77 minutesAI prompt engineering: A deep dive
Hear how production prompt engineers revise instructions, examples and behavioral constraints under real pressure instead of treating prompts as one-off text.
AdvancedPrompt Engineering
Pydantic is all you need: Jason Liu
AI Engineer. The talk that crystallised the modern "define a Pydantic model, hand it to the LLM, let validation do the rest" pattern, with concrete examples of nested objects, validators that catch hallucinated URLs, and Chain-of-Thought as a typed field. Watch it before re-reading the article's section on validators and you will recognise where its retry and refusal rules come from.
AI Expert note
Kept as the origin of the schema-first pattern — watch it to see where the article's validator, retry and refusal rules come from, then implement with whatever structured-output tooling your stack uses.
What you should get from this
Learn why schema-first LLM calls need typed objects, validators, retries and explicit handling for malformed or hallucinated fields.
Watch or know first
Comfortable with Python and LLM API calls; Pydantic experience helps but isn't required.
Last reviewed: May 18, 2026
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Take it further
Hand-picked external courses that go deeper on this topic.
Coursera · Emory UniversityGenerative AI in Marketing
Emory University Goizueta Business School faculty
The deeper, university-level counterpart to our beginner HubSpot marketing pick — Emory's business-school treatment goes past 'how to prompt' into training generative models for brand-specific output, the purchase-funnel economics of AI-generated content, and a full module of genuine skepticism about when generative AI is and isn't worth using in marketing.
Advanced~14 hours · self-paced (4 modules)
Coursera · IBMGenerative AI for Executives and Business Leaders
IBM AI Academy
The genAI-era answer to the executive-strategy question. Three short courses aimed squarely at business leaders — no technical background required — on where generative AI creates value, how to govern it responsibly, and how to turn a vague "we should use AI" into a concrete, defensible use case. Rated 4.6 across ~700 reviews. Best taken before your next AI budget decision.
Advanced~10 hours · 3-course specialization