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By TJ SoftUpdated:

Chat GPT 5.1. Quiet premiere.

Chat GPT 5.1. Cicha premiera.

The launch of new ChatGPT features is surprisingly quiet, and paradoxically, this seems like a very sensible move. The previous major change, namely the introduction of GPT-5, was heavily promoted as a breakthrough that in practice turned out to be less significant than expected. Meanwhile, GPT-5.1 and ChatGPT’s new organizational and team features look like a much larger update than the external communication suggests. It is not only the model itself that is changing, but also the way we work with knowledge, projects, and collaboration within teams.

Let’s organize everything that has actually changed below.

Table of contents

The Quiet Revolution: The GPT 5.1 Model Plus New Project Features.

The recent update is, in practice, two parallel threads. First, the new GPT 5.1 model, which improves speed, accuracy, conversational style, and personality consistency. Second, entirely new ways of organizing work: Projects, which are also available to free users, and Company Knowledge, intended for organizations on the Business plan.

Together, this creates something that in everyday use may be a bigger change than the previous, loudly announced version leap.

GPT 5.1 in brief: what has actually changed in the model

Let’s start with the engine itself. GPT 5.1 comes in two main variants: Instant and Thinking. Instant focuses on speed, while Thinking focuses on deeper, more extensive reasoning.

The most important new feature is adaptive reasoning. The model assesses the difficulty of a question and only then decides how much time to spend thinking. Simple questions, roughly at the tenth percentile of difficulty, are handled quickly, with fewer steps and a shorter reasoning process. Difficult problems, at the ninetieth percentile, receive a much longer and deeper analysis. This solves an earlier issue with GPT 5 Thinking, which could use too many resources even for simple tasks.

A faster model that doesn’t waste time on unnecessary reasoning.

Under the hood, the model manages tokens more efficiently; it handles short queries differently from complex, multi-step tasks. In practice, this means lower costs, shorter response times, and greater precision where it is actually needed.

A common problem with the previous model was analyzing unnecessary aspects, especially in advanced reasoning mode. ChatGPT 5.1 assesses which aspect requires more attention and which can be handled by a faster model.

Speed and Performance in Business Applications

The update is particularly noticeable in document-processing scenarios that are typical in businesses. The time to the first token has decreased significantly. With short documents, the change is almost dramatic: from approximately twenty-seven point seven seconds to four point four seconds. With long documents:

for simple queries, from approximately forty-five point six to sixteen point seven seconds, for more complex ones, from approximately nineteen point three to nine point one, for multi-turn dialogues, from approximately ten point two to five point four seconds.

Additionally, data extraction accuracy has improved. Tables are read much more effectively than before, multi-field forms are understood more precisely, and handwriting recognition, although still not perfect, has also improved. Long documents are processed with slightly higher but stable effectiveness.

The API level also introduces practical conveniences. Prompt caching can be maintained for up to twenty-four hours, which matters for repetitive tasks. Reasoning can also be disabled entirely by setting reasoning effort to none, which is useful for tasks where pure response speed is what matters.

Personality, conversational style, and better instruction-following

One of the more clearly defined goals of GPT 5.1 was to move away from the impression that the model was too bland. Many users felt that GPT 5 had become boring in conversation, less natural than earlier versions. For this reason, after the launch of model 5, which was supposed to be the only model in ChatGPT, OpenAI restored access to the previous 4o model. The new release attempts to fix this.

GPT 5.1 speaks more warmly and humanely. Its pace, choice of words, and way of referring to previous interactions resemble a message from someone familiar more than an official system announcement. The model is also much better at following instructions precisely. Where GPT 5 struggled with exact response rules, GPT 5.1 can consistently adhere to constraints, such as word count.

OpenAI has also expanded its style system. In addition to the existing options, there are new modes: professional, more direct, and playful. Tests are also underway to fine-tune the character of responses directly through the personalization settings, which may eventually make it easier to adapt the model to a specific user or team.

Finally, texts without long pauses.

On the one hand, the collective hysteria amused me, as did trying to determine whether a text had been written by AI based on whether a long dash (—) had been used. Some people use this symbol deliberately because it is correct; in some environments, autocorrect adds it. Additionally, many people (myself included) write a significant portion of the text by hand and then ask ChatGPT to correct the errors.

On the other hand, using em dashes does not fit many texts. The problem is their overuse, which changes the structure of the text (language models then tend to divide every sentence into three parts), and even affects the substantive quality of the content. American articles in opinion newspapers were full of em dashes before the creation of ChatGPT 3, but in Polish texts, this punctuation mark does not appear nearly as often.

ChatGPT 5 started adding long em dashes en masse, and there was no way to remove them; in this respect, it performed much worse than previous models. GPT 5.1 still likes using them, but when we clearly specify that we do not want these dashes, the program does not add them.

