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feat: 4-week AI Initiative series — plan + skeleton presentations

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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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# AI Initiative — Friday All-Hands Series
**4 weeks, 1 hour each, APAC all-hands**
**Presenter:** Conan Scott, Director of Services APAC
**Audience:** Mixed — Services team (primary target), presales, support, management. Technical range from "what's a prompt" to Dhruv/Saori-level builders.
---
## Series Arc
The four sessions follow a deliberate arc: **Wow → How → Deep → What If**
| Week | Date | Title | Goal |
|------|------|-------|------|
| 1 | Apr 4 | **The AI Multiplier: MCP + Skills in Action** | Hook them. Show what's possible. Create desire. |
| 2 | Apr 11 | **Making AI Actually Work: CLAUDE.md and the Art of Instruction** | Practical takeaway. Everyone walks out knowing how to be better at using AI *today*. |
| 3 | Apr 18 | **Real Stories, Real Results** | Credibility. Axway people, Axway problems, AI solutions. Named stories + industry context. |
| 4 | Apr 25 | **What Could You Build? (Interactive)** | Engagement. Solicit ideas. Surface hidden use cases. Plant seeds for after paternity. |
---
## Week 1: The AI Multiplier — MCP + Skills in Action
**Friday April 4 · 1 hour**
### Intent
This is the hook. The audience should leave thinking "I want that." Not "that's interesting" — "I want that."
### Structure (60 min)
**Part 1: The Problem (10 min)**
- The copy-paste loop (repurpose the existing "Without MCP" sequence diagram — grandpa Simpson energy)
- Why people "bounce off" AI for real work — the frustration cycle
- Quick reframe: the problem isn't AI, it's the interface between AI and your systems
**Part 2: MCP — Giving AI Hands (10 min)**
- What is MCP (keep it tight — open standard, created by Anthropic, gives tools to AI)
- The flip: you stop being the middleware
- Show the tool ecosystem briefly: OCP, Git, ArgoCD, databases, anything with an API
**Part 3: Skills — Giving AI Expertise (10 min)**
- The lazy-loading concept (repurpose existing skills deck — the token cost diagram)
- Skills = SOPs for AI. Your best engineer writes it once, every agent benefits forever.
- Quick examples: weather (simple), healthcheck (structured), ST flow engineering (deep domain)
- **Key point for the room:** "People leave. Skills persist." — this lands hard with the institutional knowledge crowd (the Bills and Gills)
**Part 4: Live Demo (25 min)**
- **Demo 1 — The Cluster Health Check (~8 min)**
AI investigates an OpenShift cluster via MCP. Produces insight, not just data. Show it reasoning across multiple tools.
*While AI works:* Conan does something else visibly. The multiplier point is made without saying it.
- **Demo 2 — A Skill in Action (~8 min)**
Trigger a skill-driven task. Show the difference between "wing it" and "follow the SOP."
[PLACEHOLDER: Decide which skill — healthcheck is clean, ST flow engineering is impressive but niche. Healthcheck is probably better for mixed audience.]
- **Demo 3 — The "Figure It Out" Moment (~9 min)**
Something that requires the AI to adapt — discover tools, chain them, handle an unexpected result. The "holy shit" moment.
[PLACEHOLDER: Decide scenario. The cross-platform Apple Notes demo from SCRATCHPAD is good — container → Mac node → discovers AppleScript. Or: "fix this broken deployment" end-to-end.]
**Part 5: Close (5 min)**
- "What you didn't see" — all the commands, iterations, errors handled silently
- The 3x multiplier framing: parallel work + additive AI contribution
- Tease next week: "Now I'll show you how to get this yourself"
### Speaker Notes
- During demos, narrate what the AI is doing and why, but don't over-explain. Let the audience see the magic.
- If a demo takes longer than expected (AI things), that's actually fine — the audience is watching it think. Use the time.
- Audience question time is flexible — can cut from Part 2 or 3 if demos run long.
---
## Week 2: Making AI Actually Work — CLAUDE.md and the Art of Instruction
**Friday April 11 · 1 hour**
### Intent
Practical, actionable, "I can do this Monday morning." The audience should leave with a clear mental model of how to communicate with AI effectively — and specifically, how CLAUDE.md / system-level instructions change everything.
### Structure (60 min)
**Part 1: Why AI Disappoints People (10 min)**
- The Copilot gap — "would you like me to help you think about..." vs just doing it
- The "AI doesn't work" fallacy — bad tool ≠ bad category
- Root cause: people are talking to AI like a search engine, or like a very literal junior employee
- Reframe: AI is a capable colleague who just started today — they need context, not commands
**Part 2: The Three Levels of AI Instruction (20 min)**
- **System level** — CLAUDE.md / system prompts. Who is the AI? What does it know about your org? What are the guardrails?
- Show a real CLAUDE.md example (sanitised if needed)
- The difference between "be helpful" and "you are an Axway services consultant who knows our deployment patterns, customer naming conventions, and escalation paths"
- **Project level** — Context per project/repo. What are we building? What are the constraints? What's been decided?
- AGENTS.md pattern: "read this before you do anything"
- The "new colleague joins the project" analogy — what would you put in their onboarding doc?
