Stage 2 of 8 · 9 lessons · ~5 weeks
Prompting and model APIs
Treat prompts as code and model calls as an unreliable network dependency. Be specific, fix the output format and show examples, then learn one provider's API properly: system prompts, streaming, retries and a local model for cheap experiments.
Start: The chat messages APILessons· one lesson for each topic, in this order
Start with· follow one of these
- CoursePaidGrokking Prompt Engineering for Software Engineers
Design Gurus · Beginner · Subscription
Prompting patterns for engineers building features, not for chatting
- GitHub repoFreeAnthropic Courses
Anthropic · Beginner
Free notebooks: API fundamentals, then the interactive prompt engineering tutorial
Practise
Keep handy
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Few-shot, chain of thought, JSON enforcement and parsing failures in one place
Before moving on: Build a small Python command-line tool that turns messy text, such as a job post or an email thread, into a fixed output format with an official provider SDK, streams its reply, retries on timeouts, and runs against both a hosted model and a local one through Ollama.
Get a plain prompt with clear instructions, a fixed output format and two or three examples working before you reach for tools or frameworks; most weak outputs come from vague prompts, not weak models. Keep prompts in Git and rerun them on the same ten inputs every time you change a word.