Episode Categories:
Resources:
Join the discussion on LinkedIn: Got something to say? Let us know on LinkedIn and network with other AI leaders
Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Connect with Jordan Wilson: LinkedIn Profile
Start Here Series in our Inner Circle Community: Join for free access
Unlocking Business Value with OpenAI Workspace Agents: The Overlooked Enterprise AI Feature
While widely discussed breakthroughs like GPT 5.5 and Images 2 capture headlines, one of OpenAI's most impactful recent releases for business environments has flown under the radar: Workspace Agents. Sandwiched between more hyped announcements, Workspace Agents provide a robust, enterprise-grade platform for automating repeatable business processes, connecting app ecosystems, and powering daily team operations with an intuitive workflow builder. Here’s a focused look at what sets Workspace Agents apart, demonstrating their immediate, specific value to business and technology leaders.
Workspace Agents: Enterprise AI Built for Integration and Auditability
OpenAI Workspace Agents offer a drag-and-drop agent builder designed explicitly for team-based operations. Unlike standard GPTs, Workspace Agents connect directly to business-critical apps—including custom Model Context Protocols (MCPs)—and can deliver real, read/write automation across workflows while remaining fully auditable.
Key features include:
Integration with multiple apps, including custom-developed MCPs
Full visibility into every agent action, enabling step-by-step auditing
Team-based sharing and permissions, supporting robust governance and compliance
Utility in Slack, allowing agents to operate like digital employees, responding to prompts and automating actions within familiar communication channels
Unlike individual GPTs, Workspace Agents are built to be deployed across entire teams and scaled for department or organization-level workflows, providing memory and persistent automation in a secure, manageable environment.
Real-World Workflow Automation: Concrete Use Cases
The episode's demonstration moves beyond theory, showcasing exactly how business workflows can be reimagined using Workspace Agents.
Example: Automating AI Features and Market Intelligence
An agent was configured to connect to a company Beehive account, analyze newsletter activity, pull and rank the top five most-clicked stories daily, identify which contained new AI features or immediately usable LLM upgrades, and deliver findings via scheduled email.
The agent leveraged natural language prompts but recognized existing app connections (like Beehive MCP and Gmail) without requiring technical setup from the user.
The scheduling capability meant a weekly manual task—one that previously required hours of attention and risked human distraction—could now be fully automated, freeing decision-makers to focus on prioritizing the most valued content for production and strategic planning.
Persistent memory ensures the agent doesn’t repeat or overlook items. Each time it runs, it considers historical context, providing not just repetitive automation but also intelligent synthesis and contextual awareness.
Workspace Agents vs. GPTs and Codex: Business-Critical Differences
In enterprise settings, the distinction between GPTs, Workspace Agents, and Codex automations carries tangible business consequences:
Scope of Automation
GPTs typically excel in single-turn, one-off chatbot interactions. By contrast, Workspace Agents are designed for repeatable, multi-step workflows with triggers (manual or scheduled) and persistent memory.
Read/write capabilities mean Workspace Agents can autonomously send emails, generate and save collateral in cloud drives, or act on calendar events—something standard GPTs cannot do.
Cloud-Based Reliability
Unlike Codex automations that require a local machine to be active and running, Workspace Agents function natively in the cloud, ensuring continuous operation, centralized management, and seamless integration with enterprise systems.
Control, Audit, and Governance
Workspace Agents offer granular observability and traceability. Every action can be reviewed, ensuring compliance with audit and access requirements found in regulated industries.
Organizations can implement roles-based access control (RBAC), providing layered security for sensitive workflows, a necessity for many business applications.
Skills and App Ecosystem
Skills (essentially reusable workflows or protocol sets) can be imported from other AI ecosystems (e.g., Claude, Copilot), allowing teams to bring their existing assets into the Workspace Agent environment or bundle multiple app connections in a single automation.
ROI Considerations and Pricing Implications
Workspace Agents currently require a ChatGPT Team or Enterprise Plan, with a minimum of two seats per team. These plans offer access to MCPs and significantly higher usage limits compared to even advanced individual plans. As of the release date, OpenAI shifted from unlimited access to a usage-based pricing system, highlighting the need for organizations to monitor usage and forecast cost-to-value as part of AI deployment strategy.
Best Practices for Business Deployment
Identify and Target High-Frequency Manual Tasks: Workspace Agents are best utilized for repetitive knowledge work where context needs to be carried across multiple systems (e.g., updating proposals, CRM entries, or daily executive briefings).
Leverage App and Memory Capabilities: Integrate agents with cloud storage, calendar, communication systems, and custom company data sources to realize compound productivity gains.
