Alex (2:25)

Let's begin. Just talking about Claude Code. I don't know if you've seen this, but for me recently on X, Claude Code has been a meme. It's almost like those Chuck Norris memes where people have been talking about how Claude Code could basically do anything and it's got these superhuman capabilities. And I was waiting for a post to kind of illustrate what was going on with Claude code that had made people so excited about it. And I think we got one from Ethan Malik, the Wharton professor friend of the show. And he writes the One Useful Thing substack and his post is called Claude Code and what comes Next. And I think he really illustrates just the amount of autonomous work that Claude code has been able to do and the fact that it's not simply a code autocomplete anymore. So let me just begin with the story that he starts with. He says, I opened Claude Code and gave it a command develop a startup idea that will make me $1,000 a month where you do all the work by generating the idea and implementing it. I shouldn't have to do anything except run some program you give me once. It shouldn't require any coding knowledge on my part. And so you make sure everything works well. Malik writes, the AI asked me three multiple choice questions and decided I should be selling sets of 500 prompts for professional users for $39 without any further input. It then worked independently for an hour and 14 minutes, creating hundreds of code files and prompts. And then it gave me a single file to run that created and deployed a working website. Let's just talk about, you know, we're going to go through what the ideas that Malik brings down in terms of why this is an improvement over previous generations and what the implications are here, why people are excited about cloud code. But, but just to start, are you impressed with the output that cloud spit out here?

Ranjan Roy (4:21)

I am this specific output. I'm actually not that impressed. I'm interested. But I still think and, and I'll definitely get into this in terms of like overall what I'm seeing with this kind of world of autonomous agentic. But I think again, like writing 500 prompts that you can package up, maybe even creating a website taking all these steps is actually incredible, but it should be table stakes. And more and more people are realizing every day that it is table stakes, that the technology is already there to do this level of work. And I think, remember what was one of my predictions from 2026. Agentic AI is going to be real. And I think Claude code is a lot of people's first entry into this world of truly agentic AI. And even Molik goes on to write, he was like, the latest AIs are capable of doing work more autonomously while self correcting many of their errors. But then the AIs are being given an agentic harness of tools and approaches they can use to solve problems in many ways. That second part I loved because this is what I've been talking about for six months now. Agentic AI is not like a process flow diagram. It's giving it a set of tools and letting it go figure out what to do and actually go do it. And I think Claude code, the excitement around it is everyone's finally getting a taste of that.

Alex (5:45)

That's right. And so, so the way that Molik frames it is the combination of these two things that the AI can do autonomous work and self correct and then have this agentic harness, which is jargoning to me, but basically be protocol tools.

Ranjan Roy (5:57)

I like it. Agent.

Alex (5:58)

Oh, come on. It is a terrible. No, bad, very bad. What do you like about this? Okay, go ahead.

Ranjan Roy (6:04)

No, no, hold on. I like. Okay, I have been saying like def. A predefined set of tools and data connectors. That doesn't sound exciting. Agentic harness, it's like kind of just, you know, holding it generally in place but still letting it go. I don't really know much about horse riding or how harnesses work in any kind of situation like that, but at least in my mind that's what I'm thinking. I like it.

Alex (6:30)

No, it's not. It's terrible writing. I mean, I really like the concepts here and it's bad. It's jargony. You're too close to it. Ron, John, here's all you have to say. It can do autonomous work and self correct and it can use tools. That's it. See, why do you have to make it more complicated?

Ranjan Roy (6:44)

Harness is shorter. Agentic harness.

Alex (6:48)

He writes agentic. Okay, we're going to move on after this, but we are not accepting the term magentic harness in the show. It's just does not work. Not going to work. Agentic harness of tools and approaches they can use to solve problems in new ways. Why do you have to use the phrase agentic harness? Why can't you just write? They can, they are. The AIs are being given tools and approaches they can use to solve the problem. So, so it's unnecessary.

Ranjan Roy (7:13)

Jargon this is where I think like. And I, I brought this up on, on this podcast like six months ago at RYTR where I work, like, and we're enterprise AI focused. We launched a tool and I'd started testing it in June. It was. And we joked that you were like, you know, now you're at a AI company, you're feeling AGI. But it was the first moment I actually felt like, holy shit. I gave it some direction and now it's going out and doing all this other stuff because. Because it had a predefined set of tools and data connectors one might call a harness. But anyways, feeling that autonomous AGI ish type action. I think that what Claude code has been the breakthrough. I've been seeing this for six months now. This is happening. This is no longer us talking about can I book a flight and have it search and go do it. For me, this is going and doing tasks for people. People are doing already. And Claude code is the first time a lot of people are experiencing with that. And that's why I honestly think this year this is going to break through in a big way. The way coding assistants were 20. The story of 20, 25.

