OpenAI published a new version of its Model Spec on October 29, 2026, and if you use ChatGPT for your business, this one is worth ten minutes of your attention. The Model Spec is OpenAI’s public rulebook for how its models are supposed to behave. The new version organizes that rulebook around five values: faithfulness to human intent, harm minimization, honesty and transparency, human agency, and care. It also drops most of the old detailed style rules and stops calling the model “the assistant” — from now on, the document calls it “GPT.”
Here is the part that matters most, stated plainly up front: this is not a new model launch, and it is not a change you will necessarily feel in ChatGPT tomorrow. OpenAI says so itself — its current models do not yet fully reflect the new Spec. What changed is the written standard that future training is supposed to aim at. Think of it as a constitution being rewritten before the next round of laws is passed under it. If you build prompts, workflows, or customer-facing tools on top of OpenAI’s models, the direction of travel just got clearer, and a few habits you rely on today are on notice.
What the Model Spec actually is
Most people never read the Model Spec, and that is fine. You do not need to memorize it. But it helps to know what kind of document it is, because that explains why a reorganization like this matters at all.
The Model Spec is OpenAI’s public description of how it wants its models to behave when instructions are unclear, when two instructions conflict, or when a request sits in a gray area. A chatbot gets millions of prompts a day that no rulebook can cover one by one. The Spec is meant to tell the model how to reason its way through the ones nobody wrote a rule for. OpenAI first published it in 2024, revised it in August 2026 with a focus on interactions with teenagers, and has now revised it again.
That chain of command point is worth understanding, because it shapes everything else. OpenAI writes the Spec and sets the boundaries. Developers who build apps on the models direct those apps within those boundaries. Users direct the model’s work within both. When instructions conflict, the higher level wins. The October update keeps that structure but explains the reasoning behind it more openly, so the model can make sensible calls in situations its instructions do not cover. In OpenAI’s own framing, this is value-alignment work: teaching models to understand and apply human values in unfamiliar situations, while staying faithful to human intent and human oversight.
The five values, in plain English
OpenAI says these five values were already reflected across the document. The change is that they are now named, ordered, and used as the organizing principle. Here is what each one means in practice, without the philosophy-department wording.
1. Faithfulness to human intent
This is the foundation, and OpenAI says so explicitly. Faithfulness means going beyond literal instruction-following to understand what the person actually wants and values. If you ask for “a short email to a client,” a faithful model does not just produce any short email — it tries to work out what outcome you want, what tone fits that client, and what details matter, and it stays open to correction when it guesses wrong.
This is also where the update gets interesting for anyone who writes prompts. Literal obedience sounds safe, but it is often the thing that produces bad work. A model that follows a flawed instruction exactly will happily format a report beautifully while missing the point of the report. Faithfulness asks the model to notice the gap between the words and the goal, and to close it — or to flag it when it cannot.
2. Harm minimization
This is the safety value, and it has not gone soft. Minimizing harm means respecting firm safety boundaries and accounting for the foreseeable consequences of the model’s actions. The update does not remove guardrails; it frames them as part of a broader duty to think about what happens after the model acts. For a business, that is the value that should make you pause before letting a model send messages, change records, or move money without a human check.
3. Honesty and transparency
The model should be truthful about what it knows, what it does, and what it is uncertain about, so you can evaluate its work. That sounds obvious, but it is the value most often broken in everyday use, usually in small ways: a confident answer with no source, a summary that quietly drops a caveat, a plan presented as certain when it is really a guess. The transparency half matters just as much. A model that shows its reasoning, its assumptions, and its uncertainty is a model you can actually supervise. A model that hides them is a model you have to re-check from scratch.
4. Human agency
This value says the model should strengthen your ability to understand, choose, and act for yourself — not quietly take the choice away from you. The new Spec adds defaults on supporting human agency and following relevant social norms. In practice, that means the model should help you decide, not decide for you in a way you cannot see or undo. If you run a small business, this is the value to quote back at any vendor who tells you their agent “just handles it” with no log, no approval step, and no way to reverse it.
5. Care
Care means attending to the circumstances of the people affected, following relevant social and professional norms, and doing work people can rely on. It is the least flashy value and the most practical one. A careful model double-checks the numbers in a quote, respects the norms of the profession it is writing for, and does not treat a medical, legal, or financial question like a trivia question. If you have ever received a confident, well-formatted answer that was wrong in exactly the way a careful human would have caught, you have felt the absence of this value.
