LLM Foundations for Product & Customer Experience Teams
Practical understanding of large language models for non-technical team members. Learn how AI systems work, what they can and cannot do, and how to communicate effectively about AI-powered features.
Customer Services — Feb 23–24, 2026 — RemoteWhat You'll Learn
Understand AI Fundamentals
How LLMs work, mental models for reasoning about AI behavior
Communicate with Confidence
Explain AI features to customers, handle objections, set expectations
Write Effective Prompts
Structured techniques, common mistakes, diagnostic processes
Navigate Security & the AI Landscape
Data privacy, responsible AI, evaluating claims
Understand Agents & RAG Bonus
AI systems that take action, retrieval-augmented generation, grounding in real data
Evaluate & Improve AI Bonus
Metrics, test cases, structured feedback, the improvement cycle
Explore This Site
Exercises
Guided prompt engineering exercises using BigHand Workflow scenarios. Step through prompts, observe AI responses, and compare outputs.
Materials
Slide decks for all 7 core modules plus 3 bonus modules, exercise worksheets, the complete course book, and self-assessments.
Sandbox
Experiment freely with prompts and model settings. No guided steps — just you and the LLM.
LLM Status
The status indicator in the header shows whether you're getting real AI responses or simulated output.
Session Schedule
GMT / local Notifications enabled| Time | Duration | Content | Timer |
|---|---|---|---|
| 2:00 – 2:15 | 15 min | Welcome & Introductions | |
| 2:15 – 2:55 | 40 min | Module 1: AI Fundamentals | |
| 2:55 – 3:25 | 30 min | Module 2: Mental Models | |
| 3:25 – 3:45 | 20 min | Workshop: Diagnose & Explain | |
| 3:45 – 4:00 | 15 min | Break | |
| 4:00 – 5:00 | 60 min | Module 3: Customer Communication | |
| 5:00 – 5:45 | 45 min | Module 4: Prompt Fundamentals (Part 1) | |
| 5:45 – 6:00 | 15 min | Day 1 Wrap-Up |
| Time | Duration | Content | Timer |
|---|---|---|---|
| 2:00 – 2:15 | 15 min | Day 1 Recap | |
| 2:15 – 3:00 | 45 min | Module 4: Prompt Fundamentals (Part 2) | |
| 3:00 – 4:30 | 90 min | Module 5: Prompt Engineering Workshop | |
| 4:30 – 4:45 | 15 min | Break | |
| 4:45 – 5:45 | 60 min | Modules 6+7: Security, Ethics & AI Landscape | |
| 5:45 – 6:00 | 15 min | Final Q&A & Next Steps |
These modules are provided as additional reading. They may be covered live if time permits or used for follow-up sessions.
| Time | Duration | Content |
|---|---|---|
| — | 45 min | Module 8: Introduction to AI Agents |
| — | 5 min | Break |
| — | 45 min | Module 9: RAG, Knowledge & Grounding |
| — | 5 min | Break |
| — | 45 min | Module 10: Evaluating & Improving AI |
| — | 15 min | Final Q&A & Course Wrap-Up |
Prompt Engineering Exercises
Explore how prompt design affects LLM output using BigHand Workflow scenarios
💬 Discussion Questions
Course Materials
Slide decks, exercises, and reference materials for the LLM Foundations course
Prompt Sandbox
Experiment freely with prompts and inputs — no guided steps
Session History
Data Generator
Create synthetic training data and few-shot examples for your prompts
No seed examples yet. Add examples to guide generation style.
No examples yet
Configure your task and click "Generate Examples" to create synthetic training data.