- **User level** — Personal preferences, communication style, working patterns
- "I prefer concise answers" vs "walk me through your reasoning"
- The compound effect: system + project + user = AI that feels like it knows you
**Part 3: Intent vs. Instruction (10 min)**
- Repurpose the existing "Prompt Engineering" slide from deck 01
- Expand with real examples:
- Bad: "Check if my server is secure"
- Better: "Audit SSH configuration against CIS benchmarks, prioritise findings by severity, suggest specific remediation commands"
- Best: Write a skill for it (callback to Week 1)
- "Ambiguity is the enemy of automation. If you don't define 'safe'… the AI will."
**Part 4: Live Demo (15 min)**
- **Demo 1 — Before and After CLAUDE.md (~7 min)**
Same prompt, two contexts. Show the dramatic difference in output quality.
- **Demo 2 — Building a CLAUDE.md Live (~8 min)**
Pick a real Axway project or scenario. Build a CLAUDE.md with the audience. Show it immediately improve AI output.
[PLACEHOLDER: Need to decide which project/scenario. Something the whole room recognises.]
**Part 5: Practical Takeaway + Close (5 min)**
- Checklist: 3 things you can do this week
1. Write a CLAUDE.md for one project
2. Add 3 sentences of personal preference to your AI tool
3. Next time you're frustrated with AI output, ask "what context was I not giving it?"
- Tease Week 3: "Next week — real stories from people in this room"
---
## Week 3: Real Stories, Real Results
**Friday April 18 · 1 hour**
### Intent
Social proof and credibility. Named stories from Axway people using AI to solve Axway problems. Mixed with broader industry examples to show the trajectory. This is the session that converts skeptics — not through tech demos, but through peer stories.
### Structure (60 min)
**Part 1: The Bedrock Trial — Early Results (10 min)**
- 5-person pilot, one month of data by now
- Usage patterns per persona type (without naming cost figures if sensitive)
- The reactions: "I CAN NEVER GO BACK TO COPILOT" — Gill, hour one
- What surprised us
**Part 2: Real Use Cases — Our People (25 min)**
- **Dhruv's Time Tracker** (~5 min)
Built a custom local program to efficiently fill the corporate time tracker. $2.50. One time. Previously tried with Copilot 365 — more time fighting the tool than doing the task manually. Day 1 of Claude: specified, built, done.
*The lesson:* AI that acts vs AI that asks.
- **Saori's AI Integration** (~5 min)
First AI project, complex integration, building it with Claude from day one. Junior hire 2 years ago → now building production AI systems.
*The lesson:* The tool shapes the builder. Start with a good one.
- **Gill's Consulting Superpower** (~5 min)
"It's like a consulting service." The institutional knowledge amplifier — decades of customer context + AI reasoning = advice that used to take a team and a week.
*The lesson:* AI doesn't replace expertise, it amplifies it.
- **The SecureTransport Story** (~5 min)
[PLACEHOLDER: Decide how much to share. The ST flow engineering skill, the agent, the RAG journey. This is the "deep domain" example — months of tribal knowledge encoded, instantly available.]
*The lesson:* Capture knowledge before it walks out the door.
- **Other examples from the room** (~5 min)
Open it up. "Who else has a story?" By week 3, the pilot group will have more. Others might too.
[NOTE: Seed this in advance — ask Dhruv, Saori, Neo if they want to share something briefly.]
**Part 3: Beyond Axway — What's Happening Out There (10 min)**
- Industry examples of AI transformation in services/consulting orgs
- The "AI or bust" moment from Paris AI Forum — Axway is institutionally serious now
- Competitors are moving. Standing still is falling behind.
- [PLACEHOLDER: 3-4 specific industry examples. Research closer to date for freshness.]
**Part 4: The Uncomfortable Truth (10 min)**
- The person leveraging AI will outcompete the person who isn't
- This isn't "AI will replace you" — it's "someone using AI will outperform you"
- Copilot-grade AI creates AI skeptics. Quality matters.
- "We invested in Claude on Bedrock because we believe in giving you the best tool, not the cheapest one"
**Part 5: Close (5 min)**
- Recap the multiplier: Dhruv = 3x on a $2.50 investment. What's your version?
- Tease Week 4: "Next week — your turn. What would YOU build?"
---
## Week 4: What Could You Build? (Interactive)
**Friday April 25 · 1 hour**
### Intent
Engagement, ownership, idea generation. This is where you plant seeds that grow while you're on paternity. The room should leave with concrete ideas they want to try, and ideally a few people who want to champion something.
### Structure (60 min)
**Part 1: Recap + "Things You Didn't Know Were Possible" (15 min)**
- Quick series recap (3 slides max)
- Then the mind-expanders — things the audience probably hasn't considered:
- Cross-platform automation (container → Mac → AppleScript → Apple Notes)
- Multi-agent orchestration (main agent delegates to specialists)
- Scheduled AI work (cron-style: "every Monday morning, summarise last week's tickets and email me")
- Browser automation (AI navigates web UIs on your behalf)
- Voice/TTS (AI calls you with a briefing — yes, really)
- Node control (AI operates remote machines)
- Hooks (external events trigger AI responses — monitoring alerts → investigation → report)
- n8n + AI (durable workflows with AI decision points)
- Frame it: "These are all real, working today. What would you use them for?"
**Part 2: Ideation — Small Groups (20 min)**
- Break into groups of 3-4 (or if virtual, breakout rooms)
- Prompt: "Think about your week. What's repetitive? What's tedious? What requires you to be the middleware between two systems? What knowledge is trapped in one person's head?"
