Podcasts about can chatgpt

There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all — if you can get the agentic interface right.A key trend we have been tracking over at AINews is the absolute explosion in Codex usage this year, with MAU now up >10x from Jan 2026. Less than two weeks after their July 9th launch, OpenAI said ChatGPT Work and Codex had reached 10M users combined (as we cover in the pod, Codex now powers ChatGPT Work, so all ChatGPT Work users are now users of the Codex harness, even if they aren't traditional engineers) — showing the early innings of what happens when you graduate from coding agents to knowledge work agents:We've been calling out how coding agents are “breaking containment” to do everything else this year to power every other part of knowledge work - and it started with the org chart, with a major reorg last month that amounted to two of Codex's most prominent leaders, Greg and Tibo, taking responsibility over product and ChatGPT specifically, completing a “Superapp” consolidation cycle first discussed in March.With these updates Codex is no longer just a coding tool. In June, OpenAI said knowledge workers already accounting for roughly 20% of Codex's user base and growing more than 3x as quickly as developers. A product dedicated for knowledge workers was being pulled out of the Codex team.However, knowledge work has a different set of problems and environments than coding. For decades, knowledge work has been scattered across different primitives like documents for writing, spreadsheets for analysis, slide decks for communication, and specialized applications for everything else. ChatGPT Work now enables users to work across every primitive with agents. Instead of opening an application and manually operating its features, the user can describe an outcome and collaborates with an agent that can assemble the tools, context, and artifact needed to reach it.From building no-code products at Airtable to leading Productivity Engineering at OpenAI, Akshay Nathan has spent much of his career trying to make the power of software accessible to people who do not write code. In this episode, Akshay joins swyx and Vibhu to unpack the launch of ChatGPT Work, why Codex unexpectedly took off among non-developers inside OpenAI, and the company's broader plan to bring useful agents from software engineers to knowledge workers and eventually everyone.We go deep on the shared agent harness behind Codex and ChatGPT Work, why OpenAI brought the experiences together without making them identical, and how persistent computers, artifacts, Sites, plugins, memory, and sub-agents are changing what people can delegate to AI. Akshay explains why some teams are replacing decks and spreadsheets with interactive websites, how agents can gather context across code, Slack, documents, and local files, and what OpenAI learned from personal-agent products like OpenClaw.Side note: also don't miss Abhihek's sandbox track keynote at AIE, which now powers a lot of the sandboxing for ChatGPT Work… and yes was also broken by an unreleased OpenAI model in the recent HuggingFace incident.Akshay also reflects on how AI is transforming product development itself: why more people will become generalists with a specialty, why ideas and taste become the bottlenecks when almost anyone can build, why LLMs still struggle to generate genuinely grounded new ideas, and why teams must distinguish increased motion from actual progress.We discuss:* Why Codex unexpectedly took off among non-developers inside OpenAI* Why employees felt like using Codex gave them a new superpower* The product insight that led OpenAI to build ChatGPT Work* Why Codex and ChatGPT Work share the same underlying agent harness* How their UX, Git visibility, artifacts, and sandboxing defaults differ* Why OpenAI merged its agent experiences instead of building separate products* How AI is blurring the boundaries between engineering, design, strategy, and operations* Why OpenAI wants the default model configuration to work for most users* When power users should use deeper reasoning, Ultra, or multi-agent modes* Artifacts, agentic spreadsheets, and creating high-fidelity work products* Why interactive Sites may replace decks and spreadsheets* The challenge of designing a simple interface for an agent that can build almost anything* Why users should retry tasks that models could not handle three or six months ago* How AI can gather context for performance reviews without replacing human judgment* The OpenAI automation that turns internal Slack and document activity into memes* What reaching ten million ChatGPT Work and Codex users means for the product* How OpenClaw inspired persistent environments, scheduled tasks, and personal agents* Using ChatGPT for financial planning, budgeting, workouts, meals, and household management* The design tradeoffs behind sub-agents and how much of their work users should see* ChatGPT memory, Chronicle, and long-term context* Why AI may make more people generalists with deep specialties* Why ideas and taste become more important when almost anyone can build* Why LLMs still struggle with the instruction “bring me new ideas”* Measuring productivity through quality at-bats instead of commits, tokens, or pull requests* The critical difference between AI-generated motion and meaningful progressAkshay Nathan* LinkedIn: https://www.linkedin.com/in/akshaynathan/* X: https://x.com/akshaynathan_Timestamps00:00:00 Introduction and Bringing the Power of Code to Everyone00:01:33 Joining OpenAI and Preserving a Startup Culture00:02:40 What OpenAI Learned from Enterprise AI Adoption00:05:28 Why OpenAI Built ChatGPT Work00:07:17 Codex vs. ChatGPT Work and the Shared Agent Harness00:12:07 Why OpenAI Merged Its Agent Experiences00:16:24 Models, Reasoning Levels, and Choosing the Right Default00:20:26 Artifacts, Agentic Spreadsheets, and Model–Product Collaboration00:24:22 Why Sites Could Replace Decks and Spreadsheets00:30:08 Designing an Agent That Can Build Almost Anything00:34:28 From Developer Agents to Knowledge Work—and Everyone00:36:07 Power-User Advice and AI-Assisted Performance Reviews00:40:41 OpenAI's Internal AI Memes and the Ten-Million-User Launch00:44:39 OpenClaw, Personal Agents, and ChatGPT as an Operating System00:50:24 Sub-Agents, Ultra Mode, and How Much Control