Assign Governance and Review Activity: Utilize built-in audit features to trace decisions and outputs, enabling process refinement and regulatory compliance.
Conclusion: Enterprise AI with Measurable Impact
Workspace Agents enable senior leadership and operations teams to reimagine daily workflows. Whether automating content analysis, managing complex customer support escalation, or consolidating intelligence across distributed apps, Workspace Agents provide a scalable, auditable, and integrated AI backbone for the modern enterprise. The feature stands as a strategic lever not only for improving productivity but also for elevating the standard of control and oversight in enterprise AI deployments.
Topics Covered in This Episode:
- OpenAI Workspace Agents Release Overview
- Workspace Agents vs GPTs vs Codex
- How to Build Workspace Agents Step-by-Step
- Teams-Only Access and Pricing Updates
- Workspace Agents Features and Capabilities
- Integration With Apps, Skills, and Slack
- Cloud-Based Automation and Scheduled Triggers
- Governance, Observability, and Persistent Memory
- Best Practices for Automating Manual Workflows
- Migration: GPT Conversion to Workspace Agents
Episode Transcript
Jordan Wilson [00:00:16]:
OpenAI releases dozens of products and model updates each year, and I think their recent release of workspace agents two weeks ago may have been the company's most overlooked meaningful update. Well, ever. Why is that? Because now teams have a simple drag and drop agent builder that connects to all the apps you use. It can be shared across your team. You can talk to it in Slack like an employee, and it has read and write capabilities to get work done. And maybe even better than a human employee, you can actually go back and observe an audit each step of the workspace agents work. Chances are, though, you probably didn't hear much about this. That's because the workspace agent's release was kind of sandwiched between two of OpenAI's more viral or hyped up announcements of the year during the same week, which was GPT 5.5 and their images two model.
Jordan Wilson [00:01:19]:
So, unfortunately, a lot of the normal attention that would normally come with an update like workspace agents kind of fizzled and faded away. But fortunately, I'm gonna be recapping all of the agent action that you might have missed on today's episode of everyday AI because we are putting AI to work on Wednesdays in our weekly Wednesday demo series. So here is the big picture. Well, the big picture is you might have missed this, and you should have been paying attention. Because workspace agents, like I said, got released. It it was one of OpenAI's biggest release weeks ever. I would say, actually, it was their second or third biggest week release week ever since the company started, you know, with, Chad GPT in November 2022. So if you missed it, I don't blame you because between GPT 5.5 and images two, you might look at something like the new workspace agents and say, well, this wasn't, you know, even OpenAI's biggest release of the week, but I think it actually may have been.
Jordan Wilson [00:02:26]:
So these new agents are powered by codex. That part's important and more on that later, and they can be shared across teams, used in Slack, and they have complete observability. And there are pros and cons to using these new workspace agents versus setting up something similar in codecs or even using a normal GPT that you might normally use. Also, one other thing to note, well, why it's noteworthy for today at least is pricing is set to change today. Yeah. Everyone kind of had a if you were on a paid Teams plan, you kinda have unlimited use and unlimited access. But OpenAI did say that starting today, they're gonna be shifting to a usage based, pricing system. So we're gonna have more on that in today's newsletter, but maybe today will be the day because of that price change that a lot of people are maybe hearing about ChatGPT's agents for the first time.
Jordan Wilson [00:03:20]:
So on today's show, here's what we're gonna do. Here's what we're gonna go over live. We're gonna show you how to build a workspace agent from scratch and understand their capabilities. You're gonna know the pros and cons of using workspace agents versus setting something up in codex and even versus the kind of quote, unquote older or old school GBTs. And then I'm gonna show you some of the best practices on how your team can start using Workspace agents today. Alright. Let's go. Welcome.
Jordan Wilson [00:03:50]:
This is Everyday AI. My name is Jordan Wilson. If you're new here, this is a daily unedited, unscripted livestream podcast and a free daily newsletter helping everyday business leaders like you and me keep up with all the AI advancements because like this workspace stations, you might miss some. I'd tell you what's important, how to use it to grow your company and your career. So if that's what you're trying to do, yeah, it starts here, but make sure you go to our website at youreverydayai.com. Aside from there being an entire library of free Gen AI resources, you can go listen to 750, of our back episodes, read about them, watch the videos, all of that, but make sure you go sign up for our free daily newsletter. We're going to be recapping the highlights and what you need to know from today's show in a more digestible form, as well as all of the other AI news and updates that you need to know to stay ahead. All right.