- Each group picks their best idea
- [NOTE: If the room is too shy for groups, do it as a facilitated brainstorm with post-its/chat instead]
**Part 3: Share Back + Discussion (20 min)**
- Each group shares their idea (~2 min each)
- Conan and room react — "that's buildable", "that's a skill", "that needs MCP", "that's a Tuesday afternoon project"
- Capture everything visibly (shared doc, whiteboard, whatever)
- Identify quick wins vs bigger projects
- Ask: "Who wants to own this one?"
**Part 4: What Happens Next (5 min)**
- Conan's going on paternity leave (congratulations moment)
- The AI initiative doesn't stop — here's how to keep going:
- Bedrock access continues
- CLAUDE.md templates available
- Skill creation guide available
- Champions identified from today's session
- [PLACEHOLDER: Decide on a Slack/Teams channel, shared doc, or other continuity mechanism]
- "When I come back, I want to hear what you built."
---
## Cross-Cutting Notes
### Tone
- Professional but not corporate. The Simpsons gifs stay.
- Serious content wrapped in human delivery. No "enterprise transformation" jargon.
- Be honest about limitations — "AI hallucinates sometimes, that's real, here's how we handle it"
- The old guard needs respect, not condescension. Their skepticism is earned. Meet it with evidence, not enthusiasm.
### Demo Environment
[WAITING ON CONAN: Are we demoing from Bedrock/corporate setup, or personal OpenClaw? This shapes what tools/capabilities we can show.]
### Recurring Elements
- Open each session with a 1-min recap of last week (for anyone who missed it)
- Close each session with a teaser for next week (serial structure)
- "3x multiplier" is the recurring motif — reference it every week
- Keep a running "ideas board" across all 4 weeks — things that come up in Q&A get captured
### Media Assets Needed
- Existing: axway.png, grandpa-gpt.gif, homerspin.gif, happy2.gif, robot.png, duckgpt.gif
- Needed: [PLACEHOLDER: Screenshots of CLAUDE.md examples, Bedrock console, skill structure, Dhruv's tool (if he's ok with it)]
### Risks
- Demo failure during live presentation. Mitigation: pre-recorded fallback for each demo, but try live first. Live failures are actually ok if you narrate through them — "see, it's trying something else" is part of the story.
- Low engagement in Week 4 ideation. Mitigation: Seed 2-3 people in advance to kick things off. Conan's team (Dhruv, Saori) go first.
- Audience too diverse — technical people bored by basics, non-technical lost by demos. Mitigation: narrate demos at two levels ("what it's doing" + "why that matters for your work"). The sequence diagrams help non-technical people follow.

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<!-- column_layout: [1, 8, 1] -->
<!-- column: 0 -->
<!-- alignment: left -->
![image](../assets/axway.png)
<!-- font_size: 5 -->
<!-- column: 1 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
The AI Multiplier
<!-- font_size: 2 -->
MCP + Skills in Action
<!-- no_footer -->
<!-- speaker_note: Welcome everyone. Today we're going to talk about what happens when you stop being the middleware between AI and your systems. -->
<!-- end_slide -->
<!-- column_layout: [1, 3, 1] -->
<!-- column: 1 -->
<!-- alignment: center -->
<!-- font_size: 4 -->
The Copy-Paste Loop
===
<!-- reset_layout -->
<!-- font_size: 2 -->
<!-- alignment: left -->
<!-- new_line -->
<!-- pause -->
Sound familiar?
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
sequenceDiagram
You->>LLM: I'm 10 minutes away from a demo, getting this error
LLM->>You: Try this...
You->>LLM: That didn't work! New error!
LLM->>You: Gather this info..
You->>LLM: Here it is...
LLM->>You: Try this...
loop
You->>LLM:😤
LLM->>You:😭
end
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**You** are the middleware. You copy. You paste. You translate.
The AI is blind, deaf, and handless. You're doing all the work.
<!-- no_footer -->
<!-- speaker_note: Walk through the frustration. Everyone in this room has lived this. -->
<!-- speaker_note: The AI is compelling you to work FOR it — gathering context, running commands, reporting back. -->
<!-- speaker_note: Complex problems need a lot of information, iteration and context. One narrow bandwidth interface doesn't cut it. -->
<!-- end_slide -->
<!-- font_size: 4 -->
MCP: Giving AI Hands
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
**Model Context Protocol** — open standard, created by Anthropic (2024)
<!-- pause -->
<!-- new_line -->
One sentence: **MCP gives tools to AI.**
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
sequenceDiagram
You->>LLM: I'm 10 minutes away from a demo, getting this error
LLM->>You: Let me check that..
LLM->>OCP: Get pod list
LLM->>OCP: Get pod logs
LLM->>ArgoCD: Get GitOps application
LLM->>Git: Get Git repo
LLM->>LLM: Plan fix
LLM->>You: Here is the plan. Requesting Approval
You->>LLM: Approved
LLM->>Git: Push fix to Git
LLM->>OCP: Verify change applied
LLM->>You: Applied Successfully ✅
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**You** approve the plan. **AI** does the legwork.
