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AI Super Apps: The New Strategic Imperative for Company Leadership
OpenAI, Anthropic, Microsoft, Google, and Cursor are escalating a race that is fundamentally changing the use of artificial intelligence at work. The latest shift—AI super apps—points to a world where company workflows are not managed by a series of disconnected chatbots, but by deeply integrated, autonomous AI systems working directly on the desktop. The nuances in this race, overlooked by many, are surprisingly actionable for business leaders tasked with setting AI strategies.
AI Super Apps: Definition and Enterprise Value
An AI super app represents a consolidation of work surfaces—files, browser sessions, automations, memory, and approvals—brought together under a unified, agentic platform. Rather than requiring manual context inputs across different tools, super apps operate directly on the desktop, with the capability to read, write, and automate across the OS and key business applications 07:13. This full-spectrum access means AI systems are no longer limited passive observers or simple chatbots; they can manage files, control browsers, generate dashboards, and act on scheduled workflows 10:01.
Competitive Landscape: Super App Strategies from Leading AI Companies
The recent months have seen rapid movement from major AI companies:
OpenAI’s Codex is described as being “very ahead” of competitors, offering three unified interface panes for chat, workspaces, and browser/inspector control. Codex allows users to run automations at various intervals—hourly, daily, weekly—proactively ingesting context from emails, DMs, and files to produce actionable reports and outputs 14:05. It facilitates mobile access and can operate while the user’s laptop is closed, distinguishing itself in real usability.
Anthropic’s Claude Code and Cowork initiated the desktop agentic wave as early as late 2025 and early 2026. Despite strong core models, Anthropic is currently disadvantaged by a fragmented harness: its desktop agents lack unified memory and seamless tool integration, which limits their ability to capitalize on context across tasks 28:20.
Microsoft’s Upcoming Super App is likely to leverage the new GitHub Copilot desktop application as an infrastructure layer, with plans to unify data from Microsoft 365 and introduce agentic Autopilots for deep desktop automation 26:47.
Cursor provides model flexibility, enabling use of GPT, Claude, Microsoft, and Google models within a single harness. Its strengths lie in token efficiency and developer-centric user experience, positioning it as a strong challenger—especially as it gains resources and vertical integration from high-profile industry partnerships 25:16.
Google Antigravity 2.0 arrived with their Gemini 3.5 Flash model, aiming for fast, broad code execution. However, early feedback focuses on its lack of features and doubts about its value compared to more robust competitors 32:00.
Super Apps: Execution Layer and Business Differentiation
The critical takeaway: the business moat in generative AI is now shifting away from core model quality to the quality and user experience of the harness—the super app execution layer 07:37. Since advanced models present diminishing incremental returns for the average worker, only a small share of users can exploit their full depth. Accordingly, the company advantage now depends on how smoothly these agentic harnesses connect data, tasks, and approval flows to daily business operations 22:24.
Codex currently leads because it integrates file and browser previews, real-time mobile access, and autonomous desktop control 23:42. Cursor’s open-model approach and proven developer workflow may also accelerate enterprise adoption by reducing cost per token and supporting broad internal customization 24:50.
AI Super Apps: Risk, Permissioning, and Deployment Strategy
With great capability comes operational exposure. AI super apps can execute scheduled or hands-off workflows, modify files, alter application settings, and operate on terminal commands if not strictly governed 34:02. This brings substantial risk of data loss, misconfiguration, or unauthorized access—especially if businesses rush deployment without strong approval paths, guardrails, and tiered sandboxing.
Recommendations emerging from super app deployments include:
Start with Read-Only Automations: Initial rollouts should avoid write access and enforce strict approval workflows, minimizing the impact of misconfigured automations 36:34.
Prioritize Training and Context Engineering: Effective AI harnesses require teams to understand agentic prompt structuring, chain-of-thought reasoning, and low-risk task automation before scaling to more complex actions 35:21.
Role-Based Access and Redundancies: Proper permissioning and robust backup protocols are non-negotiable to contain risks as AI super apps take on broader operational scope 34:16.
The Path Forward: Practical Next Steps for Company AI Strategy
Enterprise adoption of AI super apps is not hypothetical—corporations are already rolling out these platforms at scale, sometimes to tens of thousands of employees 13:41. The window of advantage for fast movers is shrinking as competitors iterate their harnesses and business integration becomes the new technical battleground.
Actionable recommendations include:
Adopt a staged deployment, beginning with low-risk, read-only automations and strict approval routines.