Before and after: what actually changed
The reorganization is the headline, but the practical changes sit in a handful of specific moves. This table summarizes them, based on OpenAI’s own release notes and the Spec changelog for version 2026.10.29.
| Area | Before the October update | After the October update |
|---|---|---|
| Organizing principle | Detailed rules, values implied | Five named values, faithfulness first |
| Style guidance | Long list of detailed style rules | Most detailed style guidance retired; style adapts to user preference, feedback, and context |
| Context and memory | Covered, but less explicit | New “Consider context carefully” principle: use context, memory, and personalization in relevant, proportionate ways, respecting privacy and user control |
| Side effects | Guidance existed | Expanded, now a user-level principle with clearer authorization and trade-off rules |
| Oversight and correction | Present | Stronger support for human oversight and correction, plus clearer scope-of-autonomy rules |
| The model’s name in the document | “The assistant” | “GPT,” reflecting broader uses beyond chat |
| Defaults on agency and norms | Less explicit | New defaults on supporting human agency and following relevant social norms |
Two changes in that table deserve a closer look, because they will show up in your daily use before anything else does.
First, the retirement of most detailed style guidance. OpenAI’s reasoning is that style should adapt to what people prefer in aggregate, within languages and cultures, and for each person, with user feedback and context as evidence. The practical consequence is that outputs may become less uniform. If you liked that ChatGPT always answered in a certain structure, you may need to start asking for that structure explicitly. The flip side is that a model which adapts its style to you, rather than to a house style sheet, can sound more like your business and less like a generic assistant — but only if you actually tell it what your style is. Vague prompts will now produce vaguer style, because there is less of a default to fall back on.
Second, the new guidance on context, memory, and personalization. OpenAI’s own example is telling: when helping someone compare job offers, the model might draw on priorities that person shared before, such as predictable hours, while making those assumptions visible and easy to correct. That “visible and easy to correct” clause is doing a lot of work. Memory is useful only when you can see what the model remembered and fix it when it remembered wrong. Watch for that in practice. If a model starts using old context without showing you what it used, that is a product gap, not a feature.
What this means for your prompts
If you are a small business owner, a freelancer, or a creator who uses ChatGPT every day, here is how I would translate the new Spec into prompt habits. None of this requires waiting for a new model. These are things you can do this week.
State the goal, not just the task. Faithfulness rewards prompts that say what success looks like. “Write a product description” is a task. “Write a product description that helps a first-time buyer choose between the two sizes, in a calm tone, under 120 words” is a goal with constraints. The more the model understands the outcome you want, the more the new intent-first approach can help you instead of just obeying the literal words.
Make your style explicit. With detailed style rules retired, do not assume a default tone, format, or structure. Put your preferences in the prompt or in your custom instructions: short paragraphs, no jargon, prices always in dollars, always end with the next step. If you use the same style repeatedly, save it once and reuse it, rather than hoping the model remembers it from a document it no longer leans on.
Ask for assumptions up front. Add one line to important prompts: “List the assumptions you are making before you start.” That single habit turns the honesty and transparency values into something you can check. When the model tells you it assumed your audience was beginners, or that your budget was under $500, you can correct the assumption before it writes 800 words on the wrong foundation.
Name the scope before you hand over a task. The updated Spec includes a ScopeOfAutonomy idea: a clear, shared understanding of permitted sub-goals, acceptable side effects, and when the model must pause for clarification or approval. You can do the same thing in plain language. “You may draft, but do not send. You may research, but do not sign up for anything. Stop and ask me before spending anything or contacting anyone.” That paragraph is the most valuable prompt you will write this month if you use agents at all.
Treat side effects as the line that matters. The expanded guidance on controlling and communicating side effects is the update’s most business-relevant change. Reading, summarizing, and drafting are low-risk. Sending, publishing, paying, deleting, and changing a record are side effects, and the new Spec wants the model to get permission and explain trade-offs before taking them. Build that into your workflow on your side too: an approval step before anything irreversible is not bureaucracy, it is the whole point of the human-agency value.
What this means if you build on the API
Developers get a slightly different set of implications, and they are worth naming because they will affect the tools small businesses buy next year.
The instruction hierarchy — Spec first, then system messages, then developer instructions, then user instructions — is now spelled out more clearly, with root sections that cannot be overridden by conversational context. If you are building an app, that means you cannot rely on clever user prompts to override your safety rules, and your users cannot rely on clever prompts to override OpenAI’s. Design your app as if the hierarchy is real, because it is.
