Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 723: From AI Chatbot to Autonomous Coworkers: How Consumer AI Has Changed and What's Next (Start Here Series Vol 10)

Starting point is 00:00:00 This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. Three and a half years ago, AI was kind of like a party trick.

Starting point is 00:00:51 I mean, if your entire company or department was using AI in late 2020, people probably would have thought that you were crazy or you could have easily gotten into some hot water. Oh, how the times have changed. I mean, now if your entire department isn't using AI, you're definitely in hot water. That's because there's a good chance that you, your company or your department might be sinking if you're not. That's because the rise in prominence and capabilities of AI has been astronomical over the past three years. And we've gone from AI chat bots that

Starting point is 00:01:29 were kind of fun to play around with to straight up autonomous co-workers that are doing the work for enterprises. So that's what we're going to be tackling on today's. show volume 10 of our Start Here series, giving you a quick overview of how AI has gone from a chat bot to an autonomous work, coworker, and how consumer AI has changed. And what's next? All right. And if you are brand new here, awesome. Great time to jump in. This is part of our Start Here series. This is our essential podcast series to both learn the AI basics and to double down on your AI knowledge. So like I said, we are on volume 10 of our start here series. And if you want to go listen to the entire series in order, I actually just dropped a Spotify

Starting point is 00:02:24 playlist so you can do just that. Super easy. So make sure you go to start here series.com. So that's also going to give you free access to our inner circle community so you can go learn and network with other business leaders like yourselves that are learning AI. I go listen to every single start here series, read about it. It's all in a dedicated space there. And you'll get access to our free prime prompt polish course. And hey, talking about starting here, right? Because after 700 plus episodes, I didn't have an answer for what people said,

Starting point is 00:02:59 where should I start when listening to your podcast? I was like, I don't know. Well, listen to the start here series in order. But along the way, make sure you go listens to episodes 713 and 712. that is our 2026 AI prediction and roadmap series. All right. Last episode in Start Here, we talked about agent risk security and AI sprawl in in 2026, why AI that acts changes everything.

Starting point is 00:03:24 So make sure you go listen to that, the last episode of our Start Here series. And now let's jump into today's from AI chatbot to autonomous coworkers. So on today's show, all right, I'm going to go over the five phases of AI Enable. work and why most teams are still stuck in phase one or two. I'm going to tell you how and why every major AI company is suddenly racing to put agents on your desktop. You're going to learn about the hidden layer that almost no one is talking about that changes how AI works for you or your company entirely.

Starting point is 00:03:58 And then we're going to end with my five actionable takeaways for what's next. Because yeah, it's been a fast sprint from AI chatbot to autonomous coworker. and we are not done, obviously. So let's first start with a zoomed-out overview of what the heck has happened. So large language models are not new, right? They've been around for a long time, technically, well before even the chat GPT moment of November 22. But let's start there, shall we?

Starting point is 00:04:32 Okay, so that's kind of when the whole, right, generative AI and large language model phase, and the corporate world kicked off was in November 2022, right? Many people, including Nvidia, CEO, Jensen Wong, call that the line in the sand, right? So November 2020, chatGBT launches, you know, it's a simple Q&A chatbot in a browser tab. All right. Then let's fast forward to where we are today. February 2026. I mean, we have AI agents that can run recurring tasks on your desktop with local.

Starting point is 00:05:09 file access, right? So at that point, they can use your browser, they can move files, they can upload, they can download, right? At that point, they are an actual autonomous AI co-worker. So that's where we started, right? This is like one of those social media posts, like how it started, right? In AI chat bot that was a party trick that didn't really know anything to, okay, this thing runs just like a human would. It can work on your desktop. It can use your files. It can move your files, upload, download, use your browser, right? Access all your data.