Users Need00:54:39 ChatGPT Memory, Personalization, and Chronicle01:00:19 How AI Is Reshaping Product Development and Tech Roles01:03:15 Ideas, Taste, and Why LLMs Struggle to Generate New Ideas01:04:42 Measuring Productivity, Quality At-Bats, and Motion vs. ProgressTranscriptIntroduction: Akshay Nathan, ChatGPT Work, and the No-Code ArcSwyx [00:00:00]: We're here in the studio with Akshay from OpenAI. Welcome.Akshay Nathan [00:00:07]: Thank you.Swyx [00:00:08]: And with our trusty co-host, Vibhu. So you recently launched ChatGPT Work. You lead Core Product Engineering. It's been a long journey, into all this. I find it very interesting that you started with no code or low code, with Walrus and Airtable. And to some extent, ChatGPT Work is like the super app of super apps of, well, here is the ultimate no code. You just write a prompt.Akshay Nathan [00:00:32]: Yeah. It's funny how things come, full circle. I think for a long time in my career, I started my career working consumer fintech, but then after that, like, there's this hypothesis that, the things that we were able to do with code, like, as engineers, like, if we could bring that to many more people in a more, accessible way, then that would be truly magical. We were working on a startup. It's funny, like, before LLMs, before vision LLMs, on how to do automated testing with AI. It was just kinda jank, back then, but doing what we can, and then worked at Airtable for a while on the same thesis that, like, if we can bring a database or the primitives behind a database to people, that'd be really useful to them. But once LLMs came onto the scene, it became clear that, this was the missing piece, like, the missing technology required to, like, bring the magic of code to everyone without them having to know what's going on underneath the hood. And so, like, I think this launch and a lot of the stuff that we've been up to is, like, the manifestation of that.From Walrus and Airtable to OpenAIVibhu [00:01:33]: How was stuff when you joined? So you joined OpenAI 2023. Now we've got, so much more stuff, so ChatGPT, Codex app, ChatGPT Work. Have things changed?Joining OpenAI and What Hasn't ChangedAkshay Nathan [00:01:44]: I think the more interesting thing is how things haven't changed. Like, one, I joined I remember when I joined, it was, like, five hundred people. One thing I was worried about was, like, I was looking for something, more early stage and, like, was it gonna feel startup enough? And I joined, and I was like, “This feels even more startup-y than I could ever imagine.” And, like, that really hasn't changed even till now. I think the, like, level of, like, bottoms-up ambition and, like, the ability of anyone to, like, do anything or have an idea and ship it is really cool. But on the, like, mission side, I think what was really compelling to me is this mission of, bringing frontier intelligence to everyone. Like, building AGI and then bringing it to everyone. And, I think acknowledging back then that, like, that vision is gonna, not be a linear progression. Like, we're probably gonna, like, try different products and have different things that succeed and don't. But the vision has stayed the same, and the mission has stayed the same, and we're starting to see the pieces, fall together, and that's really cool.Enterprise Lessons: No One-Size-Fits-All AISwyx [00:02:40]: You worked on Enterprise. What A lot of people never touch ChatGPT Enterprise. What is something that you learned from there that you're bringing into your work now?Akshay Nathan [00:02:52]: I think how there's no one-size-fits-all solution in Enterprise. I remember in the early days of ChatGPT Enterprise, like, when we talked to customers and, like, everyone. That was, like, when I think it was a year after ChatGPT was released, and everyone was so excited to bring, AI into their enterprise. And, there were all these teams being stood up. It was, like, the AI deployment team with, like, these enormous budgets. And if you asked anyone, like, what were they excited about? Like, what were they excited about solving? Like, at first, you'd get, like, kinda like the baseline answers of, like, “Yeah, we have all this context and data and all this stuff.” But then if you ask them, like, “What was, like, a discrete use case that, like, they want AI to enable in their workplace?” You get such a different, like, variance, like, explosion of, different types of answers. And it's interesting, like, you using, like, these models and these products, you have this box, and you can say anything to it, which is the magic. But it'on the flip side, it also means that, like, you don't know what to do with it. And in Enterprise, I think a big part of that is, like, meeting the users where they are, like, what use case were they trying to solve, and then teaching them how they can use AI to, like, gain leverage there.Swyx [00:03:56]: Do you meaningfully differentiate that from forward-deployed engineering?Akshay Nathan [00:04:01]: I think there is the go-to-market side of it and then there is the product side of it. I think you need someone on the product side. And I think, like, however good we get at FDE motion, like, I think at the end of the day, if we have a user who's, like, looking at their computer or looking at their phone, like, it's our job in the product to, like, be enabling them and showing them where to go. So we're really excited about that.Vibhu [00:04:24]: Do you think there's been changes, over the past three years of adoption? So there have been, step function changes. You have reasoning models and whatnot. Is there still the same problems of Enterprise has black box, don't know what to do with it, or have things changed?Adoption, Agents, and the Next 10x MarketAkshay Nathan [00:04:39]: We're seeing now that, like, there's this huge uptake, right? Everyone is extremely excited about it. It feels like, many people are, millions, hundreds of millions of people are using ChatGPT. They understand, like, how generally to work with AI. But then, like, every time, like, a new capability gets unlocked, so now, like, we're seeing with agents, like, there is probably a contingent of, like, early adopters still who, truly get it, who are like, “ we you can do anything. You just have to make sure the right context is there, it's connected