Alex (8:24)

Right. And that's. So it's getting past our, our differences on languages. I think that's why I thought this was important and that's why I think this was worth bringing up here is that I think that the common conception is that, you know, AI for coding is just that, like it's cool code autocomplete or in some cases, you know, you put a vibe code prompt in replit or something and then you get a website. I think what's interesting here is that you can give just the prompt and it will end up, you know, in, in a way that, that Malik has specified without him having to touch the code, it can end up building a website for him include. Which includes a sales funnel, by the way. And, and you know, basically all he has to do is put it, put it live. And the way that it's doing this is the long autonomous tasks of, of coding and then also being able to use the tools. We won't argue anymore about the language. He says the result of these two factors has led to big leaps in the latest AI tools made by the big AI companies. Now listen, if you're at this point in this discussion and you're not a coder or you're not building a website, you might, you might be asking yourself, well okay, this is very specified and what it's in it for me, and this is again, like just to go why we're leading this show. With this, it starts to broaden out and if anything, this might be just the beginning of what's coming for the rest of knowledge work. And I'll just continue to read Molik because he's very good on this. He says, unfortunately for most of us who want to experiment with AI, these new tools are built for programmers. In a lot of ways, this is a shame because these systems are actually broadly useful to knowledge workers of all types. And by seeing what you can do and experimenting with them yourself, I think you can learn a lot about the future of AI. He goes to return to the example of the startup company launched by Cloud code. It was only touching a small part of the capabilities of what the tool is capable of. If I ask it to do user testing of the live site from different Personas and give me report, give me a report, it, it connects, it deploys another tool connecting to a web browser on my computer. It takes control of the browser, goes to the site it created and scrolling through as a human would. He said he asked the cloud code tool for a critical report of the ui and he said it did a better job of nailing potential issues and spotting some sketchy fake reviews on the site. And he says as a next step, I could easily ask it to implement its suggestions, continuing the process with minimal input from me. That this to me is really the interesting part is you can not only have it go create things, you can have it test things and with natural language, then go and optimize. And you know, if you think about, you know, maybe, maybe it's a website, but maybe it's also, and we're gonna get into this, a folder of documents on your computer and you have it go in and start to, you know, give you feedback on it, make data visualizations from it. One example that he gave is his credit card statements that you could just kind of download them onto your desktop browser and obviously do this with caution and then set Claude code loose on it and maybe makes visualizations, spots, anomalies, gives you a report on your finances. And you need that, that more advanced capabilities. You need the ability to code and to call tools to be able to go and do this type of work. It's pretty, pretty crazy to me.

Ranjan Roy (11:56)

I mean, it's real, it's happening. I'm living in the future, Alex. I'm already there and, but, but I can tell you, like, this is where I think the big shift I saw is early 2025, when people talked about agentic AI, again these thinking of like these big heavy processes and how do we automate them in some way and bring an LLMs intelligence to make a decision in one part or maybe create some copy at another part. The big shift was completely rethinking like what agentic AI is and again won't say the word harness, but allowing it to start to take these tools. And I think what he showed there like around this like creating an entire business, launching it at 500 prompts, at 39 bucks a month, are you really going to do that? Maybe, but probably not. Something it's these kind of like smaller multi step processes where I, I am calling by the end of the year all of us are going to start incorporating in our life in a lot of different ways. Go check my credit card statement, find any charge above like $25, come up with a summary like email me. Stuff like that is going to become routine for especially at least any early adopter I think by the end of the year.

Alex (13:17)

And it is interesting. So we've talked, remember like last year we were talking about like is AI going to hit a wall? And there were all these different things about like well, is pre training still continuing to work? And, and I think, you know, there's another bad jargon word which is like the scaffolding, right, which is something we've used. Like what do you build around these tools that, that enable them to sort of cheat their way through the limitations of the, you know, the models topping out or for instance the context window. And context window of course is the amount of text that this model, the model can work on before it sort of runs out of its ability to like keep it in the like sort of memory window, so to speak. Uh, and, and it's just interesting to hear how this stuff works because, because Malik even talks about how like the sort of cloud code cheats its way through like the limits of the context window. He says when CLAUDE code runs out of context, it stops and compacts the conversation so far, taking notes about exactly where it was when it stopped. Then it clears its context window and the fresh version of CLAUDE code reads the notes and reviews the progress to dates. Uh, and then it gives it those notes give Claude everything it needs to keep moving. This is why CLAUDE can run for hours at a time. It carefully notes what it's doing along the way, produces interim work and you know, like pieces of software and reports that it can refer to. I mean this is, this is very interesting the way that these companies Are architecting stuff.

Ranjan Roy (14:40)

Yeah, I mean this is where anyone who is using Claude two years ago, year and a half ago and would hit that dreaded. Like you've run out of credit even as a paying Claude Pro subscriber and have to either wait 12 hours to run a prompt on the leading model. Again, like the architecture side of how people are approaching these kind of agentic workflows is getting solved. I think that's the big thing. And it's not at the model level and models are helping but. And it's. Yeah, it's the, it's not the product. Actually, you know what, instead of product versus model architecture, let's throw that in there as well is another layer that can be optimized or innovated on to actually to really move this stuff forward. So are you team architecture?

Alex (15:29)

I think I am team architecture. I mean this is something you were on stage.

Ranjan Roy (15:33)

Was it Larry or Sergey that you talked about architecture?