<!-- no_footer -->
<!-- speaker_note: Quick walk through the sequence diagram -->
<!-- speaker_note: MCP gives the LLM agency to carry out complex, multi-step plans -->
<!-- speaker_note: Collecting and collating from multiple sources -->
<!-- speaker_note: Taking actions, iterating and trying different paths when necessary -->
<!-- speaker_note: Key point: you're still in control. The AI proposes, you approve. -->
<!-- end_slide -->
<!-- font_size: 4 -->
What Can MCP Connect To?
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
Anything with an API. Today, in this room, we have:
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* **OpenShift / Kubernetes** — full cluster operations
<!-- new_line -->
* **Git** (Gitea, GitHub, GitLab) — repos, commits, PRs
<!-- new_line -->
* **ArgoCD** — GitOps application management
<!-- new_line -->
* **SecureTransport** — admin API for file transfer flows
<!-- new_line -->
* **Databases, monitoring, CI/CD, ticketing...**
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
There are 10,000+ MCP servers available. And you can build your own.
<!-- no_footer -->
<!-- speaker_note: Don't dwell on the list. The point is: if it has an API, MCP can bridge it. -->
<!-- speaker_note: The MCP ecosystem is exploding. The standard is winning. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Skills: Giving AI Expertise
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
MCP gives AI **tools**. Skills give AI **knowledge of how to use them well.**
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
graph LR
subgraph WITHOUT["❌ Without Skills"]
direction TB
BP["System Prompt<br/>20,000+ tokens<br/>Everything, always"]
end
subgraph WITH["✅ With Skills"]
direction TB
AP["System Prompt<br/>~500 tokens"]
AP -->|"task matches"| L1["Load: Healthcheck<br/>+2,000 tokens"]
end
style WITHOUT fill:#ffcccc,stroke:#cc0000
style WITH fill:#ccffcc,stroke:#00cc00
style BP fill:#ff6b6b,stroke:#333,color:#fff
style AP fill:#51cf66,stroke:#333,color:#fff
style L1 fill:#4a9eff,stroke:#333,color:#fff
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**Lazy-loaded expertise.** Scan descriptions → load on demand → unload when done.
<!-- no_footer -->
<!-- speaker_note: The problem with stuffing everything into a system prompt: context pollution, cost, degraded quality. -->
<!-- speaker_note: Skills = modular SOPs. The AI loads only what it needs, when it needs it. -->
<!-- end_slide -->
<!-- font_size: 4 -->
A Skill is an SOP
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- column_layout: [1, 1] -->
<!-- column: 0 -->
**Without Skill** 🎲
<!-- new_line -->
> "Check if my server is secure"
<!-- new_line -->
- Runs random checks from training data
- Misses half the important ones
- Suggests changes that break your infra
<!-- pause -->
<!-- column: 1 -->
**With Skill** 📋
<!-- new_line -->
> "Check if my server is secure"
<!-- new_line -->
- Loads healthcheck SKILL.md
- Follows structured audit checklist
- Firewall → SSH → Updates → Services
- Prioritised report with specific fixes
<!-- reset_layout -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**Your best engineer writes it once. Every agent benefits, forever.**
<!-- pause -->
<!-- new_line -->
People leave. Skills persist.
<!-- no_footer -->
<!-- speaker_note: This is the line that lands with the old guard. -->
<!-- speaker_note: Think about tribal knowledge in your team. What happens when that person goes on leave? Changes roles? Leaves the company? -->
<!-- speaker_note: Skills are institutional memory that actually works. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Tools + Skills + Identity
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
graph LR
T["🔧 Tools (MCP)<br/>What can I do?"] --> A["🤖 Agent"]
SP["🧠 Identity (System Prompt)<br/>Who am I?"] --> A
SK["🎯 Skills<br/>How do I do X well?"] --> A
style T fill:#ff6b6b,stroke:#333,color:#fff
style SP fill:#ffd93d,stroke:#333,color:#000
style SK fill:#4a9eff,stroke:#333,color:#fff
style A fill:#51cf66,stroke:#333,color:#fff
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
A workshop full of power tools, no training? Dangerous.
Power tools + SOPs + a qualified operator? **Productive.**
<!-- no_footer -->
<!-- speaker_note: This is the summary slide before the demo. Three layers working together. -->
<!-- end_slide -->
<!-- font_size: 5 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
DEMO
===
<!-- font_size: 2 -->
Watch the AI. Watch me. Neither of us needs the other.
<!-- no_footer -->
<!-- speaker_note: Three demos. Progressively impressive. -->
<!-- speaker_note: Demo 1: Cluster health check via MCP -->
<!-- speaker_note: Demo 2: Skill-driven task (healthcheck or equivalent) -->
<!-- speaker_note: Demo 3: The "figure it out" moment — AI adapts to something unexpected -->
<!-- speaker_note: IMPORTANT: While AI is working, visibly do something else. The multiplier makes itself. -->
<!-- end_slide -->
<!-- font_size: 4 -->
What You Didn't See
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* Every command the AI ran (and there were dozens)
<!-- new_line -->
* Every error it hit and recovered from
<!-- new_line -->
* Every tool it chose — and the ones it considered and rejected
<!-- new_line -->
* The context it carried across steps without being reminded
<!-- new_line -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**That's the loop flip.**
You used to do all of that. Now you approve the plan.
<!-- no_footer -->
<!-- speaker_note: This is the "what just happened" debrief after the demo. -->
<!-- speaker_note: The audience saw the AI work. Now name what they DIDN'T see. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The 3x Multiplier
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- column_layout: [1, 1, 1] -->
<!-- column: 0 -->
<!-- alignment: center -->
**1x**
<!-- new_line -->
You, working.