to the right tools, and that you are supervising it, but, like, anything is possible.” But then there's, like, this, like, 10x or 100x bigger market where, like, they don't yet get that, or they don't yet see that. And so I think that's the next stage here. So to answer your question, like, I think the adoption is there and growing fast, but I think the opportunity is, like, far bigger than that. That's where we wanna play, especially with ChatGPT Work.ChatGPT Work, Codex, and the Super App MergeSwyx [00:05:27]: Yeah. well, let's, let's skip ahead to ChatGPT Work. only, like, a month ago or so, announced. what was the decision process that led into it? there was this, overall merging of the super app. Is that what we're officially calling it? you deprecated the browser as well. Just, summarize your last, like, couple months of working on this thing.Akshay Nathan [00:05:50]: Yeah. It feels like forever now, but it's only been a few months. I think maybe the one, impetus that, like- Is most salient is when we release Codex, or even internally had Codex, like, it was really surprising to us, I think we recently put out some stats on this, that there was this, like, real inflection of, like, adoption among non-developers at OpenAI. And, I, through this product development process, like, would go to, like, these UXR sessions to talk to people internally. And the thing that stuck out to me is, like, one, like, you go talk to, like, strategic finance or marketing or whatever, and they're all using Codex for, their use cases. That part's cool, but the thing that really stuck out to me is how proud people were that they were using Codex. Like, how, likeSwyx [00:06:34]: It's like, “I'm not supposed to be using it, but I am.”Akshay Nathan [00:06:36]: It was that. It was, like, that they were, early to this, like, new thing, but it was also this thing of, like, they felt like they had a superpower, right? And, what we recognized then is that, like, the power of Codex, the power of agents, like, we already had this massive distribution base of people who have, come to know and love ChatGPT. Like, how do we show that to them? Like, how do we bring it to them? Which is, like, a hard product problem, and it's, like, a tricky thing, right? There's many ways you can go about it. And so that's what we called the Merge and the Super App over time, and ultimately launched it in ChatGPT Work, is how do we do that? But it came from that initial realization that, like, the power was not only for developers, like, much earlier than probably even we thought. Like, it could be extended to everyone.Swyx [00:07:17]: How do you see the products differently? So, like, who is it for, right? So Codex started out even CLI, then app. Now there's a merge of ChatGPT Codex and ChatGPT Work, so is it the opening for the average user, for enterprise, for work? How do you position it?Akshay Nathan [00:07:36]: I think we want to get it to position it for if you're doing work-related things, for lack of a better word, right?Who ChatGPT Work Is ForAkshay Nathan [00:07:42]: I think productivity is what, like, the pillar that I support. Like, that's the name of the team. And the reason for that, the reason we call it productivity and not, like, enterprise or, like, work or something like that, is because there's also personal productivity, right? And, like, I think ChatGPT Work is I've seen people do things in their personal lives that you wouldn't classify as, like, work technically, but, like, these agents are, super capable for. Like, one recent example that someone posted about, on our Slack is, like, someone had, like, a missed package, like they didn't receive it, and then they got, like, the picture of it, from Amazon or whoever the courier was, and they, like, asked ChatGPT Work to, like, find out where that package is. And, like, the agent, is extremely tenacious and, like, took the image and, like, looked at a bunch of, like, listings around their neighborhood and figured out exactly the apartment complex in which the package was, like, gave them some information. And so, like, I think there's all these things that, like, you, work-related or productivity-related things, I think that's what we want the product to be. You asked about Codex. I think we think Codex is, a durable brand, but we have a principle that, like, the user we don't want a user to get stuck in a tab or an experience where they don't get the power of the product. And so, like, everything that you can do, in the Codex portion of the product on desktop, you can do in ChatGPT Work and vice versa. But we made some opinionated product decisions on, like, how much of the Git state, if you're in a Git repo, do we wanna expose to the end user? Or how much do we wanna make the experience of seeing the agents thinking, like, diff forward so that you get exposed to the diffs out of the box. And then, like, on the safety side, like, how do we wanna think about, like, sandboxing and making sure that we have the right defaults in one state versus the other? So, there's, like, some opinions that go behind that, but we do want We don't want the user to need to choose which experience they're in.Swyx [00:09:26]: That is a good goal for AGI, right? Like, people don't want, like, to hide to choose what version of AGI they want. They just want the AGI to decide for them. can I get an answer or, like It's not super clear to me. Is the Codex harness and the ChatGPT Work harness the same? Is it just UI affordances, or are there prompt level or even deeper differences?Shared Harness, Different UX: Codex vs. WorkAkshay Nathan [00:09:49]: So the harness is the same. The harness is shared. on In both of the products, we made improvements to the harness to make it good for knowledge work, especially as it relates to plug-ins or computer use or artifacts. You get that power regardless of which experience you're in. On the UX side, there's opinionated takes that we have when you're in Codex mode, what the UX should be how the UX should behave, and some stuff around the sandbox like I mentioned, but the underlying harness and capabilities should be the same.Swyx [00:10:16]: I'm just kinda curious. Maybe we can, -- Is there a query that we can run that would look different in the two modes?Akshay Nathan [00:10:23]: Yeah. I tried to create, like ask