Install
$ agentstack add mcp-timothywarner-org-prompt-pro ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
How to Prompt Like a Pro: Master AI for Business Innovation
[](https://techtrainertim.com) [](https://github.com/timothywarner) [](https://www.linkedin.com/in/timothywarner/)
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: June 2026
Course Segments
| # | Segment | Duration | Key Topics | |---|---------|----------|------------| | 1 | [Identity, Mindset & Context Foundations](segments/segment-1-identity-mindset-context/) | 50 min | Pilot/co-pilot, anchor trap, prompt smell, context disclosure, inference | | 2 | [Context Sculpting & Prompting Technique](segments/segment-2-context-sculpting-technique/) | 50 min | Role-play, task decomposition, few-shot, chain-of-thought, meta-prompting | | 3 | [Workflow, Multimodal & Security](segments/segment-3-workflow-multimodal-security/) | 50 min | Custom instructions, prompt versioning, voice, cross-referencing, privacy | | 4 | [Agentic Orchestration & Resilience](segments/segment-4-agentic-orchestration/) | 50 min | LLM matching, subagents, checkpoints, MCP, Copilot Studio, breaking changes |
Warner's Laws of Generative AI Prompting
- 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.
Context Engineering vs Prompt Engineering
| 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.
Tools Covered
Primary Platforms
- Microsoft 365 Copilot - Notebooks, Agents, enterprise integration
- ChatGPT - Projects, Custom GPTs, GPT Image 2, Vision
- Google Gemini - Gems, Imagen 4, ~1M-token context (Gemini 3.1 Pro)
- Claude - Projects, long-form analysis, Claude Code
Agentic AI
- 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
Prerequisites
Required
- Internet connection
- ChatGPT free account
- Google account
Recommended
- Microsoft 365 Copilot license
- Claude Pro
- GitHub Copilot subscription
- VS Code
Quick Start
CRAFT Framework
Context: [situation]
Role: You are a [role]
Action: [task]
Format: [output format]
Tone: [voice/style]
Example Prompt
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.
Repository Structure
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-JUNE-2026.md # June 2026 delivery plan
For instructors: See [INSTRUCTOR-MANIFEST.md](docs/INSTRUCTOR-MANIFEST.md) for delivery guide. For agents: Review [AGENTS.md](AGENTS.md) and [CLAUDE.md](CLAUDE.md) before editing lessons.
Resources
- Anthropic Context Engineering Guide
- OpenAI Prompt Engineering Guide
- GitHub Copilot Custom Instructions
- MCP Specification
License & Contributing
Licensed under [MIT](LICENSE). See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines and [AGENTS.md](AGENTS.md) for the agent-focused repository playbook.
Code of Conduct
Participation in this project is governed by the [Code of Conduct](CODEOFCONDUCT.md).
Security
Found a vulnerability or risky prompt scenario? Follow the disclosure steps in [SECURITY.md](SECURITY.md) or email Tim directly at tim@techtrainertim.com.
Repo Guides & Automation
- [AGENTS.md](AGENTS.md) - Contributor playbook
- [CLAUDE.md](CLAUDE.md) - Copilot instructions
- [INSTRUCTOR-MANIFEST.md](docs/INSTRUCTOR-MANIFEST.md) - Run-of-show notes
- [COURSE-PLAN-JUNE-2026.md](COURSE-PLAN-JUNE-2026.md) - June 2026 delivery plan
- [markdownlint.json](markdownlint.json) & [Markdownlint workflow](.github/workflows/markdownlint-autofix.yml) - spacing rules + one-click lint/autofix
Ready to prompt like a pro? Let's transform how you work wi h AI!
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: timothywarner-org
- Source: timothywarner-org/prompt-pro
- License: MIT
- Homepage: https://techtrainertim.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.