Workshop 01 gives you the foundations. This session goes deeper into the skills that matter day to day: writing prompts that work reliably, understanding what different LLMs are good at, when to use which tool, how to spot weak output, and how to handle data sensibly across providers. Still plain English — not a developer course — but substantive enough that your team stops guessing.
Structure, context, constraints, and examples. Why vague prompts produce vague output — and how to write prompts your colleagues can reuse.
What separates models in plain terms: reasoning, speed, context length, multimodal, cost. When to reach for which — and when a simpler tool is enough.
Build a starter library for your business — tone of voice, output format, review checklists. Patterns for drafting, summarising, extracting, and assessing.
Red flags, verification habits, and when to regenerate vs rewrite. What "good enough" looks like for different task types.
What can go into which tool, enterprise vs consumer accounts, retention settings, and agreeing sensible rules for your team.
Rewrite prompts for real tasks from the room. Agree a shared prompt library and model guide for the next 90 days.