it to create, like, a retirement calculator spreadsheet or something, in both modes. And then in Codex mode, you might have to be in a repo for this, but you'll see, like, the diffs of, like, the sheet that it's creating and stuff like that, and the file edits. But in Work you won't be able to see that.Swyx [00:10:42]: I think that's, that's super clear. And then also the other thing I wanted to dive into was your, the productivity team. what else is there? first of all, what are the top-level teams other than productivity? Isn't productivity everything?Productivity Teams and Core ChatAkshay Nathan [00:10:55]: SoSwyx [00:10:55]: Science?Akshay Nathan [00:10:55]: We have a team focused on ChatGPT. Like, the core chat experience, for consumer, which is like, not, I think all productivity. Like, there'People are using ChatGPT every day for search to, figure out how to write messages to loved ones, to think about, how to, like, learn a new topic, et cetera. And so there's so much more inside to create images. And there's so much more in chat that, the hundreds of millions of users are using that warrants, like, a very dedicated effort. And there's teams focused on enterprise and infrastructure and API and stuff like that, so.Swyx [00:11:33]: I will bring it up.Retirement Calculator Demo and Git-First UXSwyx [00:11:34]: Yeah. So I have them both running. This is ChatGPT Work. There's a Codex version here. I picked “Five Little Ducks” song, so this will take a while.Akshay Nathan [00:11:43]: Huh.Swyx [00:11:43]: I think we'll just keep it in the background and, as they finish, we'll look into some of the differences.Akshay Nathan [00:11:48]: Yeah. But immediately, I think if you flip back to the Codex version you'll see that,Swyx [00:11:53]: That it assumesAkshay Nathan [00:11:54]: Like theSwyx [00:11:54]: It assumes Git. Yeah. Yeah.Akshay Nathan [00:11:56]: The, like, dynamic island assumes that you're in a Git repo. And you might miss some stuff because some of it is, like, in the actual chain of thought with those changes and how we display that, but yeah.Swyx [00:12:07]: Is there an unintuitive like, is there a thing that you wanted to ship and then you got feedback, and you were like, “No, let's not do it?” Like, what's the thinking behind that?Why Merge the ExperiencesAkshay Nathan [00:12:14]: In, ChatGPT Work?Akshay Nathan [00:12:17]: I think one direction we could have gone with this is, like, keeping the experiences, like, completely separate. So it's like, whySwyx [00:12:22]: Different apps.Akshay Nathan [00:12:23]: Exactly, like different apps or even in the same app, like different, completely different experiences. Like, why merge it all? Like, what is. Codex, people love. Like, why bring these products together? And I think the intuition here is that, like, all of our jobs are, like, changing dramatically with AI. Like, for, like, every few months, like, I feel like I wake up, and I'm, like, doing a completely different thing than I was doing a few months ago. And my hypothesis here is that, or I should say our hypothesis is that, like, part of what we're, we're building, this technology is giving people leverage. Like, the things, maybe it's the more mundane parts of your job or parts that, like, if you were able to automate, you'd be able to share more ideas faster or whatever, like, you're able to do now. And because of that, like, that might blur the lines between someone who's, like, only writing code or creating strategy docs or, planning events or, helping with marketing or doing podcasts or whatever, right? And so, like, these things are gonna get blurred over time. And so, like, trying to draw a hard boundary based on, like, the who you are is gonna be, is gonna be tough. And, like, we should enable users to choose, but we shouldn't box them in. And so a lot of the work that went in here, like, keeping the primitives the same, like for example, plugins are, like, unified across, this product and ChatGPT and the cloud, was because of that. It's this thesis that, like, eventually things are gonna come together and we don't wanna be Like, we wanna be prescriptive about when to be in either experience, but we don't want to box anyone in.Swyx [00:13:45]: I wonder if there's users who are very tuned to the old ChatGPT harness that is effectively now replaced by the Codex harness. I can't imagine what that was, but maybe they're more the more conversational side. Can you compare and contrast the two harnesses? ‘Cause only you've seen it.Akshay Nathan [00:14:02]: Yeah. I think ChatGPT, the existing harness, like, still exists today. Like, it exists in this app,Harness Engineering: ChatGPT vs. CodexSwyx [00:14:08]: The classic, right?Akshay Nathan [00:14:09]: TheVibhu [00:14:09]: You just start a new chat, and you don't go under Work, right?Akshay Nathan [00:14:13]: Yeah. If you startVibhu [00:14:13]: SoAkshay Nathan [00:14:14]: A new chat and go to chat, then you're, you're talking to ChatGPT with the instant model.Vibhu [00:14:16]: Oh, we can technically do another. But on instant.Swyx [00:14:21]: Yeah. So this one's not gonna code or it's gonna be in line. It's on a in line in a sandbox.Akshay Nathan [00:14:26]: It'llVibhu [00:14:27]: Oh, that's coolAkshay Nathan [00:14:27]: We try to push you to go to Work if you're creating a spreadsheet. Yeah, but this isSwyx [00:14:30]: And this is a router decision? Sorry. Is it a router decision?Akshay Nathan [00:14:34]: This is the decision that, the model is making, and then, like it sees that you're able to. or you're trying to do something that would be better served in Work mode. But I think your question was like, what are the advantages of, like, the chat, like ChatGPT chat harness?Swyx [00:14:48]: It's more broadly, like, I wanna, do an oral history of harness engineering. Right? the ChatGPT harness lasted us from, let's call it the ‘01 era, until now, and now it's being replaced by the Codex harness effectively. And they're, they're overlapping somewhat, but I'm curious what changed if there is.Akshay Nathan [00:15:10]: My perspective on this is, like, there's, there's, there's there's like a constant process of, like, divergence, convergence, divergence, convergence. And in chat, like, many of the use cases I was talking about before, like, search or learning, I think we're, we're really