Context & Mental Models

How AI sees your prompts

Lesson Guide

literacy

Working memory for AI

LLMs do not remember your whole project. They reason over the context you provide in the current prompt. Smaller, focused tasks produce better output than giant requests.

What to include

Give the goal, relevant files or constraints, expected output format, and one clear deliverable. Remove unrelated history unless it changes the answer.

Practice pattern

Before prompting for code, write a one-paragraph plan in plain English. If the plan needs more than three features, split it into separate prompts.

Success checklist

Defines relevant context explicitly
Limits the task to one outcome
Requests a scannable response format

Error & Debugging Simulator

Read the stack trace and craft a prompt for the AI to fix it.

CONSOLE LOGS (Next.js Hydration Mismatch)

Error: Hydration failed because the initial UI does not match what was rendered on the server.
  - Expected server HTML: <div>2026-07-20T17:47:00</div>
  - Actual client HTML: <div>2026-07-20T22:47:00</div>
  at Page (src/app/page.tsx:18:24)

External Tool Hub

Open external generators & LLMs to run your code drafts.

Claude (Anthropic)LLM

Ideal for complex reasoning, architectural prompt engineering, and clean code generation.

ChatGPT (OpenAI)LLM

Versatile AI assistant for quick code snippets, logic brainstorming, and step-by-step guidance.

Lesson Tutor

Ask for hints, debugging guidance, or one small next iteration.

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4-Step Instructional Vibe Loop

Follow the structured loop: Plan ➔ Draft Prompt ➔ Iterate ➔ Log Reflection.

+75 PTS

Step 1: Plain English Logic Plan

Write out what you want to build without worrying about code syntax. Describe features, layout, and interaction rules clearly.