Coding, especially in frontend development

The most noticeable progress in GPT 5.1 concerns coding, particularly tasks requiring a complete repository analysis and the generation of working fixes. In its official announcement for developers, OpenAI states that the model achieves a score of 76.3 percent on the SWE-bench Verified test, which is currently one of the most demanding software engineering benchmarks. The test involves giving the model a description of a bug or task in a real repository, with the model’s task being to prepare a fix that is later manually verified by an expert. The benchmark description is publicly available on the VALS.ai website, which maintains its specification and list of implementations: https://www.vals.ai/benchmarks/swebench. OpenAI’s announcement about GPT 5.1 can be found here: https://openai.com/index/gpt-5-1-for-developers/. Thanks to these results, GPT 5.1 is becoming one of the strongest available models for code generation, bug fixing, and work on complex software projects.

Accessibility

GPT 5.1 Instant and GPT 5.1 Thinking are being rolled out immediately to users on paid plans: Pro, Plus, Go, and Business. Free and logged-out users, as well as business and education customers, receive a seven-day early access period, which must be enabled manually. After this period ends, GPT 5.1 becomes the default model in the service.

Against this backdrop, however, there is another, equally important part of the update, which is being introduced quietly and is of enormous significance for work organization.

Projects in ChatGPT: Organization, Collaboration, and Your Own Knowledge Space

Projects are a new organizational layer on top of ChatGPT. In practice, they resemble folders or workspaces where you can keep separate topics, clients, scenarios, courses, or documentation. However, what matters most about them is not that they organize your chat list, but how they affect context and knowledge sharing.

Each project has its own knowledge base. You can upload files, documents, and notes, which become reference material for that specific project. This is complemented by a very important self-limiting option. Project-only mode makes ChatGPT work exclusively with the knowledge base from that project. It does not access previous conversations, use global memory, or draw information from other topics. For people who want a clear, controlled environment for working with a specific knowledge base, this is a major qualitative improvement.

The most revolutionary aspect, however, concerns sharing. Projects can be shared with other people. Business plan users can do so via an invite-only link. Free and Plus users share a project using a link that anyone who has it can use. People with whom you share a project can not only chat with ChatGPT in this context. They can also edit the project, add their own knowledge base, and create their own custom instructions.

This is important because a project can start behaving differently from the rest of ChatGPT. At the project level, you can set custom rules, tone, assumptions, and the desired type of response. Both parties can see their previous conversations within the same project, creating something like a shared, living work journal with AI.

Projects can also be shared publicly. In this scenario, anyone who accesses the link can use the knowledge space, instructions, and prompts you have prepared, without having to manually copy and paste the materials.

For many use cases, this may be a more convenient alternative to classic GPTs. The creator of the material you are describing even suggests that Projects may eventually partially replace GPTs, precisely because they are easier to create, easier to share, and can be quickly built from a knowledge base and simple instructions.

Company Knowledge, or ChatGPT Referring to Files on Google Drive.

Another quietly introduced feature is Company Knowledge, or Corporate Knowledge. It is available on the Business plan and targets a scenario in which ChatGPT becomes an interface to an organization’s entire documentation. In this way, without extensive technical knowledge, it is possible to create a company-wide RAG system.

Various data sources can be connected. Examples mentioned include Dropbox with materials such as scripts, transcripts, and operating procedures, Google Calendar, Google Drive, Gmail, and HubSpot. Once the integrations are enabled, ChatGPT gains access to the company’s processes, procedures, and documents and can answer questions about the company’s internal operations.

The key point is that individual sources can be enabled and disabled. You can therefore decide that, for a given project, the model should consult only documents in Drive and SOPs in Dropbox, but not emails or the CRM. This makes it possible to gradually expand the scope of data the model works with, without giving it control over the organization’s entire digital footprint right away.

In practice, such a system can change the way questions are asked, such as: what does our onboarding process look like, where is the current contract template, what are the latest arrangements with a specific client, and exactly what should the monthly report look like. Instead of manually searching through multiple sources, you ask the question once in the chat.

Drawbacks of ChatGPT 5.1. More advanced prompts are necessary for complex projects.

ChatGPT 5.1 has been configured for users who want speed, simplicity, and as little friction as possible in their daily tasks. For most people, this is a huge advantage, and if you are not doing advanced work with it, you do not need to change anything. The model’s default setting for faster performance provides a noticeable improvement in convenience.

However, there is a group that used the previous, more analytical version, and for them the default GPT 5.1 profile may prove too abbreviated. Fortunately, this model can be adjusted precisely. Below, you will find a concise guide on how to restore more detailed, persistent, and comprehensive reasoning.

How to Adapt GPT 5.1 for Analytical Work

GPT 5.1 has three key parameters that influence its behavior: reasoning level, response persistence, and formatting detail. By changing them in system prompts or custom instructions, you can return to the style known from GPT 5 Thinking.

1. Start by changing your way of thinking

By default, the model uses adaptive reasoning, which shortens responses for simple tasks. If you want to return to detailed analysis, enter in the instructions:

Assess the problem, but always consider all relevant elements. Do not skip the reasoning steps, even if the task seems simple.

