Inside our approach to the Model Spec
OpenAI
OpenAI laid out how it decides what its models will and won't do, publishing the reasoning behind the Model Spec. Instead of black-box rules, they're showing the actual playbook.
Based on reporting by OpenAI — read the original for the full story.
Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error
OpenAI has spent the past year and a half building something it calls the Model Spec, a public document that spells out how its models are supposed to behave, and now the company is explaining the thinking that went into it. This isn't a marketing brochure. It's closer to a constitution for chatbots, laying out a hierarchy of who gets to tell the model what to do: platform rules from OpenAI sit at the top, developer instructions come next, and user requests fill in the rest, all within limits set by the first two layers.
The pitch here is accountability through transparency. Rather than quietly tuning GPT-4o or o1 to refuse certain requests and leaving everyone to guess why, OpenAI wants the actual rules on the table, so researchers, journalists, and rival labs can poke at them. That's a meaningfully different posture than most closed-model companies take, where behavior is shaped behind closed doors and users mostly encounter refusals with no real explanation attached.
The hard part, and OpenAI is fairly candid about this, is that safety and freedom pull in opposite directions constantly. Give users too much latitude and you get models that will happily write malware or dish out medical advice that gets someone hurt. Lock things down too hard and you get the overcautious, hedge-everything assistant that annoyed plenty of ChatGPT users through 2023, the one that refused to discuss basic anatomy or write a villain's dialogue in a screenplay. OpenAI's answer is to keep revising the Spec based on real-world friction, treating it as a living document rather than a one-time policy dump.
Critically, the Spec also functions as a training and evaluation tool internally, not just a PR artifact. OpenAI says it uses the document to grade model outputs and decide what counts as an actual violation of intended behavior versus a legitimate, if uncomfortable, answer. That framing matters because it ties the public-facing promises directly to the technical process of building the next model, rather than treating them as separate tracks that only meet at a press release.
My take — AI-written commentary, not fact-checked reporting
I'll give OpenAI credit for publishing the rulebook instead of just enforcing invisible ones, that's a genuinely useful move for an industry that loves to hide behind 'safety' without defining it. But a spec is only as good as the enforcement behind it, and OpenAI still grades its own homework here. I'd trust this a lot more if an outside body, not the company selling the model, got to check whether GPT actually follows its own constitution.
Read more about this at: OpenAI