Starting point is 00:05:46 Oh, how the times have changed. And even just the last few days and weeks, right? Again, you may be listening to this in late 2026 or early 2027. I don't know. But if you're listening to it in February, right, today, February 27th, I mean, the last 48 hours alone, we've seen a ton of movement that I think signal. where this is headed, right? We got perplexity computer, co-pilot scheduled tasks from Microsoft. We got remote control and scheduled tasks from Anthropic. So, you know, three of the big five players

Starting point is 00:06:22 there in Perplexity, Microsoft, and Anthropic just released pretty big updates that signaled toward this more scheduled autonomous desktop computer worker. All right. So here's the five phases. All right. So phase one, online chatbots, right? They answer your questions in a browser tab. Phase two, business chat. This is where, you know, answers started to come with your company's data and using apps. Phase three, we have the agentic era, right? So this is both agentic models and multi-step execution toward an outcome, right? So more outcome based with multiple steps. Phase four, this is your AI coworkers, right? Delegate a goal and get finished work.

Starting point is 00:07:11 And then phase five, desktop AI, agents that work with your local files, right? And these are kind of in order. But as you'll see, as we talk about each phase a little bit more, technically there's some overlap, right? We're still obviously getting updates to phase two and phase five at the time. Right. It doesn't mean phase two is over just because phase five has started. Right.

Starting point is 00:07:35 That's not where it is. It's more of kind of the official. of when things started. And I think, you know, for the most part, I'd say phase one is probably phased out. Although, unfortunately, I still think people use chat GPT just as a online chatbot to get answers without, you know, using any of the agented capabilities without using any of the business

Starting point is 00:07:56 capabilities, without using any of the more coworker type capabilities. So I think for the most part, people have kind of face out of that era, but not completely. And then there's the feature or the layer on top of these five phases that I think might be even more important in really changing how work gets done. And that's scheduling. Right. So I just mentioned that in the last 48 hours, we've seen literally three big updates just in this space. But this does live across all phases.

Starting point is 00:08:33 So it's not its own phase necessarily. book, right? And Google and OpenAI have had this for a pretty long time, right? It's about six to 12 months a little bit longer, but it's rarely talked about until recently, right? If you go back to my original chat GPT tasks show, and it's a huge bummer that Open AI changed how tasks work in in chat GPT. It's actually weird. If you're on the pro plan, you don't even have scheduled tasks anymore, which is one of the things I use most right now, which is just pulse. In scheduled tasks, only really use an agent mode anyways. It's rarely been talked about until recently that's because of all the changes in the last 48 hours with perplexity, Anthropic and Microsoft coming in with

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Starting point is 00:10:08 tasks like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible so you can refine, redirect, or take over at any time. You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly.adopi.com. All right. Well, now you have the answers.

Starting point is 00:10:37 But if you want to dig in a little bit deeper, now's where we're going to do it. So let's talk a little bit about phase one. So that started with chat GPT launching in November of 2022. And it was obviously mega viral, right? I remember at the time, right? So my company, we had been using the GPT technology since it came out in 2020. So a lot of people overlooked that before there was chat GPT, open AI put their product out there, GPT3 in other pieces of software.

Starting point is 00:11:08 So when chat GPT came out, at least for me, and I used it in, November, I'm like, this stinks, right? It's not, wasn't, it was terrible. It was worse than using the other platforms that had been out for two years, obviously, because they had the time to improve their platforms. But regardless, this is what put today's AI in large language models on the map. And it did technically, I think, change the course. And this might sound corny, but it's true. I think it's going to change the course and has changed the course of business history. All right. Then, uh, you had a little bit later, right, about three, four months later, you had Google launching Bard in March and then also Anthropic launching Claude in March, although Claude was not generally available outside

Starting point is 00:11:51 of kind of an enterprise pilot, I believe, until that summer. But at the time, this is just online chatbot era, right? Ask a question. So a couple huge reasons why in this first phase, this wasn't suited for the business world, right? One of the reasons, large language models at the time did not have access to the internet. Okay. And that made them extremely dangerous. And I think, depending on how you look at it, fortunately or unfortunately, it was really this phase one that I think is still kind of setting the tone for how a lot of people

Starting point is 00:12:26 think about AI today. Right. That's because hallucinations were rampant in phase one. Because number one, well, three reasons, I think. Number one, you couldn't upload data. Number two, it couldn't access the internet. And models couldn't read. So unless you were really good at prompt engineering, there's a good chance that if you were trying to use a large language model in 2022 or early 2023 for any business context, it was probably pretty bad.