Jordan Wilson [00:04:38]:
So let's talk workspace agents. You probably didn't hear a lot about them. And I already told you some of the reasons why, yes, they were sandwiched between open AI, some of their biggest releases, but the other reason why is while they're only available for teens. And I think that a lot of the maybe quote, unquote hype or attention online is sometimes driven by individual power users. Right? So maybe those people with a $200 pro account or, you know, those on a normal paid plan. So, unfortunately, a lot of these capabilities, although you can kind of replicate some of the basics, in codex if you do have an individual paid plan. But for the most part, I think that's one of the reasons why we haven't heard more about these because they are right now only for business and enterprise customers. So you do have to be on a team plan to take advantage of them, and I guess that's why they're called workspace agents.
Jordan Wilson [00:05:35]:
And if you've used agent mode before in chat g p t and you're looking at your paid plan and you're like, oh, well, this says agent. That must be what it is. No. Agent mode is a older kind of, capability inside of chat g v t originally called operator. It moved over into agent mode. So if you're looking at that, you're like, no. That's not it. Workspace agents are extremely powerful.
Jordan Wilson [00:05:59]:
So think of all of these manual processes that you do over and over, all of the different apps that you use. Maybe you're using skills. Right? Obviously, skills have wide support now in certain chat GBT plans, in Gemini, plans. Microsoft has rolled out supports, obviously, Claude, with skills. You can actually use skills and bundle together skills, all of the connected apps that you use, as well as how you would normally use chat g p t. And it's all powered by codex. Right? So that's kind of workspace, agents sandwich up into a little package, but we're gonna do it different this week. We're gonna go straight live.
Jordan Wilson [00:06:39]:
Alright? We're gonna start our demonstration, and, maybe by the end, we might have an agent, fully working. If not, I already do have this one prebuilt to where we can look at the, the responses because, you know, what can ever go wrong doing, building an agent absolutely live. Right? Alright. So here we go. Alright. I'm actually gonna show everyone, how to do this kind of step by step. So livestream audience, if you could do me a favor, let me know if you can see my screen. Podcast audience, appreciate you as always.
Jordan Wilson [00:07:10]:
But if you want the video version of this, make sure to go to our website, youreverydayai.com. You can watch this video and all of our other Wednesday tutorials. So there is a new section on your sidebar. You're gonna go into agents. You're gonna see this on the left hand side. So I actually am on a cleaner account. I have another, team's account where I'm doing a lot of the majority of my actual use. This is one of my team plans that I use more for testing.
Jordan Wilson [00:07:37]:
But where you would normally have your chats in the different modes like deep research and apps, all those things on the left hand sidebar, you're gonna see a new section called agents. Alright? So make sure you look for that. There's a little plus button that you can click on there. You can click on browse agents, and then you can go in. You can see your recently used agents, agents that were built by you, and then a directory of agents. So, you can share agents, and the agents that are shared, will be accessible there in that place under the directory. So we're gonna get a little bit more into the governance side, the sharing and the memory because I think that's all very powerful, but that's the basics. So it is kind of similarly set up to GPTs.
Jordan Wilson [00:08:19]:
How your company can have a GPT store, you could build GPTs for yourself. The same thing with workspace agents, even though they are made for only teams, you obviously can have agents that only work, you know, with your data that aren't available to everyone else. So there is a sharing element as well. Alright. So we're gonna go straight in, and we're just gonna create an agent. Alright. I have my prop kind of typed up here, and I'll we're gonna watch this, live. I'm gonna explain it to you how it all works.
Jordan Wilson [00:08:47]:
So let's go. I have a very, a very simple prompt here. So there's different ways that you can build these. You can build these conversationally. You can start with a template. You can build them from scratch, but I'm just building it conversationally right now. So all I said I said I want the agent to go into my Beehive account over the past five days. So, yeah, we do a daily newsletter.
Jordan Wilson [00:09:11]:
We use Beehive. That is our platform. Beehive has an MCP server. So this is fast. Right? So, it's already kind of done, not actually, but it's already outlined, my agent. So, before I could even finish reading the prompt. So here's what my prompt is, the agent builder is kind of ready for me to start approving. So it says, I want the agent to go into my Beehive account over the past five days and give me a list of the five most clicked stories each day over the past five days, so 25 in total.
Jordan Wilson [00:09:42]:
Then I want a pullout of anything that might be considered a new AI feature or an LLM upgrade that can be used immediately. I want this to run every day at 7AM and email me the findings. So this is just an example, but this is a process that I go through every single week. Right? So we have our new show on Fridays where we go over, you know, we call it the Friday feature show. We go over seven of the most useful AI updates that you can actually use. So a little different than our Monday news story because a lot of that now is caught up in drama and, you know, you know, funding and all these other things. So Fridays are practical AI updates and LLM upgrades that you can use. So the problem is is there's obviously way more than seven.
