Maximizing Collaboration and Efficiency with OpenAI's ChatGPT Team

An upgrade for ChatGPT Plus for small and medium businesses

I’ve been a user of ChatGPT since the very first days. When ChatGPT Plus came out, I signed up immediately. And OpenAI has been adding features at a rocket’s pace.

This is both good and bad. I love the innovation. However, when it came to being a reliable business solution, it was, in my opinion, full of holes.

Last week, I signed up for OpenAI's ChatGPT Team, which integrates the advanced AI models from OpenAI, such as GPT-4 and DALL-E 3, with additional customization, efficiency, and security.

ChatGPT Team is a plan that offers a dedicated workspace for teams of up to 149 people who use ChatGPT. The plan also includes admin tools for team management. All members of a ChatGPT Team have access to OpenAI's latest models, which include GPT-4, GPT-4 with Vision (which can understand both text and images), and DALL-E 3.

The pricing of ChatGPT Team is $30 per user per month or $25 per user per month billed annually. The cost is higher than ChatGPT Plus, OpenAI's individual premium ChatGPT plan, which costs $20 monthly. However, ChatGPT Team is still a better option than ChatGPT Enterprise, which costs as much as $60 per user per month with a minimum of 150 users and a 12-month contract.

The Benefits of the ChatGPT Team

ChatGPT Team can help teams collaborate more productively and effectively throughout an organization and take advantage of the more advanced features of ChatGPT.

No more limits on queries

ChatGPT Plus has certain usage limits. As of the latest updates, the service allows users to send up to 50 messages every three hours. This limit was increased from 25 messages per three hours to allow users to engage in longer, more in-depth conversations without worrying about prematurely exceeding their limit.

In addition to the message limit, there are character limits for the input and output. Users have reported running into a 4,096-character limit, roughly 500 words.

However, this limit is shared between the input and output, meaning that the total characters of both the user's input and the AI's response cannot exceed this limit. The input field is limited to 2,048 characters, approximately 500 words. For the premium service, ChatGPT-4, the limit goes up to 4,096 characters.

Exceeding these limits can result in a temporary block. If users hit the rate limit, they may be blocked from using GPT-4 for some time. With ChatGPT Team, there are currently no limits on the number of queries.

Access to AI Models with Larger Context Window

The ChatGPT Team space can access GPT-4 with a 32K context window. Why does a 32K context window matter?

The 32K context window in GPT-4 represents a substantial enhancement in the model's ability to process and retain information. This context window refers to the amount of text, measured in tokens, that the model can consider at any given time.

With a capacity of 32,000 tokens, GPT-4 can maintain context over much longer conversations or documents than its predecessors or ChatGPT Plus.

This expansion is crucial as it enhances coherence and relevance in the model's responses, especially in complex and detailed interactions. Handling a larger context is particularly beneficial when understanding extended narratives or technical details is essential.

Additionally, it supports in-depth, detailed conversations on complex topics, retaining earlier parts of the conversation for better continuity and understanding. This feature is particularly advantageous in training sessions or chain-of-thought (CoT) prompting where continuity and reference to earlier content are crucial, allowing for a more effective and coherent learning experience.

Customization: Tailoring ChatGPT to Your Team's Needs

A standout feature of the ChatGPT Team space is its ability to create customized GPT instances, aptly named GPTs. These can be fine-tuned to align with specific team requirements, workflows, or datasets, ensuring a highly personalized AI experience. But unlike ChatGPT Plus, you can keep these GPTs private to your team, allowing for sharing but keeping your workspace secure.

Enhanced Security and Privacy

ChatGPT Team space has added security. Teams can work with the assurance that their data and conversations remain private. OpenAI's commitment to not training models on team data underscores its dedication to user privacy.

Maximizing the ChatGPT Team Space

Enhance team efficiency by transforming repetitive, manual workflows into automated processes using specialized GPTs. For example, automate routine data entry tasks, generate regular reports, or streamline customer service responses. This saves time and reduces the likelihood of human error, leading to more consistent and reliable outputs.

Specific Examples:

  • Automated Data Processing: Develop a GPT that automatically extracts critical information from incoming emails and updates the relevant databases.

  • Report Generation: Create a GPT model that compiles weekly performance metrics into a comprehensive report with visualizations and summaries.

