things that don't need a PM
  • Not having time for strategy or discovery because execution consumes everything

Signs they're too high for their role:

  • Making strategic decisions without evidence
  • Not knowing the details of what users actually do
  • Disconnected from the day-to-day shipping
  • Team can't translate their direction into action

Are they working at the right horizon?

Signs they're too short-horizon:

  • Always reacting, never anticipating
  • Roadmap looks only 1–2 sprints out
  • No time for discovery because there's always a fire

Signs they're too long-horizon:

  • Great vision but messy execution
  • Team doesn't feel the PM adds value to their daily work
  • Plans that never connect to things that ship

Step 5 — Calibration Advice

Based on the assessment, advise:

  • Which altitude to spend more time at, and what that looks like in practice
  • Which altitude to spend less time at, and how to delegate or deprioritize it
  • Which horizon to stretch toward, and what first step gets them there
  • One concrete change to make this week that shifts the pattern

Step 6 — Output

Produce:

  • Current altitude/horizon assessment with evidence
  • Target altitude/horizon for their role and stage
  • The gap between current and target
  • Three specific behavioral changes that would shift the altitude/horizon calibration
  • The type of work to do more of vs. less of in the next month

Frequently asked questions

What does the Altitude Horizon AI skill do?

Use this skill when the user asks about "altitude and horizon framework", "Shreyas Doshi altitude", "working at the right level", "am I too in the weeds", "I'm too tactical", "how do I work at the right altitude", "horizon thinking for PMs", or wants to evaluate whether they're operating at the right level of abstraction for their role and stage.

Why use Altitude Horizon on TypingMind?

Because you install it once and use it with any model. Altitude Horizon 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 Altitude Horizon 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/altitude-horizon. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Altitude Horizon?

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 Altitude Horizon?

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

Is the Altitude Horizon 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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