Alex (15:37)

Well, Sergey talked about algorithmic improvements. Okay, we put that under architecture. Yeah, yeah, I would call it architecture. And it's starting to show up in other places too. Here's Claude desktop. So this is a relatively new thing that Anthropic has released. You can put cloud on your desktop if you're in the 20amonth bracket of the paying users. And Malik says just give the access, just give the AI access to a folder. Remember that CLAUDE can do anything to the files in that folder. So be careful and make a back if it's, if it's sensitive and make a backup and you can start working with AI. Have IT research and write reports. Give it access to your credit card records so it can put them into a spreadsheet and tell you about anomalies. Ask it to do a data visualization, whatever else you like. All right, Ranjan, so as our, as our resident AI agent expert, I'm going to ask you a question about this. Do we, do we really need to like be running this stuff through COD code or can you just like upload it into the, into the context window of like the Claude chatbot itself? Like what does going through Claude code give you? Is it just more power because it can build things on the fly for you? Tell me a little bit more about why this is important.

Ranjan Roy (16:51)

Yeah, the. It's the ability to again it's multi step. It's not one action. So it's a set of like especially giving that general guidance and action. Thinking it from. Thinking of it from an outcome perspective. It's no longer telling. Claude, here's what you should go do it's saying here's what I want and to get there. Like that's not how a typical chat back and forth works. A chat back and forth is let's iterate together, let's explore, let's try to understand versus I know what I want, go get there for me. So I think and that ability to combine whatever the actual kind of like reasoning side, if it needs to actually create like hard coded Python scripts that are deterministic and are going to be used, it can do that. Like not limiting it to that chat window is the biggest difference here. And again increasingly and again talking about my own company here, like we see at Rider people, the biggest change is the routine side of it. It's these things are no longer going to be one off things you do for fun and kind of try it as an experiment. You start to set routines. So this kind of work is being done on an ongoing basis. So it's not I'm going to go in and upload a document, it's actually happening in the background and like the, the Claude UI gets abstracted away. Like maybe you just get an email or a notification with whatever results. So, so I think it's a big difference.

Alex (18:19)

Give some concrete examples, give some concrete examples of, of like the type of.

Ranjan Roy (18:23)

Routines that I mean like not to get too into the enterprise sales world but like right now at work we have like force, we have Gong, which is like a call recording and data type thing. We have something called. We have all these different systems. I literally have a list of accounts. In the past I would go through every morning. I would either have like a report in each of one or a dashboard. I literally was able to create something where it's like go in, here's a list of accounts. Did anything happen in the last 24 hours? What happened? Summarize it, email me. And like I built that, that's a whole app. There's tons of code in there and API calls and MCP connectors and I can do that stuff now that like so this is where and I think I'm a reasonably technical person but like I mean anyone especially simple, simpler levels of this will be able to start doing.

Alex (19:15)

Okay. And this is, that's a good, good segue to the end of the post here from Malik. He says today's AIs are capable of real sustained work that actually matters and in turn is starting to change how we approach tasks. He says it is starting unsurprisingly with programming. One of the more famous coders in the AI world. Andre Krapathy recently posted. I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are incredibly increasingly spare and between I have a sense that I could be 10x more powerful if I just properly string together what has become available over the last year or so and a failure to claim the boost feels decidedly like a skill issue. Malik concludes, don't let the awkwardness of the current Claude code or its specialization for coding fool you. New. Oh God. New harnesses that make AI work for other knowledge work tasks are coming in the near future and so are the changes they will bring.

Ranjan Roy (20:12)

Oh my God. Sorry. Okay, hold on. 1. I love this quote from Carpathy, so I'm trying to contain myself or regain my composure after seeing harnesses again, but okay Carvathy, I loved this quote. I think it came out over the holidays when I was at home. Caught it on Twitter like started seeing it more and more because like this is how I feel as a fairly technical but still knowledge worker at heart. Like I feel when I'm seeing what I'm able to do. I feel like holy shit, I think I'm falling behind. Or like I don't even know if other people are getting this faster than me that they're going to be way ahead. And so I that feeling was kind of like lingering in me the moment you start to see what's possible. And I think like when I saw him say that, especially about programming from one of the leading world's leading programmers, like it starts to make us feel like this stuff is so interesting right now that even someone like him can actually feel like I better get a handle on this right now.

Alex (21:22)

Right? And look, I. I'll just say this. I'm not completely sold that this is where we're going. I know you feel firmly. You're also like, you know, you're invested, you have a built in bias. You're. Yeah, because it's where, where you work. I'm not. But here's the thing. I've seen enough energy around the increases in capabilities of the type that we spoke about at the beginning of this conversation, the type that Molik listed as he explained what's going on. Uh, and I think that that has been clearly drawn out by Malik in this post that I think it would be foolish to ignore it. The same way that Malik is basically saying like don't be fooled by this being just a coding specific thing. Soon we'll probably have the interfaces that will make this type of work autonomous work things that self correct things that call tools available for, for many, many more different types of knowledge work professions. And that's why I think that this is important to highlight. I mean we are getting, obviously we're getting, you know a year is just a delineation in time but we are getting started here in 2026 after what I think was a lot of movement in this space. Obviously that a lot of money went into it. We've been very critical about the financial picture of some of these companies but I think that shouldn't blind us to the fact and again we're here for like nuance about this. That shouldn't blind us to the fact that this technology is progressing in some very interesting ways. And our mission on the show is also to be able to be like hey, pay attention to this because it's something that we think has the potential to be big. And I think that's the case here.