Jordan Wilson [00:10:23]:
So this is one thing that I would normally do manually, and I want you to put yourself in my shoes. Right? What are those tasks that you have to do manually over and over that you're like, this is silly? For me, this is one of them, but I always like to back, you know, my hunches up with data. So that's why I normally do this manually before I had my workspace agent is I would go into look into each, email newsletter that we would send out to see what are the most clicked stories because I might think AI feature b is the popular thing that most people care about. But if no one's clicking or caring about feature b and it oh, turns out it's feature c, That's all database evidence that I can go into my daily newsletter each and every day and look at. The problem is is that takes a lot of clicking. That takes a lot of manual effort. And let's be honest, I think one of the biggest upsides of using things like workspace agents or any automated AI workflows is while you take out that, the likelihood of you getting distracted. Right? Because for me, I would probably go in here.
Jordan Wilson [00:11:21]:
I would see something in in our email, and I would say, oh, a ton of people clicked on that. Let me go start planning an episode on that for tomorrow or for next week. Right? That's what would happen to me. So not only our workspace agents great at the context carry. Right? So carrying this context between different apps that you can set up, but also just well, you aren't gonna get distracted. Alright. So that is my prompt. The agent has already built a plan for me to approve.
Jordan Wilson [00:11:49]:
And you'll see here, I didn't even need to tell, which is really good, the agent builder that the beehive is actually a custom MCP that I already connected. So I didn't have to choose everything conversationally, but it already decided on its own that it needs to use the Beehive MCP connector that I have already previously set up in my Gmail account. So all I said is email me something, but it was smart enough to look through. It knew I had to be the the beehive custom m c MCP. Can't talk this morning. And it knew that I had already connected my Gmail. So that's a great benefit of just being able to talk about your goals conversationally. You don't even have to know or remember necessarily what you have hooked up in your account.
Jordan Wilson [00:12:33]:
Alright. So it gave me a plan. So here's the plan. It says this agent will review your beehive data from the previous five days, rank the five most click stories for each day, and highlight new AI features. So I can ask for edit. So one thing and I know this from the testing. One thing I did a little bit wrong, is I need to clarify the last five episodes, not the last five days because the last five days would include weekends. So I'm gonna say don't include weekends.
Jordan Wilson [00:13:01]:
I'm gonna say go back to the, last five newsletter posts that have been published regardless of day. Alright. So if you don't like the plan, just like I showed you, it's gonna go ahead and modify that. So I said that, and now, the agent builder split out into two kind of panes. So if you are familiar, with the custom GPT builder and, chat g p t, You'll be familiar with this setup, but essentially, you can talk conversationally on the left hand side for edits. In natural language, you can upload files. You can click the app button, for context bringing in, tools like your memory, web search, images, etcetera, or connect it to other apps. So if I do in the future want to add another app to this, I can do that fairly easily in a conversational editor.
Jordan Wilson [00:14:05]:
And then on the right hand side, as the agent builder builds the workspace agent, it is going to be previewed here on the right hand side. So now, my next step, it says, one important setup is still blocking. It says for the daily 7AM email, should the agent send it automatically from your Gmail or pause for approval? So I'm just gonna say, send it automatically. Again, this is like having a super smart developer That's building you an agent that can run on a schedule. It can run on a trigger and you just have to sit there and say, go do my work. You just have to think of redesigning your workflow. I think that's where most teams are gonna find the biggest benefit from using workspace agents is just reimagining how work can work. Alright.
Jordan Wilson [00:14:50]:
So now the cool thing, right, so if you have used codex like me, you could actually kind of watch this agent work. Right? So it says it's thinking. There's kind of a cursor, you know, floating around. I can see what it's doing. So we're gonna give this, a minute to cook. Right? Quite literally. And then we're gonna check back in on it here in a little bit, but we're gonna go over, some of the other features, that we need to know. So let's make sure we cover the basics.
Jordan Wilson [00:15:23]:
What are these workspace agents? They are much more than talking in chat g b team because they can follow your instructions. They can use all of your connected tools, whether they're apps that you have already connected that OpenAI provides support for, custom MCPs that you can set up. That's a model context protocol. So many of the most popular apps and softwares today have MCP connections. So it's not just for the apps that OpenAI has act you know, has official compatibility for. It's for your own apps. And here's one of the big benefits. They run-in the cloud.
Jordan Wilson [00:15:56]:
Right? So you've probably heard a lot of talk even myself. Right? Codecs. I have Codecs running around the clock. Right? I have all these automations. Same thing with Cloud Code. Right? Cloud Code and Cloud Cowork. But for all of those things, you have to have, number one, your machine running. Number two, you have to have the apps open.