Build internal expertise in context engineering—ensuring those configuring automations can anticipate and interpret agentic chain-of-thought operations.
Choose platforms with unified context memory, robust desktop and mobile access, and model flexibility.
Monitor developments in Codex, Cursor, and Microsoft’s ecosystem as leading indicators of what robust business harnesses can deliver.
In summary, the future of AI in the enterprise is being shaped not merely by model advances, but by how agentic systems are deployed, harnessed, and governed at the execution layer. Business value will accrue to those who invest not just in access, but in controlled, context-rich, and expert-driven AI harnesses right at the desktop.
Topics Covered in This Episode:
- AI Super App Race: OpenAI, Anthropic, Microsoft
- What Is an AI Super App? Explained
- Agentic Shift: Chatbots to Autonomous Coworkers
- Super App Harness vs. AI Model as Moat
- Three-Pane Super App Interface Innovation
- Codex vs. Cursor vs. Claude Benchmarks
- Enterprise Desktop Integration and Super App Strategy
- Super App Security, Risks, and Best Practices
Episode Transcript
Jordan Wilson [00:00:16]:
Any hour or day or week now, we'll get an official announcement from OpenAI that signals the biggest AI pivot we've seen since Chat GPT, and that's the official rollout of their AI super app. So the ChetGPT parent company, now with 1,000,000,000 weekly active users, made headlines recently when a senior executive off the record at least said three words to a reporter that will probably echo for months. Chat is dead. So any day, we'll get the official announcement of OpenAI's new super app. They're pushed to bring an autonomous coworker to millions of companies. But it's not just OpenAI making this push. Actually, Anthropic started the wave many months ago with their rollout of Claude Code and Claude Cowork, and every other big tech challenger is racing to get their version of an AI super app some momentum. Google released theirs in anti gravity two point o.
Jordan Wilson [00:01:20]:
Cursor has quietly become a serious cont contender in the space, and Microsoft also announced their upcoming super app as well. But that begs the obvious question. What the heck is a super app, and why should my company take note? Well, we're gonna tackle the latest work layer shift on today's show. So welcome to Everyday AI in our start here series. But let's go over the big picture of what's happening now. So Infropic started this desktop agentic era with Claude Code and Claude Co work in late twenty twenty five and early twenty twenty six. But Anthropic hasn't really been able to build off of that momentum at least when it comes to being the big name in the room when it comes to an AI super app. And I think OpenAI's super app, which is essentially codecs.
Jordan Wilson [00:02:13]:
Right? And it will, be a little more tightly integrated into ChatGPT will be coming any day. And I think that's really gonna set the tone for this big pivot to the super app era. Right? And Microsoft, I think, especially when you have OpenAI and Microsoft in the coming weeks or months, shifting most of their agentic focus to a super app. I think the rest of the enterprise really needs to pay attention. So on today's show, we're gonna be diving into and stick with me for the next twenty five minutes, and here's what you're gonna learn. Why Anthropic started the super app race, but they have kind of fallen out of immediate contention. You're gonna know why the models are no longer the moat and the Super App harness matters more than ever, and you're gonna kind of know the state of the Super App race at least as it stands right now, right before we officially get it all kicked off. Alright.
Jordan Wilson [00:03:10]:
Let's get into it. Welcome to the start here series. This is Everyday AI's essential podcast series to both learn the AI basics and to double down on your knowledge. So if that's what you're trying to do, we're at the, the tail end of the start here series. Right now we're in, episode what are we on now? We're on, volume 28 of this. So we'll probably do two more and wrap it at thirty. But if you don't know the start here series, it's great. I would say start at volume one if you can, and work your way up to where we are now.
Jordan Wilson [00:03:40]:
They're usually quicker episodes about thirty minutes, give or take, but make sure you go to starthereseries.com. There, we put together a playlist where you can listen to every single episode of the start here series so you don't have to go fishing around our website or anything like that. And that's also going to give you exclusive access to our inner circle community. Yeah. Right now, that's the only way to get open access to it. So you can not only sign up for our free inner circle community, which gives you access as well to our prime prompt polish, version three course to learn context engineering one zero one at your own pace, but also all of the start here series info. Alright. And make sure if you didn't listen to our last episode, I think it's an important one in the start here series, which was volume 27.
Jordan Wilson [00:04:24]:
We went over the token maxing era and how it's over and talking about the new era of token efficiency and how your company should adapt. So make sure you go check that out. That's volume 27 or episode seven eighty nine. But let's get into today's topic, which is the AI super app. So what the heck is an AI super app and why does it matter? Well, I'll say this. Even though I don't think we've, quote, unquote, arrived in the super app era per se, I will say it's safe to assume this is the next version. Alright. And it is funny because we started the start here series in January, and we've actually seen kind of two shifts.
