AI Explained. The clearest non-hype explanation of why o1 (and by extension o3, R1, Claude extended thinking) layers reinforcement learning on top of next-token prediction to reward correct multi-step answers, and what that means for how you talk to it. Watch this and the article's "stop saying think step by step, start writing the spec" advice stops feeling arbitrary.
Treat the o1 terminology as historical context. The useful lesson is the prompting shift toward tight task specifications; current model names, product limits and best practices will keep changing.
Understand why reasoning-model prompts should specify the problem, constraints and success criteria instead of asking for visible chain-of-thought.
Basic prompting experience and familiarity with model names such as o-series, Claude extended thinking and R1.
Last reviewed: May 18, 2026
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Hand-picked external courses that go deeper on this topic.
DeepLearning.AIIsa Fulford · Andrew Ng
Ninety minutes to a year's worth of intuition. If you've started writing code that calls an LLM — or you're about to — this is the most efficient course online for closing the gap between "playing with ChatGPT" and "shipping a feature that calls an LLM."
Coursera · Vanderbilt UniversityDr. Jules White
The academic complement to DeepLearning.AI's short course — same discipline, longer arc, written for people who don't code. Dr. White teaches prompting as a set of reusable patterns (Ask for Input, Outline Expansion, Fact Check List, Menu Actions) rather than tricks. After this you'll prompt LLMs like a designer, not a guesser.
Microsoft LearnMicrosoft Learn
Prompt engineering, but for the tool most office workers will actually touch first. Microsoft's own four-part prompting framework (goal, context, source, expectation) is a genuinely useful mental model, and unlike the generic ChatGPT prompting courses already in our catalog, this one is grounded entirely in Microsoft 365 Copilot's specific quirks and grounding behavior.
