---
title: "Context sensitivity and reasoning failures"
course: "AI103 · Prompting that works"
unit: "How LLMs work (and fail)"
lesson: 10 of 35
source: https://open.maestrocollege.edu/prompting-that-works/context-sensitivity-and-reasoning-failures
publisher: Maestro College
---

# Context sensitivity and reasoning failures

Lesson 10 of 35 in **Prompting that works** (AI103), unit "How LLMs work (and fail)". An open lesson from Maestro College.

## What the learner will be able to do
- Identify context sensitivity: how small changes in wording, order, or placement of information change a model's output.
- Identify inconsistent reasoning, such as contradictions or wrong steps behind a confident answer, and understand why it emerges from next-token prediction.
- Classify a flawed LLM output by failure mode (hallucination, bias, non-determinism, context sensitivity, or inconsistent reasoning) and name the model characteristic that most likely caused it.

## Teaching notes
Role-play a generic LLM answering slightly reworded versions of the same prompt, then step out of role to show how the wording shifted your prediction.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 10 complete: Context sensitivity and reasoning failures."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Anatomy of a strong prompt" (lesson 11 of 35), and give the learner its link: https://open.maestrocollege.edu/prompting-that-works/anatomy-of-a-strong-prompt.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: Why models hallucinate and show bias
Next lesson: Anatomy of a strong prompt