Jordan Wilson [00:05:09]:
So I think the first shift we saw in January was models becoming more and more agentic by default and saying, hey. How the future of work is not, reactively talking to AI chatbots. It's knowing how these models work, scheduling things out. Right? And then we also had another episode talking about something I called agentic context carry. Right? And that is the crucial role that, not just models, but the harness that control the models play in taking context from your certain apps. Right? So, to boil this down to the the basics here. Right? One of the biggest advantages of not just the upcoming super app era, but where we're at now, right, before Microsoft and OpenAI start really highlighting, and promoting their super apps. Right? Where we're at now is we do have these systems that can carry our contacts autonomously.
Jordan Wilson [00:06:04]:
Right? So a lot of what the human duct work, duct tape work has been over the last two years is us humans who do use large language models is giving a chat our context. Right? Connecting whether it was static files, dynamically, shifting things, but then it's a lot of copying and pasting from different AI systems. But now as these systems are living on our desktop and becoming more autonomous, that does leave, kind of lead into the next wave, going beyond this agentic context carry, and that's where the agents ultimately live, which is the desktop OS. Right? That is where I think these super apps are going to play. And I don't know if this is going to be the, quote, unquote, final frontier of the agentic era as we have officially entered into it. It may look a little bit different, but I do think at least, the companies that are gonna be most successful in late twenty twenty six and early twenty twenty seven are those that are gonna be investing in their companies using these super app systems on the desktop. So the core idea of this is simple. Right? A super app is bringing all of your different work surfaces together under one agentic roof.
Jordan Wilson [00:07:20]:
So the big AI tech companies are all building their own super apps. They know the same truth. An AI chatbot is not a moat. Right? Chatgbt.com is not a moat. The model is not the moat. They all want to own the execution layer. Right? And that is why every single big AI tech company is trying to build an AI super app. You could call it the harness.
Jordan Wilson [00:07:46]:
Right? Kind of the, the place where all of the tools come together, but it is much more than that. And I think we'll see, as we really, roll out and dig into what a super app actually is. But at its basis, I think it combines a couple of different things. It combines your company's context, your files, browser access, a file viewer, automations, unified memory, and approvals and automations all in one unified platform. And, you you know, we're gonna get into some of the the nuances and the pros and the cons and all of those things. But the way I like to look at it now, and this is after I've been using, especially codex heavily. Right? I I also use the claw desktop programs heavily, but I do think codex is in the lead in the super app. Right? And OpenAI has essentially said, FYI, they're saying, yes.
Jordan Wilson [00:08:41]:
Codex is the early version of the super app, which is why I've been encouraging people to use it so far because I do think codecs is very ahead of all of the other quote, unquote super apps. We've seen that by how they're all the other big tech companies are kind of just copying and pasting exactly what OpenAI has done with codecs because it is that good and it is that far ahead. But this is essentially the way I look at a super app right now, it is a full, like, intern. Right? It is a full almost human coworker because anything that I can do, right, a super app can do. And I don't think this was the case in late twenty twenty five with with Claude Code. I don't think it was the case in early twenty twenty six with Claude Cowork either. Because now where we're at right? So aside from what I said, dynamic access to your company's files, automations built in, approvals built built in, and then having these kind of three different pains, and we're gonna talk about that a little bit more. But then also the ability to control a browser and the ability to control your entire computer.
Jordan Wilson [00:09:41]:
Because at that point, that's when you can kind of, right, say, okay. This system at least has the capability to be a true researcher, to be a true, you you you know, in terms of an output. This can output something like a smart human actually could because it has access to every single tool. Alright? And there's obviously great downsides to this because with great power comes great responsibility. But, essentially, the super app gives read write access to your entire computer or can if you give it those permissions and kind of go in YOLO mode. Right? But it can download, it can upload, it can change different settings on your computer. Right? You can even, with codecs at least. Right? I can if my MacBook Pro is closed, I can still control my MacBook, you know, from my phone.