Starting point is 00:12:52 All right. And that's why in 2022 and 2023, rag was all the rage, right? Retrieve log men and generation because if you wanted trustworthy outputs from AI, you had to build your own rag pipeline because the outputs were absolutely terrible, just riddled with hallucinations because what? Well, the models were not capable. It was at the time, I think, more than a party trick. So no file access, no integrations, no real world actions, right? And the models were pulling on very old data, right? At the time, those first models that came out, right?

Starting point is 00:13:24 Now the people training the models are legit superstars, right? Some of your heads of research are making tens of millions or hundreds of millions of dollars, right? At the time, I don't think that was the case, right? Obviously, they're very smart researchers and seasoned researchers, but, you know, just the emphasis that has been placed on getting good, clean, reliable training data. And just the work that can be done at inference has completely changed. All right. So that was phase one.

Starting point is 00:13:52 Phase two, I'd say probably started in like 2023. And it kind of, I won't say, again, it didn't end in 2025. But I'll give this phase or this era, 2023 to 2025. So this is team AI. This is business change. This is when it was born, right? So team AI that's connected to your company's data. So first, I think technically first was Microsoft co-pilot in late 2023.

Starting point is 00:14:17 And then also you had Chachapit Enterprise in August, 2023. And then you had Gemini for workspace in February 24. And also Anthropic for Teams and Enterprises came out in 2024 as well. But it wasn't just going Team First, right? That was a big first step. So along with that, companies found out, right? Or big AI labs. They're like, okay, this is great to get, you know,

Starting point is 00:14:43 100 million consumers to check out your AI chatbot. But if we want to make this a tool that companies are going to buy, right? Because at the time, I think it was Microsoft that was cleaning house with enterprise AI, right? Because when they came out in 2023, there weren't a lot of other options if you wanted to get 10,000 people to use a product, right? you weren't going to use a consumer chat bot that didn't have data. So this is really the maturation phase. And I think things like chat GPT connectors, cloud connectors, Google apps, right, all these things in 2025 really, I think, helps solidify the space and also cut down on hallucinations.

Starting point is 00:15:25 And this is where AI could finally access your email, docs, and drives all in a dynamic way. but it really couldn't act on it, right? At least in the earlier parts of 2025, that's kind of in the next phase. But this is the beginning of, you know, AI going from fun party trick to, okay, this could work, right? Kind of the experimentation phase of 2023 and 2024 to, I think by 2025, the business world knew, I would say, I was hoping or assuming it would be in 2024. But I don't think it was maybe until early 2020. 25, maybe late 2024, that everyone realized, oh, yeah, the future of work is 100% AI and there's

Starting point is 00:16:07 no way around it. I think you still had fence sitters in 2024 at the enterprise level, which is absolutely nutty to me because now I think those fence sitters are paying for it. But phase two really pushed it. Phase three, I'll say started in 2024, kind of through 2025, although it's still technically going on, right? And it's ever improving. But this is the agentic area. This is where you have AI that plans and executes. Right. I think technically you could say 2023 because Microsoft had co-pilot studio at the very end of 2023, but I'll say 2024 because I think nothing was really, you know, adapted at March until 2024.

Starting point is 00:16:48 But this is when you had things like Open AI launch, launched operator in January 2025, right? That was a big moment, although operator was fairly bad and slow. But it signaled a big shift toward AI that could think and do human work, right? The big thing was being able to access a browser, which is what operator could do. You know, it could, it was an agent that could navigate the web autonomously. Then I think you had this shortly thereafter. You have this push for agentic browsers, right? So different than an agent, it is a browser powered by a reasoning model.