<!-- new_line -->
The baseline.
<!-- pause -->
<!-- column: 1 -->
<!-- alignment: center -->
**2x**
<!-- new_line -->
You work + AI works.
<!-- new_line -->
Parallel output.
<!-- pause -->
<!-- column: 2 -->
<!-- alignment: center -->
**3x**
<!-- new_line -->
Parallel work + AI adds
value you didn't ask for.
<!-- new_line -->
**Compounded output.**
<!-- reset_layout -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
The person leveraging AI will outcompete the person who isn't.
This isn't a threat. It's an opportunity you're choosing to take — or not.
<!-- no_footer -->
<!-- speaker_note: Don't make this scary. Make it exciting. The opportunity framing matters. -->
<!-- speaker_note: "Someone using AI will outperform someone who isn't" — that's the honest truth. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Next Week
===
<!-- font_size: 2 -->
<!-- new_line -->
<!-- pause -->
You just saw what's possible.
<!-- pause -->
<!-- new_line -->
Next Friday: **how to get this for yourself.**
<!-- pause -->
<!-- new_line -->
CLAUDE.md, system prompts, project context — the practical playbook
for making AI actually understand your work.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
🎯
<!-- no_footer -->
<!-- speaker_note: Tease Week 2. Keep it short. Leave them wanting more. -->
<!-- end_slide -->

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<!-- column_layout: [1, 8, 1] -->
<!-- column: 0 -->
<!-- alignment: left -->
![image](../assets/axway.png)
<!-- font_size: 5 -->
<!-- column: 1 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
Making AI Actually Work
<!-- font_size: 2 -->
CLAUDE.md and the Art of Instruction
<!-- no_footer -->
<!-- speaker_note: Last week: what's possible. This week: how to get it. -->
<!-- speaker_note: Quick recap: MCP gives AI tools, Skills give AI expertise. Today — how to give AI context about YOU and YOUR work. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Why AI Disappoints People
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- column_layout: [1, 1] -->
<!-- column: 0 -->
**What people say:**
<!-- new_line -->
"AI doesn't work."
<!-- new_line -->
"It hallucinates too much."
<!-- new_line -->
"Copilot is useless."
<!-- pause -->
<!-- column: 1 -->
**What's actually happening:**
<!-- new_line -->
"I gave it no context."
<!-- new_line -->
"I asked it to guess."
<!-- new_line -->
"I gave it the wrong tool."
<!-- reset_layout -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
Imagine hiring a brilliant consultant and telling them nothing about your company.
Then being surprised when their advice is generic.
<!-- no_footer -->
<!-- speaker_note: This reframe is critical. Bad tool ≠ bad category. But also: bad instructions ≠ bad tool. -->
<!-- speaker_note: The Copilot → "AI doesn't work" pipeline is real. People blame the category, not the vendor. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Three Levels
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
graph TD
S["🏢 System Level<br/>Who is the AI? What org is this?<br/>Guardrails, conventions, culture"]
P["📁 Project Level<br/>What are we building?<br/>Constraints, decisions, patterns"]
U["👤 User Level<br/>Who am I?<br/>Preferences, style, context"]
S --> P --> U
style S fill:#ff6b6b,stroke:#333,color:#fff
style P fill:#4a9eff,stroke:#333,color:#fff
style U fill:#51cf66,stroke:#333,color:#fff
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
Each level compounds. The AI gets better at every layer.
<!-- no_footer -->
<!-- speaker_note: These aren't abstract. They map directly to files and configuration. -->
<!-- end_slide -->
<!-- font_size: 4 -->
System Level
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
The organisation-wide context. Who is this AI? What does it know?
<!-- pause -->
<!-- new_line -->
**"Be helpful"** → generic, useless
<!-- pause -->
<!-- new_line -->
**"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."**
<!-- pause -->
<!-- new_line -->
→ Now the AI has context that would take a new hire weeks to absorb.
<!-- no_footer -->
<!-- speaker_note: Read the second one aloud. Let it land. That's the difference. -->
<!-- speaker_note: This is what CLAUDE.md IS — the onboarding document for your AI colleague. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Project Level
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
**The "new colleague joins the project" test:**
What would you put in their first-day doc?
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* What are we building and why?
<!-- new_line -->
* What's been decided (and what hasn't)?
<!-- new_line -->
* What are the constraints?
<!-- new_line -->
* Where is everything? (repos, docs, environments)
<!-- new_line -->
* What are the gotchas?
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
Write that document. Put it in CLAUDE.md or AGENTS.md.
Your AI reads it every single session.
<!-- no_footer -->
<!-- speaker_note: The analogy makes it tangible. Everyone knows what onboarding feels like. -->
<!-- speaker_note: If you wouldn't expect a new hire to succeed without this context, why expect AI to? -->
<!-- end_slide -->
<!-- font_size: 4 -->
User Level
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
Personal working style. The compound effect.
<!-- pause -->
<!-- new_line -->
<!-- column_layout: [1, 1] -->
<!-- column: 0 -->
**Without:**
<!-- new_line -->
- Generic tone
- Over-explains basics
- Wrong assumptions
- Feels like talking to a stranger
<!-- pause -->
<!-- column: 1 -->
**With:**
<!-- new_line -->
- Matches your communication style
- Knows your role and expertise level
- Remembers your preferences
- Feels like working with someone who knows you
<!-- reset_layout -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
System + Project + User = AI that feels like a team member, not a chatbot.