Jordan Wilson [00:10:29]:
So it also brings in that, you know, that remote aspect as well, which is why I do think, OpenAI's codex is a little more behind. Right? Because even if, you know, my my my laptop is closed or, you know, if my coworker is not in front of the desk, I can still send a message and they can still get to work and report back to me. Let's clear up a little bit about the name Super App first. Right? Because I think that there's a little bit of a mix in terms of when you throw the word super app. Because in the pre generative AI era or even in the early chat g b t days, when people heard super app, they instantly thought of China's WeChat. Right? So that is the super app, the, original super app OG. Right? So they have messaging, payment, shopping, banking, everything. And I think that that was kind of one of the big goals of x slash Twitter slash early grok.
Jordan Wilson [00:11:22]:
Right? It was this everything app ambition. Right? It was moving all of your day to day personal life into a single app like China's WeChat. But that's not what I'm talking about here when I talk about the new era of super apps, because I think for whatever reason, that dream has maybe been dashed. And maybe it's because most of the big companies have understood and realized, wait. Why would we go after this on the consumer side all on a smartphone when there's a much bigger opportunity to do this AI super app on the desktop side and to go after companies that are spending millions of dollars on this every single year? So a bigger way to capitalize in a faster way to roll this out across the enterprise as well. So now you know it's not the, you know, quote, unquote traditional WeChat mobile super app. We are talking about an AI, desktop companion, and it's better than a chatbot. Right? I don't think I need to go into too much depth on why a desktop super app is better than a chatbot, but let me just go over the basics.
Jordan Wilson [00:12:31]:
Right? A chatbot, I still have to go on. I have to make that decision. I have to go on to whether it's claw.ai or chatgpt.com or gemini.google.com or whatever. I have to proactively go in there and give information to a chatbot. I have to share the contact, share my problem, share all these things. With a super app as an example, you can have automations that run, and this is how I have it set up. So whether it's hourly, twice a day, twice a week, whatever you wanted to do, You can have it go through with your custom instructions every single important piece of your work life. Right? And, obviously, I need to put the giant the giant grain of salt out there.
Jordan Wilson [00:13:12]:
Right? Don't go and download, you know, codecs or, you know, whatever the, the Microsoft Copilot version of their super app. I think it's gonna be powered by GitHub Copilot. So they do have their version of that, but it's just not unified yet. Right? This isn't something where you're trying to use this without your company's permission. So if you are a business leader, if you're a decision maker at the enterprise level, you need to start saying, hey. Is there time that we invest in a super app strategy? And the smart companies already are. Right? Months ago, I was doing, you you know, big trainings for companies that rolled this out to tens of thousands of employees. So if you think, oh, companies aren't doing it.
Jordan Wilson [00:13:50]:
Yes. They are. They definitely are. So if you are not, you are behind. But there's a lot of reasons why it beats your traditional chatbot. But I think the biggest couple are, number one, it's always on and autonomous. Right? So you can schedule, these things to happen. Right? I have ones that run, about every four hours.
Jordan Wilson [00:14:13]:
I have runs that run every day. I have different ones that run every single hour, on codecs, especially, because then it can share all of this context. So whether it's going through my email, you know, every hour, it's going through social media every four hours, it's going through my my DMs every 12 hours, and then it's just reporting back to me, and then I can make those decisions. Right? So you can see right away how that's immensely more in, helpful than a a a chatbot that is really just, reactive. And I have to go in and the chatbot reacts to me, but I have to be the one being proactive. We're on the AI super app, and it is actually the AI super app that is the one being proactive in delivering me, decisions. Right? And saying, hey, human. I followed my rules that you set out for me.
Jordan Wilson [00:14:58]:
Here's all the this the decisions that you need to make. I went ahead and built you this dashboard. I built you this deck. I built you, you know, all these things. You approve the one which is best. Go through. Give me your updates, etcetera. Right? So there's a lot of reasons why the AI, app beats the, you know, the traditional chatbot.
Jordan Wilson [00:15:20]:
And the biggest thing, it's the interface. Right? So let's talk about this kind of three pane interface. So first, there's a lot of the you know, you have to tip your hats to the OGs. Right? I think one of the companies that actually got the three pane interface done really well early on was Google's notebook l m. Obviously, Anthropic started the, phase of the desktop agentic coworker, with Claude Code, the desktop version in late twenty twenty five, and then with Cowork in early twenty twenty six. But, essentially, if you're not watching the video version of this, I want you to think of three panes. Right? So on your left pane, that's your traditional chat and folder pane, but then you also have your automations. So that's where you have your different kind of workspaces.