optimizing for latency and optimizing for personality and, like, different things that, over time, like the product The reason people love ChatGPT is because we've been optimizing for those things and working on them for so long. Codex, what we learned was that, like, if you give the agent access to this infinitely flexible environment as a computer, it can do really powerful things. And so when we think about, like, okay, well, for knowledge work, like, what is which mode should we choose? It was like it felt more natural to us to bring that to this, like, computer environment and, maybe abstract some of the details of this computer away from users who might not be used to that, but, like, give them that same power. But ultimately, I think that we want the power in all places, right? We wanna meet people where they are. So I'm sure there'll be work down the road in order to get things to be, equivalently capable in all scenarios. But it's just a question of, like, what we've been focusing on the product on historically and what we're focusing on now.Models, Defaults, and the Reasoning SliderVibhu [00:16:24]: I think alongside that, outside of just harness and when to use Codex, ChatGPT, or Work, there's also the new models you've released, right? any guidance there? So people love to min-max what to use, like only use Terra on high reasoning versus, for this, you wanna use Sol here, ignore all theseAkshay Nathan [00:16:44]: There's 32 options.Vibhu [00:16:46]: But, that being said, for people that are expanding, so, productivity trying stuff for work that don't have the breakdown of what all this is what's, what's the advice, right?Akshay Nathan [00:16:59]: Well, I think before the advice, like the first thing is, like, none of this would be possible without these models. Like, the, I think you asked earlier, like, what was, like, the inspiration for work and, like, early on, like I mentioned, like, what we were seeing with Codex, but that was also because the models were getting infinitely more capable. That's happening again. I think it's like another step function jump now. And to answer the question on advice, like we want this default to be the best possible. Like, we wanna be opinionated about the default, and so we've we've chosen a default that we think is gonna be the best for everyone. And, we have for power users options under the hood. We could One could argue that there might be too many right now, and we're, working on simplifying it. But you can extend, the reasoning level, and you can change between the different model classes if you need to, but the default should be the best for most use cases. So my advice to most people would be to stick to that. And then, if you reach a situation in which you think that you could, you wanna try, a different configuration, if you're not seeing either the efficiency on the cost side or the quality on the intelligence side, then you can change the defaults and see if you can get something better. But we think that the default should be good enough.Swyx [00:18:09]: I have, I'm just gonna run something by you since you have way more experience than me. I've recently been doing Sol Lite but with goal, with the idea that the goal augments the reasoning effort, but with more terminations and turns.Swyx [00:18:24]: Is that a good way to think about it as opposed to Sol Ultra or Sol, Extra High?Akshay Nathan [00:18:29]: Yeah. It's hard to say becauseSwyx [00:18:31]: Yeah. It's like an interaction effect.Akshay Nathan [00:18:33]: exactly. It's like there's a preference on, for you as an individual, like how do you like to collaborate with the models? Like how many of those like terminations, as you call them, do you want where, you can steer or make sure that it's doing the right thing?Akshay Nathan [00:18:46]: I think generally people should try whatever works for them. I think that like using Ultra or the like multi-agent setups are best for like when you have like tasks that are either incredibly complicated, like open explorations or very paralyzable. I think even for tasks using goal, I think is best for tasks that you'll be able to make consistent progress in a way that's verifiable over time. But I think for most tasks, they don't fall into either of those buckets. And so like at least when they're starting, and so that's why I think the best first step is like trying it with the default configuration and then seeing like where you wanna go from there.Swyx [00:19:29]: Right. You guys worked on a slider, which is super helpful for reducing the amount of panic.Vibhu [00:19:36]: It's nice on mobile at least. There's a nice slider there.Swyx [00:19:38]: It's nicer.Vibhu [00:19:39]: I haven't tried it.Swyx [00:19:40]: So you have the advanced view there, but if you click advanced view. Yeah.Vibhu [00:19:44]: Ooh, it's just a nice slider. Yeah.Swyx [00:19:46]: Very pretty, very colorful.Akshay Nathan [00:19:48]: Yeah. The idea was here was like reduce it to like one dimension even though there's multiple dimensions, right? Try to project it onto a single dimension for the user. Like, something from that represents like, speed and efficiency on one side and then like quality and thoroughness on the other side.Artifacts, Spreadsheets, and the Work LaunchSwyx [00:20:04]: I am just puzzled that it uses Sol so much, like the lowerVibhu [00:20:07]: NoSwyx [00:20:07]: Grounds I would've usedVibhu [00:20:08]: I think the slider, if I'm not mistaken, isSwyx [00:20:09]: Terra.Vibhu [00:20:10]: Oh, it is.Swyx [00:20:11]: Yeah. See? So they preset Terra to only be the light one. But like I think a lot of people would more people should use Terra. One, because Sol keeps running out of capacity.Vibhu [00:20:22]: I'm the reason. Here's ten minutes of ourSwyx [00:20:24]: There you goVibhu [00:20:25]: Retirement calculator.Swyx [00:20:26]: Oh, that's the Excel thing working for you.Vibhu [00:20:28]: This is,Swyx [00:20:28]: Oh my God. Look at thatVibhu [00:20:28]: This is work, and then Codex is still cooking, so we'll get back into it. I think it'll be interesting to see the thought process, the reasoning, and also, this is eight minutes on work. Codex is still cooking.Swyx [00:20:41]: Yeah. And by the way, so I've, do Gabriel Chua? He's part of the OpenAI Singapore team. He showed me this, and I was like pretty shocked