Starting point is 00:17:29 you know, an agentic browser, one of its main features is to agentically browse the web. So I think some tools like chat GPT Atlas, perplexity comments, Google, you know, announced their agent mode, Project Mariner. They had their Gemini in Chrome. That was probably more, you know, late 2025. But the key shift here thing, I think was reasoning models, right? They powered all of this. you know, you don't have

Starting point is 00:17:58 worthwhile AI agents without reasoning models. All right, models that can think, plan, use logic like humans can. All right. And that's really what I think separates,

Starting point is 00:18:15 you know, at least in my opinion, it was the agenic era that I think is ultimately going to be the most impactful. It wasn't chat GBT, right? Because if we never,

Starting point is 00:18:27 kind of had models that could reason or which that would mean we probably would never have AI agents right we would have more human duct tape than agentic output so it wouldn't have been worth it for any businesses to truly invest in AI over the long term if we never entered into the agentic era or reasoning models right so some of the models maybe you've heard of these they're a little older by now but you know oh one preview really kicked it all off in September of 2024. Then you had Gemini 2.0 flash in December 24. And then Claude Sonnet 37, I think was their first reasoning or hybrid model from Anthropic in

Starting point is 00:19:09 February 2025. So a pretty big like eight month period there where we kind of left the quote unquote old versions, you know, the non-thinking transformer models, right, even though they're still transformer models, they just think and reason. Right. But I like, I really say that's like, I really say that's like. like the old school AI versus the new school AI because I think what agentic models can do and their capabilities, the scaffolding, the harnessing that continues to be improved, right?

Starting point is 00:19:38 You can make the argument today. And I've talked with very smart people about this, right? Like the head of Microsoft research that's been working in agents for 20 years, the head of agents at Cloudflare, right? I've had so many conversations with extremely smart people in the space that have eventually agreed that, yeah, if you're using, you know, GPD 52 Pro and you have all your business data connected to it, that's an agent, right? Especially when you can schedule it and it can act autonomously. It's like, yeah, that's an agent, right? Or if you're using, you know, Gemini 3.1

Starting point is 00:20:14 pro and scheduling things and it has access to your data, that's an agent. Right? So, but it really started with the reasoning models. Then we have phase four. This is AI co-co. workers. So where you delegate a goal and it just finishes work on its own, right? And yes, I know and understand that some of these phases start to blend together. I get it. Right. But in my opinion, the big difference between the agenic era, I would say that's more model and browser base, right? And that's kind of the foundation or the stepping stones for today's AI co-workers or agent co-workers. And this is more or less general AI agents that have a virtual computer and can access your data. So, right, you can say that's, you know, chat TPT agent mode, you know, Google Gemini agent mode,

Starting point is 00:21:04 obviously. But I'd say things like Manus, right, huge successful launch for Manus, you know, recently acquired by Meta. Same thing with GenSpark, right? GenSpark, another kind of general purpose agent that can browse the web. Right. It can access all your data. But for the most part, you know, scheduling. A lot of these AI co-workers are more browser based, right? But you can give access to your data and then they can go use the web for the most part. You can, you can log, even though it can be risky, right? But, you know, they have a virtual computer, a sandbox, a terminal, all these things. You know, they can

Starting point is 00:21:48 run code. You know, a lot of them can run different models, you know, use subagents. So this is kind of the version of a virtual AI teammate that works more in the cloud. And then we also, the newest entry here, you know, Perplexity Computer that was just launched, that uses 19 AI models. Yeah. Let me know if we should do a show on Perplexity Computer. I've been thinking about it. All right.