Jordan Wilson [00:16:08]:
That's where you organize, you know, all of your kind of agentic flows. In the middle, this is kind of your instruct panel. This is where you are actually chatting with the chatbot. So right in traditional, you know, chat gbt web interfaces, this is the same. On the left side, you have all your chats, your folders, etcetera. And then on the panel to the right, that's your, ability to chat. Right? So the difference here in the big, jump is the right panel. This new panel, you know, you can call it the inspector panel, whatever you wanna say, the browser panel.
Jordan Wilson [00:16:43]:
But this is where you bring in that context, and you don't have to lose or degrade the agent's ability to bring it in. So as an example. Right? The earlier days of of of Claude, it had a very clunky browser use. Right? But now with today's version with, like, codex, it has a built in browser there on the right side panel. So it cannot only browse the web without having to, you know, connect a third party tool or a second party tool technically by controlling a browser, but it has its own browser inside of the program. So it is much faster. It is much more accurate. It is much more token efficient.
Jordan Wilson [00:17:26]:
Right? That's the big thing as we talk about token efficiency is gonna be one of the biggest, trends of the rest of 2026. To be able to bring in that inspector or browser is a huge piece of what makes a super app in the actual super app. Right? So not only bringing in the right side browser or the right pane or the inspect pane browser, for the Internet, but also for any files, but also to preview anything that you're actually building. So at least for me, I've been trying to spend more and more of my time in that right side pane. Right? So bringing in my browser sessions so I can control that right side pane or, you know, codex or the super app can control it as well. I can bring in my files, my PDFs, my word documents, and then also preview different things I'm building there. But I can control that pain. Right? Or codex can as well or the super app of choice can as well.
Jordan Wilson [00:18:20]:
So you can see there by doing your work in an interface that the super app can see and work with you is obviously a huge advantage and one of the biggest steps, toward the, agentic work future. So let's quickly talk about the race right now. So I will say, codex and chat g p t, they're ahead by a far margin. And I don't think anyone is going to dispute that because even, Google literally copy and pasted codex. Right? Even in their launch video of anti gravity two point o desktop version, they accidentally left something in the video, the launch video that had a codex folder. It is a spitting image of codex. Right? Even with Microsoft's new GitHub Copilot, very much set up like codex. Alright.
Jordan Wilson [00:19:14]:
Cursor, very good, in its own right. Claw Desktop, I I I would say it's a little far behind. And, you know, you can even look at different benchmarks that talk about the harness. Unfortunately, Anthropic has some of the best models in the world. Right? Literally, the best models in the world. Their harness is bad. That's not my opinion. That's every single benchmark that looks at, that looks at, harness, tool calling, etcetera.
Jordan Wilson [00:19:42]:
So, yeah, the Claude models perform much better inside cursor as an example than they do inside of Claude desktop. Yeah. Yeah. It's I don't know. I don't know if they decide it to be token inefficient on purpose. I don't know. Right. Again, I'm not talking about the command line interface.
Jordan Wilson [00:19:58]:
I'm so I'm not talking about the CLI, side. Right? I'm talking about the, you know, everyday knowledge worker who's downloading these desktop programs. But I'd say right now, if I had to call who's where in the race, I'd say number one is codex. I'd say two a is probably cursor. I'd say two b is clawed desktop, and then I'd say the rest is, like, to be determined. Right? Anti gravity, not not a big fan, of that one. Microsoft will see where they land. I do think their new GitHub Copilot app will ultimately be the kind of the underlying harness that will, kind of power their super app that CEO Satya Nadella, previewed at the Microsoft Build Conference.
Jordan Wilson [00:20:45]:
And then you have others. Right? Grok has their new build. That's still too early kind of in the beta phase. But, I mean, just in the past month, you know, and with what codex has coming up, we've seen four of the six big players say this is where we're focusing a lot of our engineering efforts from here on out. And I'm not saying that the model can no longer become a part of the moat, but I think there is going to get a certain point. Right? I'm trying to, come up with a good way to verbalize this, and maybe I'll do a show on it in the future. You you know, the way I think of it is, like, ninety five five. Pretty sure we're gonna get to pretty soon, I I'd say probably early twenty twenty seven.
Jordan Wilson [00:21:29]:
We're gonna get to the point where only 5% of people can actually take full advantage of 95% of what a model has to offer. I think there's gonna be a certain point where your your average even your technical person is not going to be able to take advantage of 95% of what a model can offer. So that's why I think more and more, at least when it comes to short and medium term enterprise adoption, I think it's actually more about the user experience of using the harness, than it is about the model, which I think is actually one reason why cursor is actually nice nicely positioned in this. So let's quickly go over why I think codecs leads right now, and I'll give you quick takes on all of them. I think codecs is by far they they've set the the bar very high. Mainly just because everything works, and they are the only one out of the bunch that has every single thing that I talked about. Right. So the three panes, all work.