Ranjan Roy (22:52)

I think so too. And I'm going to make the bet here right now. Every week Alex and I have a collaborative Google Doc that we paste links in and kind of copy and paste text into. I think we are going to not be working in that way and have something more interesting as a process in a few months time. I'm making that call.

Alex (23:14)

I will take the listen, I may have just talked about how I believe in the power of this technology. I will not bet against Google Docs. I won't do it. We're going to be doing the same thing and I will not change my process. That's my bet.

Ranjan Roy (23:30)

Love to paste a link. It's actually the act of pasting the link is the most human thing one can do. I'll agree.

Alex (23:38)

Well also I think it sort of just to not to over index on this Google Doc discussion. But why not? I mean this is the problem too. People have processes, they like their processes and it takes an unbelievably better process and system to be able to get them to switch off. And that's probably the biggest thing that will hold this technology back over time is just the fact that like people like their processes. And if you say here's this brand new agentic way to do your know, show planning or take tasks A, B or C, their, their immediate reaction isn't going to be like oh hooray, let's, let's switch over. Their original reaction is going to be like over my dead body.

Ranjan Roy (24:20)

You, you got, I mean honestly this is the biggest thing the technology is there. Like I, I, I'VE been saying it for a while. The technology is there, it's a change management person, human, ui, whatever problem. But like exactly as you're saying, we have, we have a process. It's a beautiful one. It brings us to this show every week and, and it gets it done. But yeah, people are tied to process. So yeah, I think that's going to be the most interesting part of this year. But like the way I see it already kind of going is the more people hear about there are better ways to do things, the more you, especially early adopters, you're like, I gotta at.

Alex (25:01)

Least try and maybe technology will reinvent the world, or maybe AI will reinvent the world's oldest technology and that is of course email. And maybe it will change processes there. This is from TechCrunch. Gmail debuts a personalized AI inbox AI overviews in search and More Google has unveiled a new AI inbox for Gmail that's designed to provide a personalized overview of your tasks and keep you informed about important updates. Google is also launching AI Overviews in search and and a Grammarly like proofread feature. Additionally, Gmail is bringing to all users several AI features that were previously available only to paid users. The new AI Inbox and this is, I think where most interesting news is coming. The new AI Inbox tab features two sections suggested to dos and topics to catch up on. The first section displays summaries of top priority emails that require an action, such as a reminder and you have a bill due tomorrow or that you need to call your dermatologist to confirm your mailing address so they can ship you your prescription refill. Under the topics to catch up on, you'll see updates such as your Lululemon return has been processed or the end of the year statement now available from Wealthfront. What do you think about this? Is this, is this basically the same, the same personalized inbox that we have from Gmail? I mean Gmail has prior primary and updates. Is this the same thing or do you think the AI layer on top of it is gonna actually change the way we email?

Ranjan Roy (26:24)

So I love this article and I'm glad we just got to it right now because I created a system taught to me actually by my coworker at the time of the Financial Times, Stacey Marie Ishmael. With Gmail flags you can create like customized instead of just the star or not star you can have there's like five different options and like creating a tiered ranking system and I have my system, it's from 2011 I'm still using it in Gmail today I turned off primary inbox and all of that. So I am curious to see whether I start to use this. But on the other hand, like, like email has to change. We all know that email, like what's the value of the actual email? Is there a better way to do it? So I'm glad they're at least trying something here.

Alex (27:13)

Well, isn't this kind of exactly the version of what you were talking about before that has been so useful is that it sort of sorts through.

Ranjan Roy (27:21)

Yeah, yeah, yeah.

Alex (27:22)

I guess the action in your inbox and prioritizes it for you and summarizes it so you don't have to like. Similarly you don't have to go through every system. This one maybe you just don't have to go through every single email.

Ranjan Roy (27:31)

Yeah, no, no. So, so that's why I was laughing because like the fact that I probably will stick to my 14 year old system even though this has just been offered to me to, to give you a little bit of credit from your earlier point there. But yeah, I think like the other interesting part of this to me is it's such a rich opportunity for Google for anyone who has not been using Gemini to kind of introduce AI to them or introduce this kind of more agentic AI because like this is in their inbox. Email should be a very straightforward. It's just, it's mostly text, it's very structured, there's subject lines and like it's something LLMs should be able to do a very good job of handling. There's a lot of context and you imagine if this starts to be the way you get the next. I don't even know how many hundreds of millions of users Gmail has. Is it billions billion plus billion plus suddenly?

Alex (28:29)

I bet it's probably 2 billion. I mean it's absurd.

Ranjan Roy (28:35)

Suddenly all of these people will start to over 2 billion users active worldwide suddenly all of them as an entry point to bring Gemini to all these people and start to make them think here's how to use slightly more agentic AI. Adding more like. Now that we've summarized this for you, do you want to go do something? Actually, given our earlier conversation about Manus and Meta last week as menaces, they're kind of like a Trojan horse into consumer. Maybe this is Google's entry point into consumer. Like true consumer agentic.