that this looks like Excel. It edits Excel files. You never paid an Excel license, right? Like, but somehow this is like workable and it's agentic Excel.Akshay Nathan [00:21:01]: Yeah. one of the big like pushes that we made for this launch was like artifacts, right?Akshay Nathan [00:21:05]: Like both on the model side, like I think if you compare this with GPT-5.5 and GPT-5.4 before that, you'll see that there's been pretty dramatic improvements in the quality of these artifacts and then also on the product side.Vibhu [00:21:16]: The UX side is also crazy, like hosted sites and whatnot. No longer needing to host your own little webpage, like itSwyx [00:21:23]: Oh, I have a story about that. I can do, a separate thing. I'll need to take the visuals here, but we-we'll, we'll cut to that later. Was there co-training, because you were moving making this big move and you launched GPT-5.6 on the same day as ChatGPT Work? Was there influence between the model training teams and the harness teams, or did they did the launch dates just happen to line up the same day?Akshay Nathan [00:21:46]: I think the we collaborate heavily with the research teams, and I think that's like one of the most magical parts of the job, like the most fun parts of the job. But yeah, just using artifacts as an example. Like, a lot of what you're seeing, like underneath the hood, there's a lot of work that went into making sure that like, we had the right infra to be able to train the models to get better at this. And then on the product side, like had the right experience for users to be able to collaborate with the model on an artifact like this. In fact, like this whole viewer, like the intuition here is that like, it's not necessarily that you wouldn't need an Excel license. This is stage one, right? Like, this is probably not what you meant when you're like making a retirement calculator.Vibhu [00:22:24]: Yeah, you can iterate very easily. Yeah.Akshay Nathan [00:22:24]: You wanna iterate and like when you're seeing it, and if this thing is high fidelity to like what you would see in or what your coworkers would see if you were to send this to Sean, like that I think makes it so easier and makes you trust the product in terms of iteration.Vibhu [00:22:39]: When you say coworkers would see, do you see a multiplayer, multi-team collaboration with artifacts? Any things you guys think about that?Multiplayer Artifacts and CollaborationSwyx [00:22:46]: You can already share it, right?Akshay Nathan [00:22:48]: Yeah. It's inter It's something that, we're actively thinking about. one thing that, we've noticed internally without talking too much about the roadmap is that like there's many times when someone will ping me about something, and I will ask ChatGPT Work the question, and then I'll ping them back the answer.Akshay Nathan [00:23:04]: And then I'll be thinking likeVibhu [00:23:04]: Like the simplest would be, the three of us are just all on one hosted.Akshay Nathan [00:23:07]: Exactly. And I'll think about like was I required in this loop or and then maybe it was, rephrase like what they were asking or pulled from certain context or whatever. But like, when I gave them back the answer, that process was also lossy, right? Like I gave them just like my interpretation of what ChatGPT Work cooked up. But like underneath the hood, there's so much context like in the rollout and stuff that could be interesting.Vibhu [00:23:28]: Yeah, it'sSwyx [00:23:28]: So like the answer was preemptively respond to every inbound request?Akshay Nathan [00:23:33]: No, it was just like literally like this is what I do sometimes as my job.Swyx [00:23:36]: I know you copy-paste and then you're just a message forwarding serviceAkshay Nathan [00:23:39]: Yeah. Yeah, exactlySwyx [00:23:39]: From AI to AI.Vibhu [00:23:40]: But I think it's interesting, right? It helps people understand the capability of what you can ask and delegate that oftentimes people don't realize until they try or someone shows you, and then you're like, “Oh, okay. Okay, I see.”Swyx [00:23:52]: I think it's als there's also like a, light security issue, where like you're the permissions layer. Like yes, I could query everything that you query, and I could get an automated response, but maybe I'm not supposed to see it. And that there's no way I would know because I'm not supposed to know what I don't know.Akshay Nathan [00:24:07]: Especially as like, with ChatGPT Work, we're, we're asking you to connect your plug-ins and, it's pulling from your local files and stuff like that. Like the amount of context that the agent has access to is like- Deeply personal and like that's something I think we need to preserve, so that'll be definitely a challenge.Swyx [00:24:22]: There's Excel, there's PowerPoint, there's Docs, the, grand trio of work. What other formats of work do you think about? like you worked on Airtable. Is there a future where there's like OpenAI Airtable? Like what does that look like if you ever ended up doing it?Akshay Nathan [00:24:41]: It's a really good question. I think,Formats of Work: Sites as Knowledge ArtifactsAkshay Nathan [00:24:43]: one that you didn't bring up was Sites, and I think that wasSwyx [00:24:46]: SitesAkshay Nathan [00:24:46]: A core part of this launch. There's one side of Sites that I think people commonly talk about, especially on Twitter and stuff or X, of like, this like prototyping tool. And like we saw that happen with this launch even. The model slider that you guys were referencing earlier, like that was developed almost fully in a Site. Like, the collaboration between design and engineering and product on that was like on a site where we play with, the affordance and figure out how it feels and all of that. But the other aspect that I think is a little bit less talked about is like Sites as like an artifact for knowledge work. I was talking to someone the other day who's on like our corporate finance team, and like we were mentioning how like now when they have these reports that they're, they're working on as a team month to month, historically those things were in slide decks and in spreadsheets, and now they're just in Sites. And like Sites is the mechanism that they collaborate across the team. And the reason is ‘cause it's like, it's like somewhat higher bandwidth. Like, at these tools like