feat: 4-week AI Initiative series — plan + skeleton presentations
Week 1: The AI Multiplier (MCP + Skills) Week 2: Making AI Actually Work (CLAUDE.md) Week 3: Real Stories, Real Results Week 4: What Could You Build? (Interactive) Skeleton decks in presenterm format. PLAN.md has full series architecture, structure, speaker notes, and open decisions.
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week2-claude-md/presentation.md
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week2-claude-md/presentation.md
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Making AI Actually Work
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CLAUDE.md and the Art of Instruction
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<!-- speaker_note: Last week: what's possible. This week: how to get it. -->
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<!-- speaker_note: Quick recap: MCP gives AI tools, Skills give AI expertise. Today — how to give AI context about YOU and YOUR work. -->
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Why AI Disappoints People
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===
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**What people say:**
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"AI doesn't work."
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"It hallucinates too much."
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"Copilot is useless."
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**What's actually happening:**
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"I gave it no context."
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"I asked it to guess."
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"I gave it the wrong tool."
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Imagine hiring a brilliant consultant and telling them nothing about your company.
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Then being surprised when their advice is generic.
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<!-- speaker_note: This reframe is critical. Bad tool ≠ bad category. But also: bad instructions ≠ bad tool. -->
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<!-- speaker_note: The Copilot → "AI doesn't work" pipeline is real. People blame the category, not the vendor. -->
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The Three Levels
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===
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```mermaid +render +width:100%
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graph TD
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S["🏢 System Level<br/>Who is the AI? What org is this?<br/>Guardrails, conventions, culture"]
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P["📁 Project Level<br/>What are we building?<br/>Constraints, decisions, patterns"]
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U["👤 User Level<br/>Who am I?<br/>Preferences, style, context"]
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S --> P --> U
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style S fill:#ff6b6b,stroke:#333,color:#fff
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style P fill:#4a9eff,stroke:#333,color:#fff
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style U fill:#51cf66,stroke:#333,color:#fff
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```
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Each level compounds. The AI gets better at every layer.
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<!-- speaker_note: These aren't abstract. They map directly to files and configuration. -->
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System Level
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===
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The organisation-wide context. Who is this AI? What does it know?
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**"Be helpful"** → generic, useless
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**"You are an Axway services consultant. You know our deployment patterns use GitOps via ArgoCD. Customer naming follows the CUST-REGION-ENV pattern. Escalation path is engineer → team lead → director. Never modify production without explicit approval."**
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→ Now the AI has context that would take a new hire weeks to absorb.
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<!-- speaker_note: Read the second one aloud. Let it land. That's the difference. -->
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<!-- speaker_note: This is what CLAUDE.md IS — the onboarding document for your AI colleague. -->
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Project Level
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===
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**The "new colleague joins the project" test:**
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What would you put in their first-day doc?
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* What are we building and why?
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* What's been decided (and what hasn't)?
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* What are the constraints?
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* Where is everything? (repos, docs, environments)
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* What are the gotchas?
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Write that document. Put it in CLAUDE.md or AGENTS.md.
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Your AI reads it every single session.
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<!-- speaker_note: The analogy makes it tangible. Everyone knows what onboarding feels like. -->
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<!-- speaker_note: If you wouldn't expect a new hire to succeed without this context, why expect AI to? -->
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User Level
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===
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Personal working style. The compound effect.
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**Without:**
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- Generic tone
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- Over-explains basics
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- Wrong assumptions
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- Feels like talking to a stranger
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**With:**
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- Matches your communication style
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- Knows your role and expertise level
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- Remembers your preferences
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- Feels like working with someone who knows you
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System + Project + User = AI that feels like a team member, not a chatbot.
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<!-- speaker_note: This is where it gets personal and relatable. -->
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<!-- speaker_note: "Concise answers" vs "walk me through reasoning" — small preference, huge impact over time. -->
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Intent vs. Instruction
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===
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**Vague** 😬
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"Check if my server
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is secure"
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**Better** 👍
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"Audit SSH config
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against CIS benchmarks,
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prioritise by severity"
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**Best** 🎯
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Write a skill for it.
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AI follows the same
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checklist every time.
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Ambiguity is the enemy of automation.
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If you don't define "safe"… the AI will.
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<!-- speaker_note: Callback to Week 1 skills content. The three levels of prompt quality. -->
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DEMO
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===
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Same prompt. Two contexts. Watch what changes.
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<!-- speaker_note: Demo 1: Before and after CLAUDE.md — same prompt, dramatic difference -->
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<!-- speaker_note: Demo 2: Build a CLAUDE.md live with the audience for a real project -->
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<!-- speaker_note: PLACEHOLDER: Decide which project/scenario for the live build -->
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Your Homework
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===
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* **This week:** Write a CLAUDE.md for one project you're working on
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* **This week:** Add 3 sentences about your preferences to your AI tool
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* **Next time you're frustrated:** Ask "what context was I not giving it?"
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These are 10-minute tasks that permanently improve every AI interaction.
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<!-- speaker_note: Keep it concrete and achievable. Three things, this week. -->
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Next Week
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===
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Real stories from real people in this room.
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What Dhruv built for $2.50. What Gill discovered in her first hour.
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What's actually changing in how we work.
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🎯
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<!-- speaker_note: Name drop. Create anticipation. People want to hear peer stories. -->
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