An O'Reilly Live Learning course teaching business professionals how to extract maximum value from AI tools like Microsoft 365 Copilot, ChatGPT, Claude, and Google Gemini.
Last updated: April 2026
| # | Segment | Duration | Key Topics |
|---|---|---|---|
| 1 | Identity, Mindset & Context Foundations | 50 min | Pilot/copilot, anchor trap, prompt smell, context disclosure, inference |
| 2 | Context Sculpting & Prompting Technique | 50 min | Role-play, task decomposition, few-shot, chain-of-thought, meta-prompting |
| 3 | Workflow, Multimodal & Security | 50 min | Custom instructions, prompt versioning, voice, cross-referencing, privacy |
| 4 | Agentic Orchestration & Resilience | 50 min | LLM matching, subagents, checkpoints, MCP, Copilot Studio, breaking changes |
- You are the pilot; the AI is your co-pilot. You're responsible for its actions.
- Always know who you're signed in as and who you're chatting with.
- Beware the anchor trap — draft before you prompt.
- Trust your gut — never hesitate to second-guess the AI.
- Every AI chat has its own lifecycle; develop your "prompt smell."
- The more you disclose in trust, the more the AI can help you.
- Anything you leave out of your prompt will be inferred by the AI.
- Surgically sculpt your context. Just because you can doesn't mean you should.
- Role play like you're a director.
- Don't swallow the elephant — break down complex tasks with the AI.
- Show, don't tell — lead with examples.
- Make the AI show its work.
- Think meta: prompt about prompting and custom instructions.
- Strike while the iron's hot.
- If you need to remind the AI of something, add it to custom instructions.
- Periodically refactor your custom instructions and memories.
- Treat prompts as assets — version-control them.
- Use your voice if using words is difficult.
- Pick up a good book on technical writing.
- Always have a trusted LLM to cross-reference responses.
- Protect your LLM against abuse by integrating test prompts.
- Protect privacy ruthlessly. Know your chat storage, licensing, and data retention.
- Each LLM has its own personality. Match the tool to the task.
- Orchestrate subagents as force multipliers. Use git worktrees for parallelism.
- Checkpoint before consequence — autonomous does not mean unsupervised.
- Expect breaking changes. Stay agile, adaptable, and be an eternal learner.
| Prompt Engineering | Context Engineering |
|---|---|
| Focus on what to say | Focus on what the model knows |
| One-off interactions | System-wide reliability |
| Phrasing and examples | Everything in the context window |
Key Insight: Most AI failures aren't model failures—they're context failures.
- Microsoft 365 Copilot — Notebooks, Agents, enterprise integration
- ChatGPT — Projects, Custom GPTs, DALL-E 3, Vision
- Google Gemini — Gems, Imagen 3, 1M+ token context
- Claude — Projects, long-form analysis, Claude Code
- Claude Code — Terminal-based autonomous coding with checkpoints
- GitHub Copilot Coding Agent — Issue-to-PR cloud automation
- M365 Copilot Studio — Enterprise multi-agent orchestration
- Azure AI Foundry — Azure-hosted model deployment and orchestration
- Internet connection
- ChatGPT free account
- Google account
- Microsoft 365 Copilot license
- Claude Pro
- GitHub Copilot subscription
- VS Code
Context: [situation]
Role: You are a [role]
Action: [task]
Format: [output format]
Tone: [voice/style]
Context: I'm preparing a quarterly business review for my VP.
Role: You are a senior business analyst.
Action: Analyze this sales data and identify the top 3 trends.
Format: Executive summary with bullet points, max 200 words.
Tone: Professional and data-driven.
docs/ # Reference guides + slide deck
images/ # Cover art, social preview assets
segments/
├─ segment-1-identity-mindset-context/ # Laws 1-7, anchor trap, context foundations
├─ segment-2-context-sculpting-technique/ # Laws 8-14, few-shot, chain-of-thought
├─ segment-3-workflow-multimodal-security/ # Laws 15-22, versioning, privacy
└─ segment-4-agentic-orchestration/ # Laws 23-26, subagents, MCP demos
.github/ # Issue templates, workflows, AI instructions
COURSE-PLAN-APRIL-2026.md # April 2026 delivery plan
For instructors: See INSTRUCTOR-MANIFEST.md for delivery guide.
For agents: Review AGENTS.md and CLAUDE.md before editing lessons.
- Anthropic Context Engineering Guide
- OpenAI Prompt Engineering Guide
- GitHub Copilot Custom Instructions
- MCP Specification
Licensed under MIT. See CONTRIBUTING.md for guidelines and AGENTS.md for the agent-focused repository playbook.
Participation in this project is governed by the Code of Conduct.
Found a vulnerability or risky prompt scenario? Follow the disclosure steps in SECURITY.md or email Tim directly at tim@techtrainertim.com.
- AGENTS.md - Contributor playbook
- CLAUDE.md - Copilot instructions
- INSTRUCTOR-MANIFEST.md - Run-of-show notes
- COURSE-PLAN-APRIL-2026.md - April 2026 delivery plan
- markdownlint.json & Markdownlint workflow - spacing rules + one-click lint/autofix
Ready to prompt like a pro? Let's transform how you work with AI!