  • Customer Service Enhancement: Implement a GPT that provides initial responses to common customer inquiries, freeing up human agents for more complex issues.


The ChatGPT Team space is not just a technological advancement; it's a catalyst for organizational transformation. By strategically implementing this platform, teams can transcend traditional limitations, fostering a culture of innovation, efficiency, and collaborative intelligence.

Tip of the Week: Automating Tasks with GPTs

OpenAI GPTs allow users to create tailored versions of ChatGPT for specific purposes, enhancing their utility in daily life, at work, or home. Users can quickly build their GPTs without coding for personal use, internal company use, or public sharing.

If you have a ChatGPT Team workspace, you can provide and share these with your team privately. I am working on a couple of GPTs to automate tasks and then delegate them. So, I still have human-in-the-loop (HITL) oversight of things that are automated, as most of the outputs require

Rather than have them take a task and risk too much editorial control, I have decided to automate some of my social media tasks to get 80% of the work done in seconds and then spend the last 20% of my time working on the tweaking.

Here’s an example of how to create a GPT that does this:

Step 1: Create the GPT

Create a GPT from the Explore GPTs menu on the left of your screen. You can start by typing in the GPT Builder, or you can move over to the configure if you know what you are doing:

Step 2: Configure the GPT

Here’s where the magic happens. You can change the name and add an icon and a description to make it easily identifiable.

Step 3: Add Instructions

Here’s what I am doing for my GPT. You should customize the GPT instructions for your purposes:

You are an expert on LinkedIn copywriting. You will help me write a LinkedIn post that will drive engagement and catch readers attention. You will write  in the voice of Mark Hinkle. 

You will avoid using the following words - Paradigm, Delves,  Delve, game-changing, cornerstoneHere are the commands you will follow each command will be preference with a /:/help will list all commands with descriptions/hook 

- You will create an attention grabbing hook based on a topic or URL - Format of the command "/hook- Topic"/post - you will create a complete LinkedIn post that is less than 3000 characters 

- Format of the command "/hook- Topic"/format - You will format the  Linked /image - You will create a wide format image that can complement the LinkedPost 

- Format of the command "/image"Requirements- Posts should have no more than 2800 characters 

- Posts should have lots of white space, no more than three sentences without a page break-Every post should have a call to action

 - "If you liked this post and want to see more like it, follow me @markrhinkle and my LinkedIn Newsletter, The Artificially Intelligent Enterprise -"

Step 4: Add Conversation Starters

You can add the prompts in your GPT so that you and other users know where to start. Also, in my instructions, I added commands to automate tasks. One of those commands is /help, which echoes my instructions. So I can refer to the capabilities of my GPT at any point.

Step 5: Add Knowledge

Here’s where you can add documents that are helpful to the GPT in achieving its goals. I have added some examples of things that will help my LinkedIn Writer. They are PDFs of documents that I want to use as references:

  • LinkedIn Hook Examples

  • Examples of my top performing LinkedIn Posts

Step 6: Capabilities

Since I want my GPT to analyze data, access URLs, and generate images, I have checked all three capabilities. You may want to avoid Web Browsing if you have data privacy concerns. If you don’t need analysis, don’t choose Code Interpreter. If you want to create images, check DALL-E Image Generation.

Step 7: Create Actions

You can integrate your GPTs with third-party services. For right now, I am not doing that, but if I wanted to, I could use Zapier to automatically post when I am done. However, I don’t want to do that for this GPT, but if you're going to automate, then follow these steps:

Add Zapier Action to Your GPT:

  1. Go to the Configure option of your GPT. If you don't have a GPT, create one by clicking “Explore” and then “Create a GPT” within My GPTs.

  2. In the GPT Builder, click Configure and select “Create New Action.”

  3. Click “Import from URL,” paste the provided URL (, and click Import. This will add some text to the schema, which you should leave as is.

  4. After adding the actions, you can return to the Configure section. You will see that a new Zapier action has been added.

Step 8: Audit the Results

This is the most crucial step, in my opinion. Human-in-the-loop (HITL) ensures that the results are in line with expectations. I aim for any tasks to be completed 80% to my satisfaction, and then I provide the last 20% of human oversight.

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