Alex (29:15)

Okay, I actually got an interesting email from a reader just to like put a bow on this Manus conversation that I think is just worth reading the Reader says, keep in mind that this is. We were talking again last week about Meta acquired Manus, the AI agent company, and I was like, oh, maybe that's actually going to be the thing that they start to bake into their consumer chatbot. I got a lot of, like, not a lot, but some Reader feedback being like, no, this is an enterprise thing. So let me just read that, then we can take our break. This is a great message here. The reader says, keep in mind or listener. Actually, listener mail. When you do a podcast, keep in mind that Meta's customers are in the business of advertising on its platform, not the users. At the end of the day, it matches businesses with customers. And the more businesses it can pull it into the platform by making business operations reaching customers easier is the better. Zuck has previously said, our goal is to make it so that any business can basically tell us what objective they're trying to achieve, like selling something or getting a new customer, and how much they're willing to pay for each result, and then we do the rest. I imagine agentic workflows will be super important in achieving that vision. Meta is attempting to capture and automate the entire funnel from the product ideation to sale. Okay, that's an interesting alternate perspective that we didn't cover last week that I think makes a lot of sense.

Ranjan Roy (30:34)

Yeah, I think, I think that's reasonable. Again, like, in any of these areas. Yet business model that drives the entire company is going to kind of influence things. I guess, if you think about it like Facebook workplace, remember that? Or does it still exist?

Alex (30:51)

Yes, I think they shut it down.

Ranjan Roy (30:53)

Okay. Like, that actually is a perfect example of there is no reason Facebook and then Meta should not have been able to do something really interesting in that space. It's a very lucrative space. There's no reason, like, they should not have been able to do that, but they didn't. And I think, like, the business model and just how that drives the entire organization is kind of the core of that. But saying that Google did manage to do that, even with an advertising business, and then building the behemoth of Google, Google Cloud and Google Workspace. So. But you can see how. Yeah, like, what's the core business model actually influencing the entire, like, effort?

Alex (31:40)

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Alex (33:36)

And we're back here on Big Technology Podcast Friday edition breaking down the week's news. Big story this week ChatGPT or OpenAI released ChatGPT Health and Chat GPT for her for healthcare. So there's both going to be a consumer side of things where you can speak to the bot for specialized healthcare services and then more of a healthcare version of it that is tailored for business healthcare businesses on on the API side. So uh, let's, let's go one by one. First of all, this is Chachi PT Health. Amazing stat here. Over 230 million people globally ask health and wellness related questions to Chat GPT every week. ChatGPT Health is a new product that builds on this so responses are informed by your health information and context. You can now securely connect medical records and wellness apps like Apple Health Function and My fitness pal. So ChatGPT can help you understand recent test results, prepare for appointments with your doctor, get advice on how to approach your diet and workout routine, or understand the trade offs of different insurance options based on your healthcare patterns. Uh, it operates health operates as a separate space with enhanced privacy to protect sensitive data. Conversations in health are not used to train our foundation models. If you start a health related conversation in ChatGPT we suggest, we'll suggest moving to health for these additional protections. I don't know about you Ranjan, but I have been using ChatGPT already as a health sort of consultant, so to speak. I think these are, these are great. I'd love I have the Garmin watch. I'd love to be able to connect connect it. I basically just been taking screenshots of the watch and the app and just dropping it into ChatGPT and speaking about it. I think this is a huge potential area for growth of growth for OpenAI kind of kind of welcoming this what do you think about this? This new offering?

Ranjan Roy (35:28)

No, no. I I so at a consumer level or a customer level, I love it. I it's funny, I actually use Claude for all my health related questions. I don't know why. I just kind of feel more comfortable with Claude than chatgpt on that but like I it's the interesting part to me is again everyone is doing this. I like that they're actually kind of trying to make it more productized and make it like simpler to understand kind of presenting it as this separate offering. I was already when I saw this thinking more like what does this do to an aura ring which I'm paying 7 bucks $6 a month for a subscription and they're supposed to be analyzing my data for me whereas in realize I do reality I do kind of the same thing where I just screenshot stuff from Aura into Chat or into Claude and ask questions like all these like Apple Health. Yes, track it for me. But that app has never been that good. My fitness pal. All these start to get in a little bit of trouble with this.

Alex (36:31)

I think ChatGPT has 800 million users weekly users fully one fourth of them are using ChatGPT for health questions already. Yeah, which that's a big number.

Ranjan Roy (36:47)

But what do you think this does like at the doctor visit level because like same thing went to the doctor they for yearly physical they like tell me some stuff but then I just took all the results and just went straight to Claude and uploaded and had a much, much won't mention my doctor's name here. They're fine. Like they're, they're fine. But I got a much, much deeper, better in learning and felt more comfortable and just everything with AI chat.

Alex (37:20)

Yeah, I mean, I think this kind of shows how trusting we've become of these bots. Like, I dropped my blood labs right into chat.

Ranjan Roy (37:26)

I did the aura blood labs and yeah, first place.