Starting point is 00:22:16 And then that leads us to Phase 5. And this is kind of where we're at now, although yes, we're still in Facebook. with AI coworkers, that's not going anywhere. We're still in the agentic area era. That's not going anywhere. But I think where we are today, right, the era that is maybe most recently started, that is desktop AI agents, right? So this is a little different in a step, both in a technically a more opportunistic direction,

Starting point is 00:22:46 but also in a much more dangerous direction as well, right? It is probably in most cases, and I think most experts would agree, somewhat safer to use a cloud-based agent that maybe can't access your local files, right? Even though they can oftentimes if you grant them access, they can access your Gmail and, you know, your OneDrive, your SharePoint, right, your Notion, right? You can add, you know, all these different connectors and. apps to the kind of virtual AI coworkers. But in phase five, this is agents that are running on your actual computer. So they can do everything that an AI coworker can do, right, a virtual AI agent, but they can control your actual computer.

Starting point is 00:23:41 All right. So I think technically, you could say, oh, this is more 2026 starting, but technically, I think Claude Code kicked this off in February 2025, but it really got popular, I would say, in the fourth quarter of 2025, right? So Cloud Code was essentially a desktop coding program that really what it turned into, I think some of the popular use cases that really exploded this category was actually people using QuadCode, a terminal tool for developers. Well, non-developers started to use it for, well, non-technical work. And I think Anthropic realized that early on and capitalized on it. And that led to

Starting point is 00:24:26 the launch of co-work, Claude Co-Work in January 2026, which I absolutely love. I'm a big Claude co-work fan. I use Claude as well on the desktop version, not in the terminal, not really a terminal by myself. Right. But this is now you have in the desktop version of Claude Code and Claude Co-Work. This is a desktop AI agent that can control your computer and work for hours, right? I'm never one that's intentionally trying to push desktop AI agents to go longer and longer, but I got Codex to work for 10 hours months, right? I've gotten, Claude usually is a little faster, sometimes not as thorough. I personally prefer codex.

Starting point is 00:25:09 I'm going to talk about that here in a minute. But these are now desktop AI agents that have access to literally everything, your computer, your files, your notes, your, your browser, everything. Right. So you can't talk about Claude code and, um, uh, Claude cowork without talking about open AI's codex. All right. And I am crazy bullish on codex.

Starting point is 00:25:35 I freaking love it. If you've been listening since codex was released, I probably have it running eight to 10 hours a day. All right. I'm, I'm really getting my money's worth on. on the on the pro plan there and I know they've had like double usage and I think that might be going away sometimes soon or maybe it went away sometimes soon that's why I'm hitting my limits right so open a i launched clawed their codex desktop app in February and this is more of a multi-agent command

Starting point is 00:26:03 center and the great thing here they've had kind of skills so anthropics popularized skills kind of protocol so they've had skills support automation support so you can schedule things right so If you wanted to, right, you could schedule codecs to, you know, go on a certain website, grab some information, you know, create a Word document on your computer, you know, organize your computer every day, right? So any, any tasks that you could do in your local terminal on your local computer with your files and folders and your browser, codecs can do and it can schedule it, right? So I think this is, and also important to note, Claude Co-Work,

Starting point is 00:26:46 just literally hours ago, added scheduled task support as well. So I think that's something that's kind of like low-key. I don't think people are using, I don't think for the most part, codecs people are using for non-technical work. And that's the majority of what I'm using it for. So that space, the desktop AI agent space that can control your browser, access all your local files, upload, download. I mean, it's huge, right?

Starting point is 00:27:12 And you can't talk about this space, the desktop AI agent, without talking about open claw, right? So open claw technically can run in a virtual environment. So you could say it's a phase four, an AI coworker, but many people are buying OpenClaw their own or its own computer, right? And that's all that happens. This is OpenClawn computer, right? And this is where, you know, it has its own phone number and its own, you know, email, right?

Starting point is 00:27:39 But that's where we're at now, right? This is the journey from an AI. chatbot that hallucinated and was just kind of a fun party trick and no businesses would touch. Now, literally you have companies buying dedicated computers for multiple. I've seen stories of this, right? People buying multiple dedicated computers for every single employee so they can have, you know, desktop AI agents running more and more. So the hidden kind of phase that impacts it all, right?