Jordan Wilson [00:16:15]:
So that's a big benefit of the workspace agents and is is they run-in cloud. And then the other big one is you can talk to it and command it in Slack just like you would an employee. So if your team is a big Slack user, that's gonna be a big benefit. So you don't even have to go into ChatGPT, browse through your agents, right, if it's not scheduled because you can have it run every single day or you can trigger it manually. Right? So when a new, you know, customer support ticket comes in, maybe you wanna look through your CRM, maybe you need to look through Google Sheets, and then maybe you need to, you know, fill out a customer response. So if your team does run-in Slack and you have a Slack channel where a new, you know, customer inquiry comes in or a customer support ticket as an example, you could fire, fire off, your workspace agent or it could obviously do that automatically based on the trigger of receiving, you know, any of that information. So these triggers can be automatically or you can talk and kind of get the, workspace agent running inside Slack. But, essentially, this replaces the older paradigm of well, you just having to go in and give chat g p t a prompt and then have it go do work.
Jordan Wilson [00:17:29]:
So the difference here is there's a trigger. It can be scheduled. You line up the process. It uses the different tools that it has access to. It also has persistent memory, which we'll talk about here in a minute. Then you get an output and you can review it. So this is best for repeatable, multi step workflows, not one off chat. So your one off chats, you know, maybe you'll still use GPTs for that.
Jordan Wilson [00:17:51]:
That's a big difference between workspace agents and GPTs. Well, number one, the workspace agents have read write ability. And by default, GPTs can't actually write. They can't go into your Gmail and send an email. They can't create a calendar event. Right? Some, you can do draft versions, but you can't actually autonomously do that actual work, and that's where workspace agents actually set themselves apart. Next, here's kind of the five parts that make it useful. So you think of your workspace agent as having a role or a job.
Jordan Wilson [00:18:25]:
In my very specific instance here, all that's doing is it's doing some basic research for me, going into my, newsletter, clicking through, looking at the performance, and then also thinking. It has a layer of thinking because not all of these top click stories each and every day are gonna be actual features that you can use today. So it's doing a level of synthesizing, thinking, and then also a level of research. So anything that you can normally do inside of Chad GPT, this workspace agent can do. So you give it a roll or a jot. Then there's a trigger, whether that's a manual trigger, a scheduled trigger, or inside of Slack. Then there's different steps in a process. It has tools.
Jordan Wilson [00:19:08]:
That's kind of the system that it works within. And then there's also guardrails on the back end for observability and traceability. And the big thing here is skills. So when you're building this, and I'll show you some of the more, customizable features inside of these workspace agents, any skill that you have in Claude, in Copilot, you know, now even Google Chrome supports skills. Right? Kind of an open protocol of, you know, essentially a set of markdown files. You can import a skill. So if you export it from anywhere else, it's gonna give you a zip file. So in the same way that I conversationally gave the agent builder a prompt and said, I wanna do all these things that it was smart enough to connect it to my current apps, you can just upload a zip file and say, hey.
Jordan Wilson [00:19:51]:
This is a skill I was using in quad. Right? But maybe it couldn't do it everything you wanted it to. And then it will use all of that skill. It will import it, and then connect all of the different apps. So what can they do? The biggest thing is repeatable work. Because if I'm being honest, if this is a process you do once a year, it's not probably worth building a workspace agent on it right now. These are for those tasks, the manual tasks that you are having to be the human duct tape. You are having to do the context carry.
Jordan Wilson [00:20:22]:
Right? Going in, checking, you you know, you get an email. There's a new entry from your website. You're going into Google Sheets. You're looking at this person. Then you're going into your CRM. You're seeing what's the latest. You're doing some manual research on the company. Then maybe you're updating a proposal, that you have saved in, you know, Canva or Figma or Gamma, whatever it may be, and then you're uploading that and, you know, sending it to your team for approval in Slack.
Jordan Wilson [00:20:50]:
Right? That might be a two, three, four hour process that I just described. That entire thing, you can go to either draft or even publish it if you wanna get spicy without any work. Right? So this is for the repeatable work. So whether that's for prep docs, briefing, I think that's a very popular use case, you know, kinda like your daily briefing looking at your, your calendar, your email, your Google Drive, or if you're on the Microsoft side, it connects to, you know, your Outlook, your SharePoint, your OneDrive, but kind of just helping you manage your day to day, your meetings, all of those things done for you. Analysis, coordination, you know, creating content, obviously, triaging, you know, certain things based on a set of predetermined rules that you can build conversationally. So, I really would say that there's no hard limitations right now with workspace agents, mainly due to the fact that you can schedule them. They can run autonomously in the cloud to your connected data. You can edit them, and they have custom MCP and skill support.
