Technical practice
Explaining Prompt Engineering Fundamentals
What to coverDescribe how you would explain the concept of 'context window' and 'system instructions' to a non-technical beginner. Focus on using relatable analogies to help them understand how LLMs process information and why specific prompt structures yield better results.
Claude Artifacts and Projects Workflow
What to coverExplain the practical utility of Claude Artifacts for business users. Discuss how you would demonstrate the transition from a simple chat response to a functional, rendered output like a document or a dashboard.
Designing Agentic Workflows with n8n or Make
What to coverWalk through the logic of building a multi-step automation using a tool like n8n. Focus on how you handle error states, data mapping between different APIs, and ensuring the workflow remains maintainable for the end user.
Vibe Coding and AI-Assisted Development
What to coverExplain your approach to teaching 'vibe coding' using tools like Cursor or Claude Code to someone without a traditional engineering background. Highlight how you manage the abstraction of code while ensuring the learner understands the underlying structure of the application they are building.
Troubleshooting AI Hallucinations
What to coverWhen a learner encounters an incorrect or hallucinated output during a live session, what is your step-by-step process for troubleshooting? Focus on identifying whether the issue stems from the prompt, the model's limitations, or the provided context.
Responsible AI and Data Privacy
What to coverHow do you coach learners on the risks of inputting sensitive corporate data into public LLMs? Discuss the balance between leveraging AI for productivity and maintaining organizational data security standards.
Rapid Prototyping Strategies
What to coverDescribe a scenario where you would use AI to rapidly prototype a business solution. Explain how you decide which tools (e.g., Power Automate vs. n8n) are most appropriate based on the client's existing tech stack.
Evaluating Model Outputs
What to coverWhat framework do you use to teach learners how to verify and validate AI-generated content? Discuss the importance of human-in-the-loop processes and critical thinking when reviewing AI-assisted work.
Behavioural practice
Adapting Training for Diverse Audiences
What to coverDescribe a time you had to adjust your teaching style for a group with mixed technical proficiency. Explain the situation, the specific adjustments you made to your delivery, and the result in terms of learner engagement or comprehension.
Handling Technical Failures During Live Demos
What to coverTell me about a time a live demonstration or hands-on exercise did not go as planned due to a technical issue. How did you handle the situation in front of the learners, and what steps did you take to resolve it?
Facilitating Hands-on Learning
What to coverProvide an example of how you have guided a learner through a complex task until they achieved a 'lightbulb moment.' Focus on your approach to patience, scaffolding the information, and ensuring they felt confident to replicate the task independently.
Staying Current with Rapid AI Changes
What to coverThe AI landscape evolves weekly. Describe your personal process for keeping your own skills sharp and how you translate those updates into actionable curriculum changes for your students.