PowerPoint and Excel are like infinitely flexible, but at some point you reach the boundary of like either as a human you may not know how to use some feature or something, or the product itself doesn't support it. But with a site you can do anything. You ask for anything and you can get that. once people see that magic, I think it's been really valuable.Swyx [00:26:02]: Yeah, let me show you my case study. this involves all the hot topics including ChatGPT Work, but also GPT-5.6 token billionaires and token maxing and Sites and auto research. I'm a fan of this game called Strata. It's, it's like a little board game that youSites, Auto Research, and Research DashboardsSwyx [00:26:17]: That you play with, physical blocks, that come on top of it like that. So over the weekend I took like thirty photos and just threw into ChatGPT. one point seven billion tokens later, out comes this site with a fully playable thingAkshay Nathan [00:26:32]: WowSwyx [00:26:32]: With 3D, block placement and everything. Because it requires physical blocks and I needed friends to train on it so they can get better, so I can play against them. But also, I could also, do things like train an AI on it and that's, thatAkshay Nathan [00:26:45]: That's your auto researchSwyx [00:26:46]: That gets into auto research. So, you want to train your own AIs, and then make sure they self-play against, each other. I need to set both AIs. So this is AI versus AI, and they're, they're gonna self-play. the AIs start out bad and then you want to define a loss function and get good. I wasn't gonna supervise all this. I was at, I was down in San Mateo, attending a conference. What I ended up doing was, auto researching and on this and creating benchmarks and that there was just way too many parameters for me to read. So I started asking it for a site, and it's created this lab, panel. Where is there a, is there a shortcut for a site that is created?Akshay Nathan [00:27:28]: You should be able to go in the sidebar to Sites, top of the sidebar. The left sidebar.Swyx [00:27:33]: This one? Oh, left?Akshay Nathan [00:27:35]: Yeah. Just scroll all the way to the top.Swyx [00:27:36]: Oh. Oh, it says Sites. Oh, there you go. Yeah.Akshay Nathan [00:27:39]: Ooh.Swyx [00:27:40]: So it create, it creates the sites. I don't, I don't think this is, it is exactly what I wanted, but let me show you what it popped up, right? Like I think as a research artifact, it is very important to communicate, exactly, what is being done. Outputs this thing which I eventually started publishing. So I moved it off of Sites because I wanted more, database and infrastructure than Sites afforded me. But this is like a research output that you can start to mess with and like try to think about like what hyperparameters are you tuning for training AIs. And like I was trying to make like scaling laws and everything and doing all sorts of like game optimization stuff. And the fact that you can just throw this up as a research artifact, like I no longer need to read ChatGPT output. I read Site output. But then there's also a huge sprawl. Like look at how long this thing is. There's so many numbers. It is pretty overwhelming, so then I have to start pruning it from there. But, it's an interesting transition from Markdown effectively that you're putting out to, you're putting out a whole functional site.Akshay Nathan [00:28:41]: I think Markdown just isn't that optimal for people to read, right? Might as well just write HTML website and I don't know. I think you can do a lot with customizing this, right? You have your skills that explain what you want. Like I noticed they're quite verbose. I don't need a lot of this information.Swyx [00:28:57]: It's very verbose.Akshay Nathan [00:28:58]: So and then the nice thing of having a site side by side is, you just iterate on what you want and what you don't, right?Swyx [00:29:05]: Yeah. I don't know if, any that triggers any stories for you of how it's run internally. Am I doing this right?Akshay Nathan [00:29:11]: Yeah. I think that this is like a workflow that we're seeing like all different types of teams use, where like the canonical artifact that was previously a deck or something is now becoming a site. And like with a site you, because it's just HTML, you can like. It's infinitely flexible. And so, if you want to give more prominence to a certain thing that like in a slide deck would, feel like it was buried, like you can do that. You can have it be like the hero image, right? And so I think that like, people are starting to see that. There's more work to be done to make these things like much more easier, easy to collaborate on. You mentioned that they're very, they're long and verbose, could be broken up. I'm sure that there's still something to do there.Swyx [00:29:53]: They're super long. Yeah.Akshay Nathan [00:29:54]: Yeah. But I think we're starting to see that like there is this aspect of this is a really interesting, format, for people to use, that's like much more flexible than what they ever had before.Swyx [00:30:07]: I think your job also comes becomes meta. You're not designing the products. You're designing a product to make products, and I'm curious how you manage that.Designing a Product That Makes ProductsAkshay Nathan [00:30:18]: I think one thing that we've been Like when we look at the UX, like that we've been thinking a lot about is how can we balance like simplicity with capability? Like if we're designing a product, like you said, that like is made to make up build other things, right? You can build so many different things. But we can't put that all in front of you because you'll get overwhelmed.Vibhu [00:30:41]: Yes.Akshay Nathan [00:30:41]: And so we had similar problem or similar challenges even Chat-with ChatGPT, but especially now, like when there's so much that can be done, I think the balance that we're constantly trying to strike is like, how can we give the user enough of a UI surface where, they can be expressive, they can tell the agent what they need, they can verify that it's using the right tools, it's pulling from the right sources, et cetera, but then it gets out of the way. And then how can we build the right system such that we can show them instead of telling them what can be done? Because so much of this is gonna be like, how do they discover