Jordan Wilson [00:21:52]:
So this is kind of like the agents that I think a lot of us have always wanted, but we just haven't really had access to. So there are different ways to build them. I showed you one way, which is just conversationally. Right. So that's way number one. Another way that you can do it is by using a template, which is great. The third way is you can build it from scratch. So if you are more of a builder, that's a great way to do it.
Jordan Wilson [00:22:17]:
And then last but not least, OpenAI has said that there's going to be a custom GPT conversion. So what does that mean for the future of GPTs? I'm not sure. OpenAI did call Workspace agents the next iteration of GPTs. So we don't know if they're going to eventually get rid of them, stop supporting them, maybe they'll always be around. I'm not sure. But that is kind of the last way to build it is OpenAI did say that they will be releasing soon a dedicated tool that converts all of your GPTs into workspace agents. The big holdup there is, well, what about for people with non team accounts? Right? That's gonna be one of the biggest stick ups. And let me just tell you the the straight facts here.
Jordan Wilson [00:23:01]:
Right? For me, I have a team account that I just use. Right? And one of the reasons why is because even on my, you know, $200 ChatGPT Pro account, I don't have MCPs. Right? Yeah. Don't have custom MCP access on that certain level. So I've always had different tiers, but for a lot of people, you might just want to get a team plan. You have to have a minimum of two seats. And if you look at that, right, so you're paying, I don't know, at that point, like, $60 a month, then you get workspace agents. You technically have double the accounts because you have two accounts.
Jordan Wilson [00:23:33]:
You do have to have a minimum of of two accounts even if it's under one team. So even if you're on something right now, as an example, like the Claude $100 a month plan. Let's say you are a PowerAI user, and you're like, well, I'm not gonna do this because it's only for teams. Well, for $60, you're saving money. A single, team or business account gets higher rates than a $100 a month plan. So you probably have double the rates for almost half the price. So I'm just putting that out there. That's not biased.
Jordan Wilson [00:24:03]:
That's just the facts. Go go do that yourself. I've done it plenty of times. I've been on all the different quad pet plans, the $20, the $100, the $200, and you get better limits, on the, business plan for ChatGPT. It's a little bit better than the $20 a month plan. So you're getting better limits anyways. So just putting that out there. So those are the different ways that you can build, you know, four different ways.
Jordan Wilson [00:24:25]:
One of them not out yet with the GBT conversion, then you connect to your apps and skills. You can preview it. You can do test runs. You can refine it like you already saw me do, and then you can share and publish it to your team, or you can use it individually. So you just build in plain English and then you test before you share. Last but not least the controls and governance. This part's big because you can actually go through and see every single thing that this agent has done. Right? You don't have that right now with GPTs.
Jordan Wilson [00:24:56]:
You technically don't even really have that capability in codecs, which I absolutely love. So I think the play here with workspace agents is for teams that are already embedded on a Chatt GPT business plan or a Chatt GPT enterprise plan, obviously, because that level of control is huge. There's also RBAC or roles based access control. So, you know, especially if you're a a heavy Microsoft organization or if you do need that very strict governance because with great power for workspace agents means great responsibility. So it's not like you are going to have, you know, swarms of agents going out and performing work and no way to actually go through and trace and observe what they actually did. So the control and governance side is a pretty big piece that you can go through literally. Right? I like I say, it's like showing your work back in grade school for math. You can go back and see every single run that an agent has done to know if something did go off the guardrails.
Jordan Wilson [00:25:54]:
Maybe you need to go and tighten that up. If you didn't get the best responses last week and you need to improve it, you can go see where it maybe went wrong and how you can improve it. Alright. So let's go back here and take a look. Let's see how our agent did. Alright. It's done. Cool.
Jordan Wilson [00:26:13]:
So now I'm showing you the view, for your agents that are already built. So like I said, this is a different account. I don't use this one a ton. This is more for testing, but now I have my Beehive AI story digest. Alright. So this is on my main agent's page. I can go in and edit this. I can copy the link.
Jordan Wilson [00:26:33]:
I can go in and start sharing, etcetera. So couple other things to point out here as I'm showing you now the inside. You'll see right now in the upper right hand corner, it is, it this is on a schedule because I told it conversationally, to run every single day. So I can go in and I can edit this. I can run it now or I can add a new schedule. So I can click on this as an example and say, maybe I want this on weekends, or maybe I do only need this Thursday. Actually, I really only need it Thursday, so I'm just gonna go ahead and update this. I only need this Thursday, and we're gonna say at seven.
