How do you actually use AI at work?
AI won't make you faster at the wrong things. The professionals who get real value from AI aren't the ones with the most tools. They're the ones with a system for thinking about their work differently.
That system starts with a question most people skip: which parts of my work need my judgment, and which parts can AI handle? When you get that distinction right, everything changes. You stop asking AI random questions and start building workflows that handle entire processes.
What is the CRAFTER SuperPrompt Framework?
The CRAFTER framework is a structured method for briefing AI that turns vague prompts into reliable, repeatable results. It's the difference between getting lucky once and getting consistent quality every time.
- Context
What's the situation? What are you trying to achieve? Give AI the background it needs to understand your world. A prompt without context is a shot in the dark.
- Role
What expertise should the AI bring? "Act as a senior HR consultant with experience in Belgian employment law" produces fundamentally different output than "help me write an email."
- Action
What specifically should it do? Be precise. "Analyse this data and identify the three most significant trends" beats "look at this" every time.
- Format
How should it present the result? A bullet list, a narrative, a table, a one-page summary? The format shapes the thinking.
- Target audience
Who is this for? Writing for a C-suite audience requires different language than writing for a technical team. Tell AI who's reading.
- Examples
Show what good looks like. One concrete example teaches AI more than a paragraph of instructions.
- Refining
Build in feedback loops. "After your first draft, ask me three questions to improve accuracy." The best results come from iteration, not perfection on the first try.
The CRAFTER framework is at the heart of my book Build Bot Brains: How Superprompts Make AI Your Ally. It works with any AI platform — ChatGPT, Claude, Gemini, Copilot. The method stays the same even when the tools change.
Get the bookHow are AI agents different from chatbots?
There's a shift happening that most people haven't caught yet. We're moving from asking AI questions to directing AI workflows.
A chatbot waits for your input and gives you a response. An AI agent takes an objective, breaks it into steps, uses tools, and delivers a result. The difference is like the difference between asking someone for directions and hiring a driver who knows the route.
In Finally, Superpowers!, I call this "the team in your laptop." One person with the right agent setup can handle research, analysis, drafting, formatting, and distribution — work that used to take a team of five and a week of back-and-forth.
But here's the part nobody talks about: the person directing those agents needs to think clearly about what matters. Agents amplify your intentions. If your intentions are scattered, your agents will be too.
What tools and techniques do I teach?
Prompt engineering — Not just writing better prompts, but building a system for consistent results. The CRAFTER framework, superprompts, and quality rubrics that make AI output reliable enough to trust.
Workflow automation — Using platforms like n8n to connect AI to your existing tools. Email processing, content pipelines, data analysis, client communication — automated with AI in the loop where it adds value.
AI-assisted content creation — From first draft to final version, using AI as a writing partner that handles structure and research while you bring voice, judgment, and expertise.
Model Context Protocol (MCP) — Connecting AI directly to your databases, documents, and business tools. This is where AI stops being a separate application and becomes part of how you work.
Why does collecting tools fail without a system?
There's a pattern I see in almost every team I work with. Someone discovers a new AI tool, gets excited, uses it for a week, and then forgets about it. Three months later, they discover another tool. Same cycle.
The problem isn't the tools. The problem is that nobody stopped to ask: what am I actually trying to accomplish, and what does a good workflow look like?
This is what I call the AI Tool Trap. The cure isn't fewer tools or more tools. It's stepping back far enough to see the system. In my workshops, we call that moment the Sacred Pause — the discipline of thinking before automating.
Where do I start?
What comes next?
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