Working with LLMs¶

LLMs have become genuinely useful research tools in a short time, and genuinely misleading ones when used without care. The difference is almost entirely in how you use them. This track covers where they add real value, where they fail, and how to build habits that keep you in control of your work.

Lessons¶

• Lesson 01: What LLMs Are and Are Not: How LLMs work at a high level, what hallucination means, and why confidence does not imply correctness.
• Lesson 02: LLMs for Code: Pair programming, debugging, and code review, with a verification mindset.
• Lesson 03: LLMs for Writing: Drafting versus authoring, when assistance is appropriate, and academic integrity.
• Lesson 04: LLMs for Literature Search: Why you must never trust LLM-generated citations without checking the source.
• Lesson 05: Prompt Engineering for Research: Writing effective prompts for summarisation, explanation, and brainstorming.
• Lesson 06: Verification Habits: A checklist for reviewing LLM output before using it in research.
• Lesson 07: Skill Files: Encoding project context, conventions, and style rules as persistent LLM documents, with a coding template and a HEP writing skill file.