Alex (37:29)

Yeah, it was amazing. It, it, you know, the doctor gives you like an email and through like the portal, it says everything looks good, watch cholesterol or something like that. This goes, you know, data point by data point, explaining what each one of them are and sort of, you know, taking into account your age, your health status. It already knows when you work out, if you talk to it about that and gives you like this full picture of your health, maybe it will suggest other tests to order. So here's kind of how I think this goes. It's just like we had this like episode about AI and law a little while ago that like AI can, can. If you're a lawyer, AI can, you know, take in all your documents and sometimes get you to an answer. Sometimes it's right and sometimes it's wrong. But it definitely enables you to do more than if you were to co buy this stuff, you know, minute by minute as a, as a human user. Right. Or a human person trying to get through these, this data. I think the same thing's going to happen in health that like ChatGPT will often like, diagnose you or give you things to consider, and it does a much better job than WebMD. I mean, my favorite example about WebMD is like, I once had a scratchy throat and WebMD is like, all right, some possibilities here, maybe Ebola. And I was like, God damn. I, I don't think ChatGPT does that. So I think what, what it's going to do is it will give you some better medical advice. Sometimes it will diagnose you. I think the key then is to bring that information to a human doctor. Right. And I think that's what's going to happen is that like, doctors will see people coming in with their chat GPT logs and they'll sort of start to consult with the human and the bot about what's happened. And obviously that human expertise is pretty invaluable. But I, I'm certain we're going to see much more people in the clinic coming in and being like, hey, you know, please tell me a little bit more about this possibility that ChatGPT suggested. Does that sound right?

Ranjan Roy (39:23)

Actually, hold on. I like that. I think, I agree. I think the big behavioral change in 2026 is going to be people going into the doctor and pulling out ChatGPT. Whereas like certainly a year ago I can't picture people actually doing that with confidence. Maybe they were. But like I mean I was to the side talking to Claude while leaving the doctor going in, but I wasn't looking him in the eye and being like well Claude told me this.

Alex (39:53)

Right.

Ranjan Roy (39:53)

But I think you're right people. And honestly it should maybe any doctor listeners can like send us any negative feedback on this, but I would think it would make their life a little easier too because it would start to at least kind of rather than very, very loose personal ways of trying to explain symptoms and other things. There's already at least one layer of work that's been done that the doctor would have had to do anyways. So for them to actually try to like think of through things in a more reasonable manner. So it seems good.

Alex (40:32)

Well, you know how there's these memes that like the students are writing their homework with ChatGPT and then teachers are grading the homework with ChatGPT. Yeah, maybe that's going to happen with Medicare, Medicare with health care because you're going to have patients that are going to be doing this on their end and then they're going to bring it to the doctor. And now OpenAI is also releasing OpenAI for health care. So they are going to have both, you know, a chat side of things and API side of things and they are going to have like specific models built for healthcare workflows that will diagnose here's this is from their blog post. They'll have high quality responses for clinical research and operational work. Powered by GPT5 they'll have institution institutional policy and care pathway alignment. So they'll integrate with enterprise tools like SharePoint and other systems so responsys can incorporate and institutions approved policies, pathway documents and operational guidance to support consistent execution across teams and reusable templates to automate workflows such as share templates for discharge summaries, patient instructions, clinical headers and prior authorization support. So they're really going to end up being deep in the clinic. I don't know, I, I, I mean obviously like the hallucinations can be a problem and there's a lot of, you know, there is a lot of room to go here to make it make it as good as it can get but I personally think that medical field is something that needed this technology deeply. I've said on the show before, I'll say it again. My father's a doctor and he's spent like half his life just doing paperwork. And if you could get a tool that like records, take notes, takes those notes and allows people to like either focus on the patient or, or even see more patients or, or give them the bright prompts to negotiate their health records when they're using ChatGPT, it can't be much worse than the situation is today. And I'm very, very optimistic about this. And from a business standpoint, it could be a very big business line for OpenAI.

Ranjan Roy (42:31)

No, I, I definitely agree consumer level overall for health care. One thing I will say though is on the topic that's recurring about OpenAI and Focus, still don't quite understand because remember we had enterprise is the focus of 2026 scientific discovery, ChatGPT subscription growth now ChatGPT Health, which I guess kind of ladders up into subscription growth. But like it's still a reminder to me that they're trying to do absolutely everything. Maybe they will, they have some good products, but it's still that more clear focus still isn't there for me.

Alex (43:12)

Yeah, but I don't know, I think that this, I mean obviously you actually like when you read this, you see how much work they actually did on it.

Ranjan Roy (43:18)

That's what I mean though. No, no, that's, that's what I mean. This isn't just let's create another tab and call it health. Like they're having different connectors and EMRs and like there's definite work that went into it, which is work that did not go into other parts of the business that they're talking about and AI, cloud and personal devices and all the above.

Alex (43:39)

Yeah, that's true. I mean, I just think that like again, if you're like, it's a general purpose technology, if you're selling investors on a tam, you need, you need.

Ranjan Roy (43:47)

No, no, I get it, I get it. I'm just saying.

Alex (43:51)

All right, yeah, I hear you.

Ranjan Roy (43:54)

If you were to create a poly market contract on whether. Actually I'm sure there is 1. Whether OpenAI is IPOing this year. Which side are you taking?

Alex (44:06)

I'm taking. No, definitely not.

Ranjan Roy (44:10)

No. What about if it's 2% chance to pay out 50 times to one that they are. Do you like those odds?

Alex (44:18)

That's a good, I mean that's good odds, but doesn't change my, my overall feeling on the matter, which is that. No. Okay, but Speaking of prediction markets. Well, wait, sorry, what are you.

Ranjan Roy (44:29)

What? That was. That was my segue. That was my segue.