Jordan Wilson [00:27:08]:
No. We're gonna say at 5PM. Right? Because this is for my Friday show. So this is gonna be an email that I'm now gonna get, at least just on Thursdays at 5PM because there's always a lot of releases on Thursdays. Alright? And I'm gonna update my schedule there. Perfect. So the other thing is I can see the latest runs. There's two different places here.
Jordan Wilson [00:27:34]:
There's one on the left hand side that says review the latest digest. So this does run every single day versus having to go search for the end. Right? Because my end output for this example was going to my, excuse me, was going to my email. So instead, I can click on this and chat with the agent and, you know, it'll send a prompt that says review the latest Beehive Digest and show me the top clicked, stories and AI updates. These are kind of starter prompts, and you can, add these to your agent. But let's go ahead and look at two other things. So this is your activity. There hasn't been a run yet.
Jordan Wilson [00:28:08]:
So let's go ahead and test this. So let's go ahead and let's just click run now. I do have one that's already done. So now you'll see at the top, it says, running automation. Alright. Which is, I'll probably just jump in. I have the email already done. But two other things I do wanna talk about.
Jordan Wilson [00:28:28]:
You can always see which apps are connected there. So at the bottom, you have your activity, your apps, and your memory. So you can see right now, the only apps I have connected are my Gmail and my Beehive. Let's say I wanted because you can take advantage of all of the capabilities. Let's say, I wanted to create a slide deck of these seven AI features. I can use, ChatGPT images too. I can create a slide deck and then I can have it save that slide deck as an example in Google Drive. So, maybe if I want to improve upon this workflow, I can do that and then you'll see those apps added as you go through and modify them a little bit more.
Jordan Wilson [00:29:05]:
Last but not least, memory. This is huge. So there's nothing in here yet, because our first actual run of this version is running right now. But, eventually, in the same way, like, projects have dedicated memory for anything that's happened in there, you're gonna have a persistent memory that's going to build up over time within your workspace agent. So what does that mean? That means that next week when this runs, it's gonna know the seven, you know, tools or I think, technically, I asked for 25 because I asked for the five biggest stories over the past five days. So it's not going to repeat anything. It's gonna have a running memory of what it's done each time that it runs. Alright.
Jordan Wilson [00:29:45]:
So that's kind of the big picture overview. We went hands on, but maybe let's quickly look, let's quickly look here at an output. Alright. So now I'm sharing my actual email. This is the message that was sent. So it went through. It told me the most clicked. Right? So it said this you know, as an example, this version had 309 unique clicks.
Jordan Wilson [00:30:10]:
Right? So it's going through each day. It's telling me the most click stories like I asked. Right? I'm scrolling through to the bottom. Here we go. It went through and it kinda did the thinking and the synthesis. And the real cool thing here is it also went and found additional sources on the web, which I told it to. So it could verify all of this information from the email, from inside Beehive. So it see now it ranked, let's see.
Jordan Wilson [00:30:37]:
It gave me the four that I should focus on the most. So I'd go through and I would ask for, you know, hey. Out of the AI features and LLM upgrades, send me the top 10. So I didn't tell it to. I just said go through and find the five stories from the last five. The five most click stories from the last five episodes. So it went through the 25, and then it suggested kind of the top four. So if I were going through and edit this again, I would say send me the top 10 that are actual AI features or LLM upgrades that you can use today.
Jordan Wilson [00:31:04]:
It did send me four. So it said the biggest ones that were the most clicked, the most interest was GPT 5.5 instant, which just came out yesterday. The new Claude Finance agents, Manus cloud computer, and Copilot in Outlook's Ghost Agentic. So there's a very quick overview of how all of that works. So now let me wrap up by zooming out a little bit. Should you use this? What's the difference between GPTs versus this versus codex, etcetera? Well, I will tell you this. Especially if you're on a team plan, I would not be creating new GPTs because we don't know what's gonna happen. We also won't know pricing on how these things are actually priced until later today.
Jordan Wilson [00:31:53]:
Alright. That's when OpenAI when they announced these workspace agents, they said May 6. Right? Essentially, yeah, free reign until May 6, and then they're gonna introduce some sort of usage based pricing. So not sure if there's a, you know, default kind of, rate that you'll have included or if it's gonna be a 100% usage based. Alright. So we'll know more on that, but let's take out future pricing aside and just look at the utility of utility of these three different things. So looking at GPTs versus codex versus workspace agents. Alright.
