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Mastering Claude Opus 5 & GPT-5.6 for Software Development

44 lessons9h

A practical, balanced course for software engineers who use both Claude and GPT models daily. Learn to write precise prompts, configure system instructions, reason step-by-step, structure outputs for reuse, handle large codebases, and choose the right model for each task while verifying results and avoiding hallucinations.

What you'll learn

Lessons unlock once the course is in your library.

Module 1

Foundations: Understanding Your Two Models

5 lessons
  1. 01What Claude Opus 5 and GPT-5.6 Actually Are13 min
  2. 02How LLMs 'Think': Tokens, Context, and Attention13 min
  3. 03Setting Up Your Coding Environment13 min
  4. 04The Mental Model: You Are the Architect, They Are the Pair Programmer12 min
  5. 05Common Beginner Mistakes That Waste Your Time12 min

Module 2

Prompt Engineering: Writing Instructions That Work

6 lessons
  1. 01The Anatomy of a Great Coding Prompt13 min
  2. 02Being Specific: Naming Functions, Files, and Behaviors13 min
  3. 03Giving the Model Context It Can't Guess13 min
  4. 04Few-Shot Prompting: Teaching by Example13 min
  5. 05Chain-of-Thought Prompting for Complex Tasks13 min
  6. 06Iterative Refinement: Prompting as a Conversation13 min

Module 3

System Prompts and Custom Instructions

5 lessons
  1. 01What System Prompts Do That Chat Prompts Can't12 min
  2. 02Writing a Personal Coding System Prompt12 min
  3. 03Custom Instructions in Claude and GPT: A Comparison12 min
  4. 04Encoding Project Conventions and Style Guides13 min
  5. 05Versioning and Testing Your System Prompts13 min

Module 4

Getting Models to Reason and Avoid Mistakes

6 lessons
  1. 01Why Models Hallucinate and How to Reduce It13 min
  2. 02Step-by-Step Reasoning for Algorithms and Debugging13 min
  3. 03Asking for Plans Before Code13 min
  4. 04Constraint-First Prompting to Prevent Overreach13 min
  5. 05Self-Critique and Red-Teaming Your Own Prompts14 min
  6. 06Handling Ambiguity: When to Ask Clarifying Questions13 min

Module 5

Structuring Outputs for Reuse

5 lessons
  1. 01Enforcing JSON Output for Machine-Readable Results13 min
  2. 02Generating Tables, Diffs, and Markdown Reports12 min
  3. 03Using Schemas and Type Definitions in Prompts12 min
  4. 04Prompting for Test Cases and Edge Cases13 min
  5. 05Building Reusable Prompt Templates for Your Team13 min

Module 6

Handling Long Documents and Large Context Windows

5 lessons
  1. 01Understanding Context Limits and Where They Bite12 min
  2. 02Chunking Large Codebases for Focused Queries12 min
  3. 03Summarization and Progressive Disclosure12 min
  4. 04Working with Long Logs and Stack Traces12 min
  5. 05Managing Multi-File Refactors Within Context Limits13 min

Module 7

Advanced Features: Tool Use and File Handling

6 lessons
  1. 01Tool Use and Function Calling in Both Models13 min
  2. 02Reading and Writing Files Through the Model13 min
  3. 03Running Code and Interpreting Results12 min
  4. 04Integrating with Git, Build Tools, and CI13 min
  5. 05Building an AI-Assisted Code Review Workflow13 min
  6. 06Automating Repetitive Tasks with Prompt Pipelines14 min

Module 8

Choosing the Right Model and Verifying Results

6 lessons
  1. 01Claude vs GPT: A Decision Framework for Coding Tasks12 min
  2. 02Verifying Code: Compile, Test, and Review13 min
  3. 03Cross-Checking Answers Between the Two Models13 min
  4. 04Detecting and Correcting Hallucinated APIs and Libraries14 min
  5. 05Security and Privacy When Using AI for Code13 min
  6. 06Building a Personal Workflow That Combines Both Models13 min