Starting point is 00:28:14 So there's our five phases, but the hidden one is scheduling. All right. We've seen, like I've already said, you know, Claude Co-Work just added this. Microsoft co-pilot just added this. Codex has always had this since it was announced. But I mean, Open AI released scheduling via task more than more than a year ago. Although, like I said, unfortunately, it's really just in ancient mode now. Google has it, which I don't know why more people aren't using scheduled actions in

Starting point is 00:28:44 Google Gemini, it's amazing. Perplexity and GROC rolled out tasks, you know, about seven, eight months ago. Open AI Pulse, which I'm not a fan of if they made Pulse better. I think it would be great, right? But this is kind of the hidden layer that infiltrates now, you know, phases two through five, right? The ability now to schedule, right, whether it's scheduling a desktop agent, which is crazy, right? That's why I leave my computer on now all the time because, you know, all of a sudden, no, it's 2 a.m. You know, Codex is going to go do a three-hour task for me. Right. So this is,

Starting point is 00:29:20 if you aren't paying attention to scheduling, whether it's in the business chat context, whether it's the remote, you know, AI virtual coworker, or whether it's phase five, you have to pay attention to it. All right. Now, let's just go to, let's wrap it up here. I told you I'm going to give you what's the next. And here's kind of my five facts and strategies for what's next. All right. Um, number one, agents are delivering real artifacts, decks, docs, spreadsheets, everything, better than humans. I think this is probably what, um, one of the most overlooked facts and aspects of large language models. And this is models by default. People don't understand that you can literally, if you know what you're doing, if you give,

Starting point is 00:30:10 uh, you know, Claude or, uh, I'd say right now, Probably Anthropic and Open AI are the leaders in this, at least on the business chatbot space. You can literally go do your research, contextualize and personalized through your business context and create spreadsheets in docs, decks, et cetera. Number two, desktop AI creates a security and governance challenge that most IT teams aren't remotely ready for. So be ready for Agent Drift and Agent Crash. That is going to be a huge trend of 2026 and 2027. All right.

Starting point is 00:30:47 The next piece of advice here, tomorrow's AI winners are going to care less about what actual AI systems they're using and they're going to care more about in spending more time rebuilding how knowledge work works, right? I think, you know, oh, today's best model, right? It becomes a commodity, right? They're all getting similar or the same features. Yes, I still think there's always going to be winners and ones that are slightly better. But if your team is spending more time on deciding, oh, are we going to use Gemini or Open AI?

Starting point is 00:31:18 Oh, are we going to use, you know, Claude or Google, right? At that point, if you're spending more time doing that than rebuilding how knowledge work works, you're behind. All right. Number four, the AI assistant era is already over, right? The AI worker era is here, both virtually and on the desktop. And most companies haven't noticed because I think it's been. then swift, right? A lot of these other rollouts, right, even if you look at the, you know, the business chat context, you can say that took 18 months, right? The AI worker and going

Starting point is 00:31:54 from AI assistant to AI worker has taken 18 days. It is fast. It is here. Most companies haven't noticed. If you're listening to me, you need to pay attention. All right. And then last but not least, scheduled or proactive AI is the sleeper feature that, changes the entire relationship between humans and AI, right? And it's still one of those things that's flying under the radar for now. So if you, your company, your department wants to take advantage, that's where you should be spending your time on right now. All right. I hope this one was helpful. A quick journey and recap of how we got from AI chatbots to now we have autonomous AI coworkers. So if this was helpful, please go to start here series.com. That's going to give you free access to

Starting point is 00:32:42 our Inner Circle community, and it's going to put you right into our Start Here series channel, where you can listen to now all 10 volumes of our Start Here series. So, thank you for tuning in. I hope to see you back tomorrow and every day. For more Everyday AI. Thanks, y'all. Meet Firefly AI Assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio.

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Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 723: From AI Chatbot to Autonomous Coworkers: How Consumer AI Has Changed and What's Next (Start Here Series Vol 10)

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