Alex (44:32)

Okay. Speaking of prediction markets, we talked about prediction markets last week. Some crazy shit has happened with prediction markets this week that we cannot overlook. So first of all, the Maduro capture was on these prediction markets and somebody who, it seems like they had under knowledge, they invested $30,000 on Friday in Maduro's exit. After Maduro went into custody Saturday morning, the Same investor made $436,000 and you know, some change after that. Obviously this person probably had knowledge of Maduro, of the Maduro operation. Here's my question. So, so here's my question to you. So clearly insider trading is going to be a thing on prediction markets. Is that fine? Because the argument here has been like, yes, there's going to be insider trading, but ultimately one of the functions of prediction markets is you want them to be able to accurately predict something. And if somebody does have insider knowledge of what's going to happen, then prediction markets become like an unbelievable tool to see the future.

Ranjan Roy (45:33)

I saw that thesis. I forget from who. This is killing me. I mean, a couple of weeks ago I talked about how I actually do love the concept of prediction markets. I don't love how polymarket and Kalshi and stuff are really rolling it out. But this week was kind of my just hanging my head and camp, just being in disbelief about the kind of stuff that's happening. The thing about that idea is like the whole point of financial markets or any kind of market is giving everyone the kind of at least belief, some belief that there is a fair opportunity to try to make money in it. Like, and if you're, if you're. And yes, I understand, like there's a lot of people, especially outside of traditional financial markets that are like everything's rigged anyways and there's lots of problems in market structure, kind of biasing towards bigger players. Yes, all of the above. But like, I mean the idea that someone in this situation knows that this is going to happen, Maduro can make that kind of money, I don't think is good for anyone. But I also don't think it's good for prediction markets because if you're always like, I am playing at a disadvantage and insiders will be able to, you know, get ahead of this, it kind of kills the whole point of the market. So I think like on one hand, yeah, or I'm curious, I don't know. How are you feeling about that?

Alex (46:59)

I mean, as someone who's Interested in whether prediction markets can predict things. Yes, that's good. But also going back to our discussion last week of the reason why these things have become so big is because the only place that people are, you know, feel like they have any agency is the casino. They don't. And they will, they will end up, they are playing against. There's no way you can have a prediction market without insider information. It's even harder to keep that free of insider trading than it is the stock market. And there are fewer regulations, by the way.

Ranjan Roy (47:28)

Similar.

Alex (47:29)

Yeah, exactly. But there's one thing that's really annoyed me this week, which has been this story about Caroline Levitt, the White House press secretary. You know, she left just before the 65 minute mark of her.

Ranjan Roy (47:42)

Where we explain. Explain the actual.

Alex (47:44)

Or there, there was a, some sort of like on the prediction markets, you know, a prediction of how long her press briefing would last. And the over under was 65 minutes and she like, you know, wrapped up. There was so the, so there was a 98% chance that it was going to run past 65 minutes. And then she left with 30 seconds to spare. So 30 seconds before that 65 minute mark and everyone's like, oh, Levitt's got money on the prediction market knowing that she would go 64, 30. I mean, obviously there's a chance. But these, these press conferences, they wrap abruptly anyway. I don't think she was running away to make it before. See, the buzzer just doesn't see.

Ranjan Roy (48:30)

I'm gonna say like, at first I'm like, this is ridiculous. But I watched the clip a few times and there's a bit of a smile and there's a bit of like, just like very quickly running off stage. And again, remember, like, I mean, the Trumps are on the Polymark and Kalshee like their advisor, like, and not even saying there's any kind of like connection there. It's more. Prediction markets are the same way in the Situation Room or whatever at Mar a Lago when they're invading Venezuela or getting Maduro, they have X up on the screens and searches for like prediction markets have to be part of the conversation within like the Pew staffers at the White House. And whether it's just for fun, and it could be just kind of stupid fun in this case. But to me, the more interesting part of this is going back to our earlier the question around this. What happens when people can actually drive outcomes based on bets? It's one thing to say I have insider information and I'm going to use that to make a bet it's another two. I'm actually going to change the end outcome because I have money on it. Same as like throwing, throwing a game, throwing a match or in sports, like yeah. Actually creating a specific outcome. And to me like the crazy thing to start thinking about is, I mean this is where it just got so dystopian. Like something like this, let's say you're as. It's funny you're doing the prediction mark cutting the press conference short. And again it's just so ridiculous that we have contracts on this. But I guess that's fine. Like the more imagine if we start making big decisions people do to make money on prediction markets and letting that actually drive the decision itself. That's terrifying. Like.

Alex (50:20)

Yep. I mean, I don't know. I'm, I'm still not fully, fully bought into. I mean yes, you have to consider the possibility, but I'm not. But I mean these press conferences, I.

Ranjan Roy (50:32)

Don'T, I don't, I think the time.

Alex (50:34)

And in such speculation, I'm surprised it got that much, you know, pickup. But you're, but the, the broader point that you're making, I'm on board with the principles can drive the outcomes. And if you're doing and as these prediction markets rise, you're going to see that happen.

Ranjan Roy (50:49)

I mean imagine the world where we capture Maduro because there's so much money on the prediction market. Or like, like if these are actually maturing and growing and becoming more integrated, more people have money in them, we're going to start to see some really weird, troubling outcomes, I think. But I still love prediction markets in theory.

