Ai Shaped Readiness Advisor
Honestly score whether your product org is AI-first (faster old tasks) or AI-shaped (redesigned operations) across five PM competencies and pick what to build next.
Overview
AI-Shaped Readiness Advisor is a journey-wide agent skill that assesses AI-first vs AI-shaped product maturity across five PM competencies—usable whenever a solo builder needs to prioritize org capability before committi
Install
npx skills add https://github.com/deanpeters/product-manager-skills --skill ai-shaped-readiness-advisorWhat is this skill?
- Separates AI-first automation from AI-shaped operating model redesign with explicit definitions
- Scores readiness across 5 essential PM competencies for 2026
- Interactive assessment estimated at 15–20 minutes
- Outputs concrete recommendation on which competency to build first
- Best for teams using AI tools but unsure if workflows actually changed
- 15–20 min estimated interactive assessment
Adoption & trust: 1.2k installs on skills.sh; 5k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your team uses AI tools but you cannot tell if you are just automating the same PM tasks or actually operating differently.
Who is it for?
Founder-PMs and lean product teams planning AI investment who need an honest AI-first versus AI-shaped diagnosis before scope locks.
Skip if: Pure engineering codegen tasks or teams seeking implementation plans for a specific feature with no org maturity question.
When should I use this skill?
Evaluating AI maturity and choosing the next team capability to build; when unsure if work is AI-first or AI-shaped.
What do I get? / Deliverables
You get a gap-aware maturity view across five competencies and a concrete recommendation for which capability to build first next quarter.
- AI-first vs AI-shaped readiness interpretation
- Gap view across five PM competencies with a prioritized next capability to build
Recommended Skills
Journey fit
Useful at every journey phase - explore requirements and options before committing to a direction.
Where it fits
Before committing to an AI-native product thesis, check whether the team can operate AI-shaped discovery or only accelerates legacy PRD writing.
Prioritize which of the five competencies to fund this quarter instead of buying more seat licenses.
Decide if lifecycle experiments should be redesigned around agent-assisted loops or merely sped up with drafts.
Re-run the advisor after a major tooling change to see if rituals actually shifted toward AI-shaped operations.
How it compares
Interactive PM readiness advisor, not a code generator or a security audit skill for repositories.
Common Questions / FAQ
Who is ai-shaped-readiness-advisor for?
Product managers, solo founders, and small product orgs evaluating AI maturity and deciding which of five PM competencies to strengthen before deeper build or growth bets.
When should I use ai-shaped-readiness-advisor?
Use it in Validate when scoping next quarter’s AI bets, in Idea when framing whether the opportunity needs AI-shaped discovery, in Grow when lifecycle work should reflect new competencies, and in Operate when iterating how the team runs with agents.
Is ai-shaped-readiness-advisor safe to install?
It is an interactive planning skill without described shell or network side effects; review the Security Audits panel on this Prism page like any third-party SKILL.md.
SKILL.md
READMESKILL.md - Ai Shaped Readiness Advisor
## Purpose Assess whether your product work is **"AI-first"** (using AI to automate existing tasks faster) or **"AI-shaped"** (fundamentally redesigning how product teams operate around AI capabilities). Use this to evaluate your readiness across **5 essential PM competencies for 2026**, identify gaps, and get concrete recommendations on which capability to build first. **Key Distinction:** AI-first is cute (using Copilot to write PRDs faster). AI-shaped is survival (building a durable "reality layer" that both humans and AI trust, orchestrating AI workflows, compressing learning cycles). This is not about AI tools—it's about **organizational redesign around AI as co-intelligence**. The interactive skill guides you through a maturity assessment, then recommends your next move. ## Key Concepts ### AI-First vs. AI-Shaped | Dimension | AI-First (Cute) | AI-Shaped (Survival) | |-----------|-----------------|----------------------| | **Mindset** | Automate existing tasks | Redesign how work gets done | | **Goal** | Speed up artifact creation | Compress learning cycles | | **AI Role** | Task assistant | Strategic co-intelligence | | **Advantage** | Temporary efficiency gains | Defensible competitive moat | | **Example** | "Copilot writes PRDs 2x faster" | "AI agent validates hypotheses in 48 hours instead of 3 weeks" | **Critical Insight:** If a competitor can replicate your AI usage by throwing bodies at it, it's not differentiation—it's just efficiency (which becomes table stakes within months). --- ### The 5 Essential PM Competencies (2026) These competencies define AI-shaped product work. You'll assess your maturity on each. #### 1. **Context Design** Building a durable **"reality layer"** that both humans and AI can trust—treating AI attention as a scarce resource and allocating it deliberately. **What it includes:** - Documenting what's true vs. assumed - Immutable constraints (technical, regulatory, strategic) - Operational glossary (shared definitions) - Evidence standards (what counts as validation) - **Context boundaries** (what to persist vs. retrieve) - **Memory architecture** (short-term conversational + long-term persistent) - **Retrieval strategies** (semantic search, contextual retrieval) **Key Principle:** *"If you can't point to evidence, constraints, and definitions, you don't have context. You have vibes."* **Critical Distinction: Context Stuffing vs. Context Engineering** - **Context Stuffing (AI-first):** Jamming volume without intent ("paste entire PRD") - **Context Engineering (AI-shaped):** Shaping structure for attention (bounded domains, retrieve with intent) **The 5 Diagnostic Questions:** 1. What specific decision does this support? 2. Can retrieval replace persistence? 3. Who owns the context boundary? 4. What fails if we exclude this? 5. Are we fixing structure or avoiding it? **AI-first version:** Pasting PRDs into ChatGPT; no context boundaries; "more is