Jordan Wilson [00:22:27]:
Right? Specifically on the inspect or browser, they have the code preview pane, they have the file preview pane, and then they have the, the browser pane. All connected, which I think only two others have. So not everyone has all of those different, elements, which I think all of them are very important. But the other reason why I think codecs is very far ahead, two reasons. One, for the laptop crowd, you can literally have your laptop closed, and codecs can still run everything as if your laptop was open and logged in, which I still don't understand the wizardry that OpenAI did to make that work. Alright. But then the other thing is being able to access this from your phone. Because as you are on the go, I you know, this is weird.
Jordan Wilson [00:23:13]:
I've never been able to get so much work done from my phone. So I think that's two reasons why aside from the obvious design and UX of codecs, which everyone is copying, but the fact that the computer use, the browser use are just a step ahead of everyone else, the actual harness itself, but the ability as well. Your computer can be closed. It it can be on the lock screen logged out, and to be able to access everything from your phone is huge. Right? So as an example, we're gonna talk about, Anthropic's claw desktop here. It's like they have dispatch where you can kind of access some things from your phone, but it's super buggy. And you actually can't you know, as an example, you can't access everything. You get one thread that's just a dispatch thread, which to me wasn't very helpful.
Jordan Wilson [00:24:03]:
But I think codecs really leads. But I think cursor, yeah, Cursor might actually be one of the best challengers, at least right now, in the super app game. So not only have they, you know, kind of been in the super app space a little bit longer than everyone else, but they've had the developer feedback. Obviously, now they have this partnership, with SpaceX, which just had the largest IPO in history. So you can't count Cursor out because they're gonna have more and more resources, to build, this this their kind of super app, but also their own model as well. Their new composer, I think it's composer 2.5 model is really good. It is token efficient and, you know, you can kinda get about 90% of what you can get out of, like, an Opus 4.8 for, like, 10% of the cost, which is why one of the reasons I think you can't count Cursor out. They've been in this space the longest.
Jordan Wilson [00:25:04]:
Their user experience and the harness is really good. It's been, shaped and loved by, many developers for multiple years, and they have the one big advantage where you can use literally any model. This is the only one where you can use any models. You can use, you know, the GPT models. You can use the Claude models. You can use Microsoft's models. You can use Google's models and their own models. So Cursor, I think, you have to pay close attention to.
Jordan Wilson [00:25:32]:
Next, Microsoft's could be. Right? We don't know. Microsoft has said their super app is coming. I know people laughed at me, like, six months ago when I'm said I'm actually kind of bullish on Microsoft. Right? They we've seen some pivots that in early twenty twenty six that was kind of against their strategy of 2025, which was creating more and more products where it seems like they are going to this super app strategy and trying to streamline and unify everything. So we don't know what it's gonna look like. I do think that their recent GitHub Copilot desktop app was well received. I think what was not well received was their, kind of coupling that with the, unsubsidizing, of their plan.
Jordan Wilson [00:26:18]:
Right? So, yeah, we talked about that in, the last episode. But so I think a lot of people had a sour taste from GitHub Copilot's pricing moves, but their actual new desktop app that they rolled out for Mac and Windows, it's really good. And it does look like that's gonna serve, like, the underlying baseline, of the feat of the future Windows Copilot super app. So they did talk about this at their build conference in bringing also kind of the new element that they're gonna be bringing into this is their autopilots. Right? So this is their their version of an autonomous coworker that works on your desktop. Right? It can read, write, you know, you can schedule it, and they can access all your Microsoft three sixty five data. So even though Microsoft's version isn't out yet, I do put this fairly high up. Alright.
Jordan Wilson [00:27:03]:
Let's talk about Claude and Anthropic because they deserve a ton of credit here. Because I think without, Anthropic's move, in late twenty twenty five and early twenty twenty six, specifically with Cowork, I don't know if we would be in this era of, Agentic AI and AI super apps. So, I do think even though they've they've fallen behind maybe a little bit, and probably Claude, you have to give them their shine on this. Right? Because even I remember working with the early versions of Cowork, I'm like, even though this is slow, even though it's clunky, even though it fails sometimes, when it did get something right, co work was mind blowing. And I do actually think, which maybe this is because I do this every single day, I do think the enterprise now is just realizing. Right? Because I think the enterprise is always about three months behind kind of cutting edge AI, which is why I still think that there's this momentum, around Claude Code and Claude Cowork and and, you know, Claude's desktop offerings. But at least when you compare it to what's out there right now, specifically with codecs, I do think they're behind. One of the reasons why, and I've done this on the show before, I showed this, it's not unified.