Alex (51:11)

Still love them in theory. I don't know if they're really working in practice. Okay, before we leave, I want to talk about the end of busy work. Here's this Wall Street Journal article. The downside to using AI for all those boring tasks at work. Workdays without busy work are closer to reality than ever, thanks to artificial intelligence. AI tools that can sort and summarize emails, take meeting notes and file expense reports promise to free us to concentrate on the important stuff. That sounds great. The catch is our brains are incapable of thinking big thoughts nonstop and we risk forfeiting the epiphanies that sometimes spring to mind while doing easy, repetitive job functions. AFLAC Chief executive Dan Amos dots his calendar with low intensity tasks that could be delegated to an assistant or a bot. These practices are partly about old fashioned habits and personal touches. They're also about taking mental breaks or leaving space for creative sparks to fly. It's the same principle as thinking in the shower, putting your brain on autopilot until it goes aha. There's also a CEO from a company called Conventional. His name is Roger Kirkness. He's become to the value of slack time around the middle of the year. That's when he noticed meaningful productive gains from AI about 20%. Then he noticed meaningful productive gains from AI about 20% overall. But he observed that. He observed that teammates are often mentally exhausted and unproductive by Friday. Ranjan, are you going to stand up together with these CEOs in defense of busy work? Or. Or is this just like the. The last bastion of stupidity in the office, where people say you actually need to do, you know, things like file expense reports to think creatively?

Ranjan Roy (52:49)

I am not going to defend this. I think going back to the beginning of this episode, maybe there is something beautiful about taking a link and pasting it into a Google Doc, and maybe we're never going to give that one up. And there's just something cathartic and like, just reminds you of what's important in this world. But expense reports, come on. Like, what are the most kind of, like, mentally drudgery, mental drudgery type of work you have to do and. Yeah, that. That. I don't think so. I do think the handwritten notes to employees who receive bonuses or retire. It's interesting. Like, there's something about handwriting that's still meaningful to me, but I think this idea of busy work is just kind of like, I just want to be an old executive guy and just save ridiculous things and have them kind of like land as. As wisdom one day. That's my goal in life.

Alex (53:55)

I mean, the call, right? Like, you get it. Hey, it's. It's Callan Borchers from the Wall Street Journal. Oh, hey, Callum. How are you? This is Mr. Amos. I'm the CEO of Aflac. Yeah. What do you think about busywork? Oh, I love it. Love doing expense reports. It's like thinking in the shower.

Ranjan Roy (54:16)

And one. And then hold on. And then he went on to Incubator. His favorite idea, Incubator is the steam room. After a workout, often steps out of the fog with a clear thought and dashes off an email about it. I actually. Steam room.

Alex (54:30)

I'm with that. Steam room is not bad.

Ranjan Roy (54:32)

But he's not doing busy work. That's not busy work.

Alex (54:35)

Am I. Am I being too optimistic and thinking we can end busy work and make.

Ranjan Roy (54:42)

Room for the steam room? That's what get Rid of the busy work so you can be in the steam room and you can think, this is, this is a travesty of journalism.

Alex (54:53)

For this. I, I. There's only one thing that can save us for this. And you know where I'm going. We need the agentic harness.

Ranjan Roy (55:01)

We need it, yeah. Just to get that agentic harness in place. More time in the steam room.

Alex (55:07)

Get in. Get yourself into that agentic harness, and away you go. Steam away. Think big. Believe in your company once again.

Ranjan Roy (55:14)

Wait, hold on, hold on. Just to end the piece. Did go on to say, like, he makes 20 million a year, but he declined to pay a few extra bucks for an ad free version of a streaming service service because commercials offer a moment to think about what he just watched.

Alex (55:30)

I think that's a fireable offense. I mean, that's, that just shows some very poor decision making, if you ask me.

Ranjan Roy (55:35)

I love this guy. Actually, you know, do you think he was just trolling here? He was like, I'm just gonna say some ridiculous stuff and let's see if they go with it, because, come on, he's not watching commercials. I'm sorry. You're making 20 million a year. You are not. You can hit pause. You know how to hit the pause button.

Alex (55:54)

They printed it, so I'd love to have them on. If you're. If you're Aflac CEO Dan Amos and you listen to the podcast, come on and speak with us about busy work. I'd love to have this conversation and take the other side of it and, And. No, for God's sakes, man, just skip the commercials.

Ranjan Roy (56:12)

Just.

Alex (56:13)

Not ours. Not ours.

Ranjan Roy (56:14)

Not ours.

Alex (56:15)

Not. Not our stars, but others do. Okay, all right, let's. Let's call it here. Ranjan. It's been good. We've done it. We've done our. We've done our work this week for sure.

Ranjan Roy (56:25)

I'm gonna go file some expenses right now.

Alex (56:27)

I'm gonna go into.

Ranjan Roy (56:27)

Just to think. Just to think clearly.

Alex (56:31)

All right, everybody. Thank you, Ranjan. Thanks, everybody, for listening. We'll have Mistral CEO Arthur Mench on the show to talk about whether AI is a managed service at the end of the day. That's going to come. Come up on Wednesday, and then Ranjan and I will be back next week. Thanks again for listening and we'll see you next time on Big Technology Podcast.

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