Course TOpics
Prompt Engineering
Move beyond basic prompts. Learn the systematic design, evaluation, and management of prompts for real production AI systems.
What Makes this different
Prompt Engineering As Engineering
Prompt engineering is software engineering applied to language model inputs. It requires the same rigor — version control, testing, observability, and iteration discipline.
Systematic Prompt Design
Role prompting, chain-of-thought, few-shot learning, and structured output formatting. Design prompts that produce reliable outputs, not just good ones.
Prompt Versioning & Management
How to version, store, deploy, and roll back prompt changes in production systems. Treating prompts as code — because they are.
Evaluation & Testing
Evals, regression testing, and automated quality gates for prompt changes. Know before you ship whether your prompt change helped or hurt.
Context Window Management
Token budgets, context compression, and retrieval strategies. Make efficient use of context windows without sacrificing output quality.
Prompt Security
Injection resistance, system prompt protection, and output filtering. Build prompts that are robust against adversarial inputs.
Model-Specific Optimization
GPT-4, Claude, Gemini, and open-source models behave differently. Learn what works for each so you stop cargo-culting prompts between providers.
Engineer Better Prompts
Start with Prompt Engineering for Engineers — a practical, production-focused course.