<!-- no_footer -->
<!-- speaker_note: This is where it gets personal and relatable. -->
<!-- speaker_note: "Concise answers" vs "walk me through reasoning" — small preference, huge impact over time. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Intent vs. Instruction
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- column_layout: [1, 1, 1] -->
<!-- column: 0 -->
**Vague** 😬
<!-- new_line -->
"Check if my server
is secure"
<!-- pause -->
<!-- column: 1 -->
**Better** 👍
<!-- new_line -->
"Audit SSH config
against CIS benchmarks,
prioritise by severity"
<!-- pause -->
<!-- column: 2 -->
**Best** 🎯
<!-- new_line -->
Write a skill for it.
AI follows the same
checklist every time.
<!-- reset_layout -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
Ambiguity is the enemy of automation.
If you don't define "safe"… the AI will.
<!-- no_footer -->
<!-- speaker_note: Callback to Week 1 skills content. The three levels of prompt quality. -->
<!-- end_slide -->
<!-- font_size: 5 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
DEMO
===
<!-- font_size: 2 -->
Same prompt. Two contexts. Watch what changes.
<!-- no_footer -->
<!-- speaker_note: Demo 1: Before and after CLAUDE.md — same prompt, dramatic difference -->
<!-- speaker_note: Demo 2: Build a CLAUDE.md live with the audience for a real project -->
<!-- speaker_note: PLACEHOLDER: Decide which project/scenario for the live build -->
<!-- end_slide -->
<!-- font_size: 4 -->
Your Homework
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* **This week:** Write a CLAUDE.md for one project you're working on
<!-- new_line -->
* **This week:** Add 3 sentences about your preferences to your AI tool
<!-- new_line -->
* **Next time you're frustrated:** Ask "what context was I not giving it?"
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
These are 10-minute tasks that permanently improve every AI interaction.
<!-- no_footer -->
<!-- speaker_note: Keep it concrete and achievable. Three things, this week. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Next Week
===
<!-- font_size: 2 -->
<!-- new_line -->
<!-- pause -->
Real stories from real people in this room.
<!-- pause -->
<!-- new_line -->
What Dhruv built for $2.50. What Gill discovered in her first hour.
What's actually changing in how we work.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
🎯
<!-- no_footer -->
<!-- speaker_note: Name drop. Create anticipation. People want to hear peer stories. -->
<!-- end_slide -->

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<!-- column_layout: [1, 8, 1] -->
<!-- column: 0 -->
<!-- alignment: left -->
![image](../assets/axway.png)
<!-- font_size: 5 -->
<!-- column: 1 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
Real Stories, Real Results
<!-- font_size: 2 -->
AI at Axway APAC — What's Actually Happening
<!-- no_footer -->
<!-- speaker_note: Last week: how to instruct AI. This week: proof it works. From people you know. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Bedrock Trial — One Month In
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
5 people. Different roles. Same tool. One month.
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* Usage patterns varied wildly by role (as expected)
<!-- new_line -->
* Consistent feedback: **"This is what AI should have been all along"**
<!-- new_line -->
* Two unsolicited "this is SO much better than Copilot" messages — within the first hour
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
That last point matters. Nobody asked them for feedback. They volunteered it.
<!-- no_footer -->
<!-- speaker_note: Let the numbers and reactions speak. Don't oversell. -->
<!-- speaker_note: PLACEHOLDER: Add specific usage/cost data if appropriate by this date -->
<!-- end_slide -->
<!-- font_size: 4 -->
Dhruv's Time Tracker
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
**The problem:** Corporate timesheet system. Terrible UI. 15 minutes a day of pain.
<!-- pause -->
<!-- new_line -->
**Attempt 1 — Copilot 365:**
More time fighting the tool than just filling in the timesheet manually.
"Would you like me to help you think about possibly..."
<!-- pause -->
<!-- new_line -->
**Attempt 2 — Claude, Day 1:**
Specified requirements. Built a custom local program. Works exactly how his brain works.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 3 -->
**Cost: $2.50. One time.**
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
For someone billed out at thousands per day.
That's not a tool. That's arbitrage.
<!-- no_footer -->
<!-- speaker_note: This is the story that makes builders lean forward. -->
<!-- speaker_note: The contrast with Copilot is the key — same person, same task, different tool, completely different outcome. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Gill's First Hour
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
Gill — the person everyone goes to for answers.
Decades of institutional knowledge. Client relationships. The kind of expertise that takes years to build.
<!-- pause -->
<!-- new_line -->
**Her reaction, 60 minutes in:**
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 3 -->
"It's like a consulting service"
<!-- pause -->
<!-- new_line -->
<!-- font_size: 3 -->
"I CAN NEVER GO BACK TO COPILOT!!!!!!!!!!!!!!!!"
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
That's not polite feedback. That's a professional assessment
from someone who knows what good advisory looks like.
<!-- no_footer -->
<!-- speaker_note: Let the quotes do the work. Gill's credibility in this room is the proof. -->
<!-- speaker_note: "Consulting service" — from the person who IS the consulting service. That's recognition. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Saori's AI Integration
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
Joined two years ago as a junior. Toyota engagement, Japanese language requirement.
