ai-adoption-playbook
By adimango
Orchestrate structured AI adoption for engineering teams: assess fluency via quizzes and data, diagnose blockers, select quick-win use cases, build 90-day plans with owners and metrics, audit tool stacks for waste, calculate ROI, run quarterly reviews, and generate board-ready scorecards and narratives.
npx claudepluginhub adimango/ai-adoption-playbookComponent Overview
Component Details
Skills (12)
Use when a founder has diagnosed their AI adoption blockers and picked a first use case, and now needs a phased rollout plan with milestones aligned to board reporting cycles
Use when a founder needs a quick snapshot of current AI adoption status for a board deck, leadership update, or progress check — not a diagnostic, just the numbers
Use when AI adoption has stalled and the founder needs to understand specifically what's blocking their team — goes deeper than the fluency assessment to identify root causes per pillar
Use when a founder needs to draft the AI section of a board update and already has results data — produces the formatted update, not the rehearsal
Use when a founder is preparing for a board meeting and needs to present their AI adoption progress — rehearses with hard questions first, then drafts the actual board update
Use when a founder needs to choose where to start with AI adoption — finds the highest-probability first use case that produces visible results within 2-4 weeks
Use when a leader responsible for AI adoption wants to understand where their team stands with AI tools — the entry point diagnostic before any other AI adoption skill
Use when a founder wants the complete AI adoption process from start to finish — orchestrates assessment through board narrative in sequence
Use when a founder has completed at least one adoption cycle and needs to reassess progress, compare to the previous scorecard, and prepare the next board update
Use when a founder needs to calculate or present the ROI of AI tool adoption — typically before a board meeting or when justifying continued investment
Use when a founder wants to evaluate their current AI tools — identify overlap, waste, gaps, and whether tools match actual use cases
Use when someone responsible for AI adoption starts a conversation about AI strategy, AI tools, or getting their team to use AI — routes to the right skill based on context and whether a fluency assessment has been completed
README
AI Adoption Playbook
From "we're exploring AI" to board-ready results.
A skills framework for leaders responsible for AI adoption — founders, CTOs, CAIOs, VPs of Engineering, COOs, or anyone who needs to show the board that AI investment is producing results.
The Problem
Leadership asks "what's your AI strategy?" You bought tool licenses. You told the team to use them. Nothing happened. Next board meeting, you say "we're exploring AI." The board is unimpressed. Repeat.
This playbook breaks that loop with a structured process: diagnose what's stuck, build a plan with owners and milestones, and produce board-ready updates with real numbers.
Quick Start
- Clone this repo
- Open it in Claude Code
- Say: "My board is asking about our AI strategy"
The playbook will run a fluency assessment, diagnose your blockers, and guide you to the right next step.
Skills
Component Skills
| Skill | What it produces |
|---|---|
adoption-scorecard | Snapshot of who uses what AI tools, how often, how well |
board-ai-update | Board-ready narrative with specific numbers |
tool-stack-audit | What you pay for vs. what gets used |
roi-calculator | Quantified impact in terms your board cares about |
Interactive Skills
| Skill | What it does |
|---|---|
fluency-assessment | Entry point — scores your team across three pillars |
blocker-diagnosis | Deep dive into what's stuck and why |
first-use-case-picker | Finds the right starting point for maximum visible wins |
90-day-plan-builder | Phased rollout with board-cycle milestones |
board-narrative-coach | Practice with a skeptical VC, then draft the update |
Workflow Skills
| Skill | What it orchestrates |
|---|---|
full-adoption-cycle | Assessment -> diagnosis -> use case -> plan -> narrative |
quarterly-review | Re-assess, compare to last quarter, generate board update |
How It Works
Every AI adoption failure maps to one of three pillars:
- Psychological barriers — fear, identity threat, "I don't need it"
- Integration failures — tools don't fit workflows, wrong use cases, too much friction
- Ownership gaps — nobody owns it, no metrics, no accountability
The playbook diagnoses which pillars are blocking you, then guides you through fixing them in an order that produces board-reportable results.
Installation
Requires Claude Code.
Install as a plugin from GitHub:
/plugin marketplace add adimango/ai-adoption-playbook
/plugin install ai-adoption-playbook@ai-adoption-playbook
Or clone and use directly:
git clone https://github.com/adimango/ai-adoption-playbook.git
cd ai-adoption-playbook
Once installed, say "My board is asking about our AI strategy" and the playbook takes over.
Test locally during development:
claude --plugin-dir ./ai-adoption-playbook
Skills are namespaced as /ai-adoption-playbook:skill-name (e.g., /ai-adoption-playbook:fluency-assessment).
Future: MCP server packaging for use with Claude Desktop, Cursor, and other MCP-compatible clients.
License
MIT
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