Jordan Wilson [00:32:24]:
So technically, some benefits of GPTs is, well, you can use them in any normal chat inside of chat GPT. Whereas agents are not really like that. They have predefined workflows. And, yes, in theory, you could turn whatever you're normally doing into a chat, into a, into a workspace agent. But still the biggest benefit of GPTs is within one conversation, you can kind of flip back and forth between a bunch of different GPTs, and you don't really have those capabilities, right now inside of, ChatGPT with Workspace agents. I'm actually double checking unless they, updated something, which I don't think they did. Oh, no. I say corrected.
Jordan Wilson [00:33:06]:
Alright. So I do it live and I always check. I don't think this feature was available when they first came out, but now I'm looking if you click the add button, you actually can, flip between different agents, which is really cool. Right? That's the fun part of doing these live and, you know, sometimes I forget to test every single feature during my prep, but I always wanna make sure that I do it while we while we talk. So, alright, in terms of benefits of GPTs then, there's not a ton. Right? Unless they're already really ingrained in your workflow. If you did a bunch of custom, set up on these GPTs. Right? Because you can connect, via third party via APIs, all those things.
Jordan Wilson [00:33:41]:
But like I said, eventually, OpenAI is gonna bring you a way to easily convert those into workspace agents. So I wouldn't start building new GBTs if you're on a team plan. Instead, I would look at well, either build them now inside workspace agents or wait for that conversion process. If you're on an individual plan and you don't wanna spring for the workspace agents, maybe you continue to worse g to use GBTs. Or you use codecs. Right? So these workspace agents are powered by codecs. So for those that were watching live, that's how, you know, it was kind of using my screen, and you could watch it, click around. Right? That's the power of codecs.
Jordan Wilson [00:34:15]:
For me, let me be honest. I very rarely use Chat GPT anymore. Little little secret. Right? The only time I really use Chat GPT is if I know I'm gonna need to access something via mobile. Right? So if I'm working on something throughout the day, I know I'm gonna be out and about, you know, that's when I'll actually use Chat GPT because then I can have it on the mobile app. Because right now, one of the biggest reasons why I don't just use codecs for a 100% everything, is, well, no mobile app. Although the team did kind of allude to that was coming. And we do know if you don't know codecs, you know, I think it's gotten, maybe not quite the most accurate representation of what it is because it was originally a cloud based developer tool.
Jordan Wilson [00:34:56]:
Now it is if you've ever used Claude Cowork or Claude Code, Codex is all of that and more in one unified platform, and it is for everyday knowledge work. So I'll just go ahead and put my personal plug. Codex is better than Claude desktop, Claude code, Claude co work by far, not even close. Codecs, in my opinion, much better than the normal, quote, unquote, version of chat g p t. So if you're a heavy codecs user, maybe you're not gonna find a ton of utility out of workspace agents. But if you are a heavy, enterprise team, a heavy business user that uses chat g b t right now, workspace agents are going to be your go to. That and the fact that they all run-in the cloud, whereas at least right now, for the most part, anything that you build in codecs because you can build. Right? They may not be called workspace agents, inside codex, but in your automations, you can build out the exact same thing.
Jordan Wilson [00:35:51]:
But the downside is, yeah, your actual physical machine has to be on, and the codex app has to be running for these to run. So that's kind of a very informal quick back and forth between GBTs, codecs, and workspace agents, but I'll leave with this. Whether you're setting these up in codecs or setting them up via a workspace agent that you can share across your organization, The big call out here is it is easier than ever without being technical, without knowing how to write any code, where you can just go and start converting all of your day to day manual knowledge work processes. Like, that's why I wanted to give you an actual example of how I'm using these workspace agents now with the custom MCP. This is a task that, you know, doesn't take me very long. It might take me an hour without AI to go into those last five, you know, beehive posts, scroll through, see which ones are the most clicked, click on it, verify, see if there's anything I missed, synthesize it, say which ones are actually available now versus which ones are available next month. Right? So maybe that process took an hour, but the biggest thing for me is while the context carry carrying that context over, but also the ability to get distracted. I think that's one of the biggest, you know, fringe benefits that people don't talk about is human distraction in the day and age of social media, the Internet, even AI.
Jordan Wilson [00:37:06]:
Right? You're, oh, wow. I could, you know, do a, b, and c while I'm in here. No. Go build, redesign your workflows front to back, and then give it to workspace agent, and then you don't have to really worry about it. Alright. I hope this one was helpful putting AI to work at Wednesdays. If you want if I should do a more in-depth show on workspace agents, if you wanna see more on it, if you wanna see more on codex, whatever it is, let me know in the comments. I always do go and check the Spotify comments or if you're listening live on LinkedIn.
Jordan Wilson [00:37:34]:
So thank you. If you haven't already, please go to your everydayai.com. Sign up for our free daily newsletter. Thanks for tuning in. We hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.