<!-- pause -->
<!-- new_line -->
Now: building a **complex AI integration** — her first AI project.
Not a chatbot. Not a demo. Production-grade, customer-facing.
<!-- pause -->
<!-- new_line -->
**With Claude as her baseline from Day 1.**
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
The tool you start with shapes what you think is possible.
<!-- pause -->
<!-- new_line -->
She will never accept less. And that's the point.
<!-- no_footer -->
<!-- speaker_note: Saori is the "next generation" story. Junior → building production AI in 2 years. -->
<!-- speaker_note: The tool shapes the builder. Start people on a good tool and they build good things. -->
<!-- end_slide -->
<!-- font_size: 4 -->
Capturing Tribal Knowledge
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
We have a SecureTransport flow engineering skill.
<!-- pause -->
<!-- new_line -->
Months of tribal knowledge — API quirks, deployment patterns, testing harnesses, error log locations, PGP encryption flows.
<!-- pause -->
<!-- new_line -->
Written once. Available to every AI agent, instantly.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**What tribal knowledge exists in your team right now that only one person holds?**
<!-- pause -->
<!-- new_line -->
What happens when they go on leave? Change roles? Leave?
<!-- no_footer -->
<!-- speaker_note: This is the "people leave, skills persist" callback from Week 1. -->
<!-- speaker_note: Make it personal. Everyone in the room knows knowledge that isn't documented. -->
<!-- speaker_note: PLACEHOLDER: Decide how deep to go on ST story. Adjust based on audience engagement. -->
<!-- end_slide -->
<!-- font_size: 4 -->
From the Room
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
**Who else has a story?**
<!-- new_line -->
Something you built. Something that surprised you.
A moment where AI actually saved you time or changed how you work.
<!-- new_line -->
<!-- pause -->
Don't be shy. The best use cases come from people solving their own problems.
<!-- no_footer -->
<!-- speaker_note: Open it up. By week 3, the pilot group will have stories. Others might too. -->
<!-- speaker_note: PREP: Seed Dhruv, Saori, Neo in advance. Ask if they want to share something briefly. -->
<!-- speaker_note: If the room is quiet, have backup prompts ready: "Has anyone used it for email drafting? Documentation? Code review?" -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Bigger Picture
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
Axway came back from the Paris AI Forum with a clear message:
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 3 -->
**"AI or bust."**
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
This isn't an experiment. The company is institutionally serious.
<!-- pause -->
<!-- new_line -->
We invested in Claude on Bedrock because we believe in giving you the best tool, not the cheapest one.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
Competitors are moving. Standing still is falling behind.
<!-- no_footer -->
<!-- speaker_note: Connect the individual stories to the company direction. -->
<!-- speaker_note: "AI or bust" is the Paris takeaway. Make it real. -->
<!-- speaker_note: PLACEHOLDER: Add 2-3 specific industry examples of AI transformation. Research closer to date. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Uncomfortable Truth
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
This is not "AI will replace you."
<!-- pause -->
<!-- new_line -->
This is **"someone using AI will outperform someone who isn't."**
<!-- pause -->
<!-- new_line -->
Dhruv saved 15 minutes a day on timesheets. That's 60+ hours a year.
What did he do with that time? **More valuable work.**
<!-- pause -->
<!-- new_line -->
The multiplier isn't about doing more. It's about doing **better**.
<!-- no_footer -->
<!-- speaker_note: This is the most important slide in the series. -->
<!-- speaker_note: Don't make it scary. Make it empowering. The choice is theirs. -->
<!-- speaker_note: The old guard needs to hear "this makes your expertise MORE valuable, not less." -->
<!-- end_slide -->
<!-- font_size: 4 -->
Next Week — Your Turn
===
<!-- font_size: 2 -->
<!-- new_line -->
<!-- pause -->
You've seen what's possible. You've seen how. You've heard the stories.
<!-- pause -->
<!-- new_line -->
Next Friday: **What would YOU build?**
<!-- pause -->
<!-- new_line -->
Come with ideas. Come with problems. Come with that thing that wastes your time every week.
We're going to figure it out together.
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 2 -->
🎯
<!-- no_footer -->
<!-- speaker_note: Set expectations. They need to come prepared to participate. -->
<!-- speaker_note: "That thing that wastes your time every week" — seed the thinking now. -->
<!-- end_slide -->

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<!-- column_layout: [1, 8, 1] -->
<!-- column: 0 -->
<!-- alignment: left -->
![image](../assets/axway.png)
<!-- font_size: 5 -->
<!-- column: 1 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
What Could You Build?
<!-- font_size: 2 -->
Ideas, Problems, and Possibilities
<!-- no_footer -->
<!-- speaker_note: Final session. Interactive. The room drives this one. -->
<!-- speaker_note: Quick recap: Week 1 — what's possible. Week 2 — how to instruct AI. Week 3 — real stories. Week 4 — your turn. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Story So Far
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* **Week 1:** MCP gives AI tools. Skills give AI expertise. The 3x multiplier is real.
<!-- new_line -->
* **Week 2:** Context is everything. CLAUDE.md turns generic AI into a team member.
<!-- new_line -->
* **Week 3:** Dhruv built a tool for $2.50. Gill can't go back. Saori is building the future.