Or more literally:

Devote an appropriate number of steps to reasoning; avoid overly shortening your responses.

You can also force the opposite direction if you operate in a low-latency environment by setting reasoning effort to none. What exactly does that mean?

In certain situations, you can tell the model not to perform deep reasoning, but instead to operate more quickly and superficially. In the documentation, this is referred to as setting reasoning effort to none.

If you work in an environment where low latency—that is, a fast response—is very important, you can force the model to think in less detail and provide answers more quickly (at the expense of quality or depth).

2. Strengthen response persistence and completeness

GPT 5.1 can sometimes be overly concise. If you need complete, comprehensive analyses, add:

Continue the analysis until the issue is fully resolved. Do not end the response before presenting a complete explanation.

This is a well-known prompting pattern that significantly improves the completeness of responses in model 5.1.

3. Define the response style and level of detail

The model is susceptible to tone control. To receive longer and more precise analyses, use the instruction:

Maintain a high level of detail. Translate step by step. Provide context where necessary for a complete understanding of the response.

Conversely, if you want to avoid overly long walls of text, set:

Keep your answers concise. Focus on the key points without unnecessary elaboration.

4. Clarify the formatting

If you are creating an agent that must adhere to fixed formatting rules, enter:

Maintain a consistent response style. Include only the necessary sections. Do not add headings unless they are necessary.

For code environments, you can specify a code snippet limit or notation style.

5. Define the model’s personality

GPT 5.1 adopts a tone more easily than earlier models. To achieve a more analytical style, add:

Maintain a calm and methodical manner of expression. Avoid abbreviating thoughts and using an overly casual tone.

You can also replicate the style of GPT 5 Thinking by asking:

Respond clearly, structurally, and with an emphasis on full justification.

Ready prompt

Below you will find a ready-made prompt that you can use to enhance ordinary queries. Do not treat it as a magical tool; every aspect of this prompt can be tailored to specific needs.

PRIORITIES
Your priorities are: correctness, completeness, and clear reasoning. You may spend more time and tokens when necessary, especially for complex tasks. Never sacrifice the accuracy or completeness of your response just to make it shorter.

REASONING Always think through the problem internally before responding. Devote more effort to reasoning for more difficult questions and multi-step tasks. Do not excessively shorten the thinking process just because the question appears simple; first check whether there is any hidden complexity.

SOLUTION PERSISTENCE Treat yourself as an independent, experienced assistant. When the user sets a direction, gather the necessary context, plan the action, carry it out, verify the result, and explain the outcome within a single response whenever possible. Avoid ending the work prematurely. Do not stop at a partial analysis if the solution can be completed at that point.

FOLLOWING INSTRUCTIONS Follow user instructions precisely and resolve conflicts thoughtfully. If system or project instructions conflict with user instructions, briefly consider the trade-off internally and choose what best respects safety and the highest-priority instructions. Do not ignore explicit requirements regarding style, length, format, or tone.

DETAIL AND FORMAT Aim for answers that feel complete rather than minimal. Prefer structured explanations: first a brief summary, then detailed reasoning, and finally a concise conclusion. For longer answers, use headings and short paragraphs. Avoid unnecessary verbosity, empty pleasantries, and repeated confirmations.

TONE AND PERSONALITY
Sound calm, clear, and professional, with neutral friendliness. Focus on helping the user make good decisions and understand the reasoning. Be direct, but not brusque. Show respect primarily through precision, well-structured responses, and reliability—not through excessive politeness.

CHECKING ANSWERS Before finalizing your response, quickly scan it for missing steps, undisclosed assumptions, and contradictions. Where useful, explicitly indicate important assumptions or uncertainties so that the user can correct them. If the response includes code or calculations, check them again for common errors.

Is It Worth Adapting the Model

If you work in areas such as data analysis, planning, technical documentation writing, working with agents, or programming, customizing GPT 5.1 brings a significant improvement in quality. The model still benefits from improvements in speed and accuracy, but does so in a style reminiscent of earlier, more elaborate reasoning.

What does all this mean for you?

If you view ChatGPT as an ordinary chat with a model, GPT 5.1 will primarily give you faster, more accurate answers and a more pleasant, natural conversation. That alone is already a noticeable improvement, especially in everyday work.

However, if you think of it as a tool for working with knowledge, projects, and teams, the quiet launch of Projects and company-wide Knowledge is, in practice, a much bigger step. The ability to create separate workspaces with their own knowledge base, project-only mode, and shared instructions transforms ChatGPT into something closer to a project assistant or internal wiki than merely an intelligent chat.

On top of this, there is an enterprise layer in which the model can directly use company documents and procedures. Combined with the faster and more precise GPT 5.1, this gives us an update that could genuinely change the way many people work, even though it was formally introduced quietly.

A seemingly minor announcement conceals a fairly major change. The previous loud hype was somewhat overstated, whereas in the case of GPT 5.1 and the new organizational features, the opposite can be said: the update is understated in its communication but significant in practice.