Jordan Wilson [00:28:16]:
Right? Claude Code has no clue what Claude Cowork is doing. And on the desktop, there's essentially three different modes. You have your standard chat, you have your Claude cowork, you have your Claude code, and none of the others know that any of the others exist. So there's no unified memory, which is one of the biggest downsides, of something like an autonomous AI super app. Like, it has to know everything. That's one of the things I think codex is great at. Codex can actually go in and start new codex chats on its own. Right? Which is great, right, when it comes from an organizational standpoint.
Jordan Wilson [00:28:50]:
You can't do any of that with, Anthropic's desktop offerings now. The easy I guess, the the the bright side for, Anthropic in what they should be doing, because this would even change my per per perception on the current AI race. All they have to do is do what everyone else has done. They'll copy OpenAI, they'll copy paste codex, and that turns what I think, the rest of 2026 and 2027 looks like. If they don't, I do think OpenAI has the ability to really run away, especially with the however many weeks or months or quarters we have until Anthropic and OpenAI both go public. I think OpenAI is gonna be way further ahead than most people are giving them credit for unless Claude essentially, or Anthropic copies, co work, which or or sorry, copies codex, which I don't know why they haven't. Everyone else has done it because it's very popular. It's the best thing out.
Jordan Wilson [00:29:49]:
Right? So, yeah, we'll see. We'll see what Anthropic decides to do. Next, Google anti gravity. To me, again, aside from being a, a I don't wanna say anything, bad about the team there, because I do have good relationships with a lot of the people at Google. I don't think they should have released their anti gravity two point o. It's it just wasn't ready. It's it's there's hardly no features. I don't know.
Jordan Wilson [00:30:19]:
They rolled this out, right after their IO conference. You you know, they rolled it out in conjunction with Gemini 3.5 Flash, which I thought was a good model. So they thought that, hey. The combination of this fast coding, you know, model Gemini 3.5 Flash that can do this long autonomous work, Let's couple it with Google anti gravity, and, you you know, it's gonna be this great splash. I I I don't think it played out like that mainly because I think Google kind of changed the Flash model from what people expected versus what they were making it. Because I think the way people looked at Gemini 3.5 flash was it's a cheap fast model, and it's no longer cheap. It's still very fast, but it is expensive relatively compared to every other, quote unquote flash model that Google has ever released. So in that aspect, by tying it together with the anti gravity two point o, with the Gemini 3.5 Flash, maybe hurt adoption of anti gravity, but that and just the features aren't really there.
Jordan Wilson [00:31:15]:
Yes. It's an earlier version. Yes. They have basic automations. You you know, you can use a couple other models. Right? You can use the Claude models, in there. Not for me. Right? Just not enough features.
Jordan Wilson [00:31:30]:
It is, like, the most bare boned, kind of super app you can think of, right, where I think codecs is robust, you know, even cursor and, claw desktop, much more robust. Anti gravity, it's not super clunky. It's just there's, like, no features. So maybe it's great if you want to learn what a super app can do, and if your organization is heavily bought into the Google ecosystem, maybe it's a good place to start and get your kind of super app feet wet. But if you have the choice to use the others, I would not personally use Google anti gravity two point o. Although, I do hope that they continue to improve it in the future, and I think they will because, like I said, they did give it a lot of spotlight, at their Google IO conference. Alright. So let's begin to wrap this up and because we have to talk about the other side.
Jordan Wilson [00:32:21]:
I talked about all the reasons why, hey, Super App is the next trend. It is the next wave of work. It is the execution layer. Right? It is the harness because I think most of the big companies know that the the the kind of the benefits or the advantages, over new models is gonna become less and less as a smaller and smaller, section of the enterprise will even be able to squeeze out the juice. Right? Let's just say as an example. Let's say Fable 5.1 or, you you know, GPT 5.7. What percentage of people What percentage of people honestly are going to be able to take true advantage of those point step releases? And I think not a lot. So that's why I think the emphasis in the moat in the short medium term is actually gonna be on the user experience and giving people the harness to power all of this.