<!-- new_line -->
<!-- pause -->
<!-- alignment: center -->
Now: **what's YOUR version?**
<!-- no_footer -->
<!-- end_slide -->
<!-- font_size: 4 -->
Things You Might Not Know Are Possible
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* **Scheduled AI work** — "Every Monday morning, summarise last week's tickets and email me the report"
<!-- new_line -->
* **Cross-platform automation** — AI in a container reaches out to a Mac, runs AppleScript, creates calendar events
<!-- new_line -->
* **Multi-agent orchestration** — main agent delegates specialist tasks to focused sub-agents
<!-- new_line -->
* **Browser automation** — AI navigates web UIs, fills forms, extracts data
<!-- new_line -->
* **Event-driven AI** — monitoring alert fires → AI investigates → produces a report before you wake up
<!-- new_line -->
* **Voice interaction** — AI generates spoken briefings, reads summaries aloud
<!-- new_line -->
* **Workflow integration** — n8n / automation platforms with AI decision points in the flow
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
All of this is real, working, today.
<!-- no_footer -->
<!-- speaker_note: Don't demo these — just name them. Let imaginations run. -->
<!-- speaker_note: The goal is to break the "chatbot" mental model. AI can DO things, not just answer questions. -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Question
===
<!-- font_size: 2 -->
<!-- new_line -->
<!-- pause -->
<!-- alignment: center -->
Think about your week.
<!-- pause -->
<!-- new_line -->
**What's repetitive?**
<!-- pause -->
<!-- new_line -->
**What's tedious?**
<!-- pause -->
<!-- new_line -->
**Where are you the middleware between two systems?**
<!-- pause -->
<!-- new_line -->
**What knowledge is trapped in one person's head?**
<!-- no_footer -->
<!-- speaker_note: Pause between each question. Let them think. -->
<!-- speaker_note: These are the prompts for the group exercise. -->
<!-- end_slide -->
<!-- font_size: 5 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
GROUP EXERCISE
===
<!-- font_size: 2 -->
Groups of 3-4. Pick your best idea. 15 minutes.
<!-- no_footer -->
<!-- speaker_note: Break into groups (or breakout rooms if virtual) -->
<!-- speaker_note: Each group picks ONE idea to present back -->
<!-- speaker_note: Float between groups. Nudge. Ask "what wastes your time?" -->
<!-- speaker_note: FALLBACK: If groups don't work, do facilitated brainstorm: go around the room, one idea each -->
<!-- end_slide -->
<!-- font_size: 5 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
SHARE BACK
===
<!-- font_size: 2 -->
~2 minutes each. What's the idea? Why does it matter?
<!-- no_footer -->
<!-- speaker_note: Each group presents. React honestly: -->
<!-- speaker_note: "That's a Tuesday afternoon project" / "That's a skill" / "That needs MCP" / "That's bigger but worth it" -->
<!-- speaker_note: Capture everything visibly — shared doc or whiteboard -->
<!-- speaker_note: Ask: "Who wants to own this one?" — identify champions -->
<!-- end_slide -->
<!-- font_size: 4 -->
What Happens Next
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
I'm taking a few weeks off soon. 👶
<!-- pause -->
<!-- new_line -->
The AI initiative **doesn't stop.**
<!-- pause -->
<!-- new_line -->
<!-- incremental_lists: true -->
* Bedrock access continues — keep using it
<!-- new_line -->
* CLAUDE.md templates available for your projects
<!-- new_line -->
* Skill creation guide available if you want to capture expertise
<!-- new_line -->
* Champions from today's session — you know who you are
<!-- new_line -->
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
When I come back, I want to hear what you built.
<!-- no_footer -->
<!-- speaker_note: Congratulations moment for baby. Keep it brief and warm. -->
<!-- speaker_note: The handoff needs to feel empowering, not abandoning. -->
<!-- speaker_note: PLACEHOLDER: Decide on continuity mechanism — Slack/Teams channel, shared doc, named champion(s) -->
<!-- end_slide -->
<!-- font_size: 4 -->
The Series in One Slide
===
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
```mermaid +render +width:100%
graph LR
T["🔧 Give AI Tools<br/>(MCP)"] --> S["🎯 Give AI Expertise<br/>(Skills)"]
S --> C["🧠 Give AI Context<br/>(CLAUDE.md)"]
C --> Y["🚀 Give AI YOUR Problems<br/>(Today)"]
style T fill:#ff6b6b,stroke:#333,color:#fff
style S fill:#4a9eff,stroke:#333,color:#fff
style C fill:#ffd93d,stroke:#333,color:#000
style Y fill:#51cf66,stroke:#333,color:#fff
```
<!-- pause -->
<!-- new_line -->
<!-- alignment: center -->
<!-- font_size: 3 -->
The person leveraging AI will outcompete the person who isn't.
<!-- font_size: 2 -->
<!-- pause -->
<!-- new_line -->
That was always the point. Now you have the tools to do it.
<!-- no_footer -->
<!-- speaker_note: Full circle. Callback to the recurring motif. -->
<!-- speaker_note: End with energy, not a whimper. This is the launch, not the conclusion. -->
<!-- end_slide -->
<!-- column_layout: [1, 8, 1] -->
<!-- column: 0 -->
<!-- column: 1 -->
<!-- jump_to_middle -->
<!-- alignment: center -->
<!-- font_size: 3 -->
Thank you. Now go build something.
<!-- new_line -->
<!-- font_size: 2 -->
🎯
<!-- no_footer -->
<!-- end_slide -->