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LLM Context Engineering for Testers

Full-Day Tutorial (6 hours)

LLMs don’t read your mind. They test with what you feed them.

Timetable

8:30 a.m. – 4:30 p.m. Monday 24th

Room

F-,E- & D-Rooms

Artificial Intelligence (AI)

Audience

Testers, Developers, and Anyone curious about how LLMs can go from party trick to test partner.

Required

Laptop with RDP access, ChatGPT/Claude/Gemini paid account, curiosity, caffeine.

Key-Learnings

  • Prompt LLMs to generate sharp, scoped test ideas
  • Inject real context (requirements, bugs, risks) into test conversations
  • Structure YAML/JSON pipelines for reusable test generation
  • Build a Langchain agent that acts like a thinking test consultant
  • Evaluate and tune LLM output quality for real-world use

Stop Prompting Like a Noob

Everyone's using ChatGPT to write tests. Most are doing it wrong.

This workshop takes you beyond “write test cases for login” and into the art of Context Engineering. This is where you teach the LLM what matters before you ask it what to do.

We’ll start simple: prompt like a pro. We do this until the prompt tricks stop working and context starts to matter. We then level up fast: inject SRS logic, layer bug taxonomies, pull CVEs on the fly, and wire it all up into a Langchain agent that remembers, reasons, and retrieves.

Expect more hands-on exercises than we’ll have time for, one meaty case study, and zero slide fatigue. By the end, you’ll stop treating an LLM like a vending machine and start using it like a context-driven test collaborator.

This isn’t AI hype. It’s applied thinking, powered by language models, grounded in test design.

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