Companion videos

Choosing and prompting reasoning models

The article recommends starting with a clear problem, constraints, required evidence and an output contract, then comparing configurations on representative tasks. These videos document the o1-era context in which some reasoning-model guidance emerged. They do not establish a universal rule for OpenAI's current models or for other providers. Use current provider documentation and workload-specific evaluations for implementation decisions.

Primary pick

27:51

o1 - What is Going On? Why o1 is a 3rd Paradigm of Model + 10 Things You Might Not Know

AI Explained

The video offers an independent explanation of the early o1 framing and its prompting implications. It is useful historical context, but its claims about o1 should not be extended automatically to later OpenAI models, R1, Claude thinking modes or other providers.

What you should get from this: Understand one historical account of o1, then compare a direct task specification with other supported prompt variants on your current model and workload.

Watch or know first: Basic prompting experience and familiarity with model names such as o-series, Claude extended thinking and R1.

AI Expert note: Treat the o1 terminology and prompting claims as historical context. Check current provider documentation, test quality, latency and cost, and ask for checkable sources, calculations or test results rather than a hidden reasoning trace.

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Also worth watching

03:16

Building OpenAI o1

OpenAI

This three-minute first-party video records how the OpenAI team presented o1 at launch. It is useful for understanding the category's history, but it does not establish how current models work internally or which prompting pattern will perform best on a different provider or task.

What you should get from this: See the original o1 launch framing and separate that historical account from current implementation guidance.

Watch or know first: Watch the primary pick first or read the companion article's reasoning-model section.

AI Expert note: Keep this as historical source material, not as current implementation guidance or proof of a private reasoning process. Base production choices on current provider documentation, representative evaluations and checkable output evidence.

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