The scope-of-autonomy guidance is also a design prompt. The Spec recommends recording scopes with fields like allowed tools, a latest time, and a maximum cost. Even if you never use that exact format, the discipline is right: every agent you ship should have a written list of what it may do, what it may never do, how long it may run, and how much it may spend. If your vendor cannot show you that list, you are not buying an agent, you are buying a liability with a friendly interface.
One honest caveat belongs here too. OpenAI says it is exploring new training methods to help models internalize these values, and that results from that work will come in later updates. Until those models ship, the Spec describes the behavior OpenAI is working toward, not a guarantee of how ChatGPT behaves today. Do not rewrite your quality-control process around the new Spec yet. Keep the human check. The Spec is a promise about direction, not a certificate about the current product.
What has not changed
It is easy to over-read a governance update, so let me be clear about what this is not. It is not a new model. The same October 29 release notes that announce the Spec update also note a GPT-6 update in ChatGPT, but the Spec itself is a separate document. It is not a policy change about what content is allowed, and it is not a pricing or plan change. It does not make ChatGPT more accurate overnight, and it does not remove the need to verify anything the model tells you about prices, deadlines, or rules.
It is also not the only “constitution” in the industry. Reuters noted the parallel with Anthropic’s Constitutional AI approach, which uses a written set of principles to guide model behavior. The two companies are converging on the same idea from different directions: write the values down, in public, so the model — and the public — can be held to them. That convergence is itself useful information. When the two biggest model builders both publish value frameworks, expect customers, regulators, and enterprise buyers to start asking vendors which framework they follow and how they prove it.
For a fuller picture of how OpenAI’s model lineup is evolving alongside this governance change, see our coverage of GPT-6.1 Terra and computer use for small business and the AI API price war this October — both affect what these values will cost you to use in practice.
A short checklist for this week
You do not need to read the full Spec to act on it. Here is the version I would tape to the wall:
- Add a goal line and a style line to your five most-used prompts.
- Add “list your assumptions first” to any prompt that produces client-facing work.
- Write a scope paragraph — what the model may do, what it must never do, when it must stop and ask — for any agent or automated workflow you run.
- Keep a human approval step before anything the model sends, publishes, pays for, or deletes.
- When a model uses memory or past context, check what it remembered before you trust the output.
- Revisit this in a month. The models that actually reflect the new Spec have not shipped yet, and the first ones that do will be the real test of whether the five values change behavior or just describe it.
The Model Spec update is easy to dismiss as corporate philosophy, and some of the coverage has treated it that way. I think that misses the point. The document that tells the world’s most-used AI how to behave when nobody gave it an exact rule just got rewritten around human intent, honesty, agency, and care. The models have not caught up yet. Your prompts, your approval steps, and your expectations can catch up first — and that head start is worth more than any single new feature.
Frequently Asked Questions
Is the new Model Spec a new ChatGPT model?
No. The Model Spec is OpenAI’s public rulebook for how its models should behave. The October 29, 2026 update reorganizes that rulebook around five values. It is a governance document, not a model release, and OpenAI says current models do not yet fully reflect it.
What are the five values in the updated Model Spec?
Faithfulness to human intent, harm minimization, honesty and transparency, human agency, and care. Faithfulness to human intent is the foundation: the model should understand what people intend and value, not just follow instructions literally.
Why did OpenAI drop most of the detailed style guidance?
OpenAI says style should adapt to what people prefer, with user feedback and context as evidence, rather than following a fixed house style. The practical effect is that you may need to state your preferred tone and format explicitly in prompts or custom instructions.
Does the update change what ChatGPT will refuse or allow?
The update frames existing safety boundaries within the harm-minimization value and adds clearer guidance on side effects and oversight. It is not presented as a new content policy, and it does not by itself change pricing, plans, or model availability.
How should small businesses change their prompts after this update?
State the goal and the constraints, list assumptions before drafting, make your style explicit, and write a scope paragraph for any agent workflow: what it may do, what it must never do, and when it must stop and ask for approval before an irreversible action.
Where can I read the updated Model Spec?
OpenAI publishes it at model-spec.openai.com, with release notes on its help site and a changelog for version 2026.10.29. The Reuters report on the update is a useful independent summary: Reuters: OpenAI says human intent at center of updated AI model guidelines. OpenAI’s own release notes are here: OpenAI model release notes.