Jordan Wilson [00:33:13]:
But with that comes great responsibility. Right? Essentially, let's talk about YOLO mode. Essentially, I can set up, and you can set up most of these super apps to quite literally do anything. And when you talk about the ability to read and write any file, any folder to use the terminal, you can accidentally, if you're not paying attention, to use to have browser use, to have computer use, if you don't have the right, role based access controls, if you don't have the right user permission set up, if you don't have redundancies and backups, these AI super apps, if you're whether the person's trying to be a little bit too aggressive in automating too much of their work, whether someone's being a little lazy and not really paying attention, whoops, you can accidentally do a lot of harm. You can accidentally delete something. And if you don't have, something properly permissioned, if you don't have the backups, in place, yeah, you can the the the the AI super apps, there's actually the risk is in the action. Right? The power is actually the downs the downside and the downfall as well. Right? I did a training for a large, organization, a a a couple of months ago that was rolling out kind of a a desktop super app to thousands of users.
Jordan Wilson [00:34:31]:
And they were asking me, hey. How should we be using computer use? And I said, don't. Right? Don't. You know, you shouldn't you like, some of the more powerful things, you can go and change settings on the computer. If you're not, strict enough in your context engineering or prompting process, sometimes these systems, especially if you're using, inferior model, they're gonna look at the end goal, and they're gonna build a completely new path that might be a path that's detrimental to your group. So, you know, if you're not paying enough attention to learning, and if your company, your department, you personally, if you haven't put in the proper, time to even understand the agentic natures of these models by default, I wouldn't recommend, you know, letting these things loose and then having hands off. Right? Human in the loop plus an AI super app is not a good combination. That's why I preach expert driven loops.
Jordan Wilson [00:35:27]:
So if you are doing true human in the loop, that's where you give it a prompt. And, I'm gonna have it go run for forty eight hours. Let's go token maxing. Let's use computer use, browser use, everything, and just have it solve all my all my issues for the quarter. Right? And just go truly hands off YOLO mode. If you don't know what you're doing, if you don't know what that agent is capable of, things can go down a sour path. If you just go truly, oh, I'm the human in the loop. Let me set this up.
Jordan Wilson [00:35:53]:
No. You have to have an expert driven loop. You have to be very hands on in learning and understanding these capabilities, reading the chain of thought, iterating, sandboxing, you know, sandboxing, your your browser use that first until you fully understand it. Because they can you can log in to any any SaaS application that you and your company use even if there's not an API, even if there's not an MCP or a direct integration or a connector in these super apps. Right? You can go log in and, well, the super app can control whatever browser you're using. So the risk is immense if you are not properly learning, and keeping up with all of the developments. So let's wrap here. Here's where I think you should start.
Jordan Wilson [00:36:34]:
Start here. Read only first. Right? Add approvals. You need to be sandboxing these things. Instead of rolling these out to hundreds or thousands of employees because there is going to be, I think, the the urge to do this. Right? Whether it's in a couple of days or a couple of weeks when OpenAI unveils and opens up their super app. Same thing with Microsoft as we undoubtedly see improvements from Anthropic and from Google as well. I think most people are gonna wanna rush in.
Jordan Wilson [00:37:02]:
Right? They're like, oh my gosh. Look at all these new capabilities. Don't. Read only strict permissions, guardrails, training, learning, and development. You have to be educating because I think this is where when I talked about agentic crash, you know, in our 2026, AI prediction and road map series, this is where agentic crash happens. When you have companies that give too much access, not enough training, you you know, too much power without proper responsibility and training. So you have to automate the low hanging fruits with low risk. We've talked about how you can tear off the different risk.
Jordan Wilson [00:37:39]:
So that's where you start. Don't start with the highest capabilities, with the most hand off and autonomous, actions because I know that's the that's the that's the sexy thing. Right? You're like, oh my gosh. I can automate 90% of my work, have this thing work for forty eight hours, and I can come back and it did two weeks of deliverables for me. Oh my gosh. Let's do it. Let's do this at scale. That's not where you start.
Jordan Wilson [00:38:03]:
Alright? You have to be able to crawl before you walk, walk before you run. So don't start this with the sprint. You will get burned. Alright. That is a wrap previewing with the AI super apps and why every company is racing to create one, what they are, and, hopefully, how your company can properly take advantage of this. So if this was helpful, make sure you go to starthereseries.com. That's gonna give you access to our everyday AI inner circle community, a playlist with every single start here series episode on there, and you can go connect and network with other business leaders who are trying to do the same. So thank you for tuning in.
Jordan Wilson [00:38:39]:
Hope to see you back tomorrow in everyday for more everyday AI. Thanks y'all.