the next use case and the next one after that if they really want to be super powered by the AI.Games, Private Evals, and Show-Don'TellVibhu [00:31:19]: Yeah. It's interesting. I feel like everyone also just has a different way to do it, right? I made a similar version of this same game. I didn't take any pictures of board or rule game. I threw in at goal eighteen minutes, fifty-three seconds later, a lot of tokens later, I've got a similar version. not with all the auto research and whatnot, butAkshay Nathan [00:31:39]: You gotta do all the latest trends.Vibhu [00:31:40]: And yeah, I did it with, did it with Codex, not Work, but it's interesting, right?Akshay Nathan [00:31:45]: Yeah. And this is GPT Image generating the pro avatars. Very good for game design. LikeVibhu [00:31:51]: AndAkshay Nathan [00:31:52]: A lot of game designers were like really into GPT Image for assets.Vibhu [00:31:54]: I will say like the broader takeaway probably is the reason that we do this is more so just to test the tools, right? Like, this was also a test for GPT-5.6 came out. I had done the game on GPT-5.5, right? The ability for me to no longer need it to. I had to feed it the rules. It's, it's a pretty niche game. It couldn't find how to do this on its own.Akshay Nathan [00:32:15]: Oh, yeah.Vibhu [00:32:15]: GPT-5.6Akshay Nathan [00:32:16]: It is out-of-distribution, which is why I was also very keen on testing the GPT-5.6 capability.Vibhu [00:32:21]: But, this is just as work comes out, as new things come out, these are just our side ways to test things, right?Akshay Nathan [00:32:27]: Yeah. It's some private eval. That is not this private.Vibhu [00:32:31]: But also valuable because now you can send this to your friends and I learned about this game through seeing this.Akshay Nathan [00:32:36]: It's a hard game. He's very good.Vibhu [00:32:39]: It's good to when no one is competing with you. But yes, it's a classic RL problem of like self-play, bootstrapping your game AI. yeah, you see how easily work becomes personal and personal becomes work because the thing I do for personal, it directly informs people I work with because I showed it to them. They were like, “Oh, you can do that with GPT?” Which like I imagine is the growth strategy.Akshay Nathan [00:33:02]: Yeah. The show not tell is a big piece that, I think we've we're not still not fully cracked of like, showing people all the things that they can do with the product versus like trying to teach that to them through like, articles or onboarding or whatever.Akshay Nathan [00:33:18]: So meeting them in the moment.Vibhu [00:33:19]: It's a career risk for me, because I used to be in developer relations, right? Where your job is to show, and then you're like, “What do you mean? You don't, you don't need.” your job is to tell. And then. But the product people are like, “Well, we don't need you if our product is intuitive enough.” SoAkshay Nathan [00:33:37]: Yeah. that's the magic of the models. So you can tailor the telling or the showing to like specifically what the user needs, like what they care about, what they've done in the past, exactly where they are on the adoption journey. So I think that's like gonna be a super big opportunity.Vibhu [00:33:50]: Seems easier and easier now to tailor custom showing, right? People have different use cases. As much as you said you don't wanna segment different people into different buckets, right? It's also not that hard to for people that are in different categories. But the question, is you said your team is more broadly on. What was the term you used? Productivity?From Developers to Knowledge Work to EveryoneAkshay Nathan [00:34:12]: Productivity.Vibhu [00:34:12]: Productivity. So howAkshay Nathan [00:34:12]: Which is now work.Vibhu [00:34:14]: Is it work? Is there another distribution that we're not hitting? Is there a group of people that will have something different than ChatGPT, Codex or Work? Is there more that the mass isn't targeting?Akshay Nathan [00:34:28]: I see it as like a sequencing, like. The vision is like bring useful agents to everyone. We started with like developers. Like developers historically are like early adopters that are willing to put up with more friction, set things up, et cetera. Like that's where, Codex started. I think the next opportunity is like what we call general knowledge work, all the other functions around developers. I think when you go from developers to this segment, like there's inherent challenges with like, this show not tell thing that we're talking about, making the product more understandable, bringing in new capabilities that matter more for this cohort than matter for developers, things like artifacts, things like computer use, et cetera. And then I think like the same learnings, like similarly how we took the learnings from developers and brought it to, general knowledge work, the next stage will be like taking the learnings from general knowledge work and bringing it to everyone no matter what they're doing in their lives. And we're already seeing that a little bit. Like this game example that you have is, something that's like on the border of like fun and personal life to, your professional life. I use ChatGPT Work full-time at home for everything, like for whatever I'm doing. I used it the other day to come up with a meal plan and like, save that on the like computer environment that it has and something that I can continue going back to. Like is everyone doing that yet? Probably not because the thing says work on it, but eventually, we wanna get people there.Vibhu [00:35:51]: ChatGPT life.Akshay Nathan [00:35:52]: Yeah, exactly. ChatGPT cooking. But I think there's a lot of, there's a lot of opportunity there, but I see it as like, we're, we're built we built a foundation in software engineering, and we're gonna take the same learnings that we take from software engineering to knowledge work to everyone.Vibhu [00:36:07]: Do you have any power user advice? I feel like, there's a group of people that will live it, use it for everything, stay on it twenty four-seven. And then there's a bit of a gap between that crew and people that, okay, I use it for work. I use it occasionally. Sometimes I type questions. any advice, any learnings, anything you recommend or just, takeaways that you've found that help bridge that gap?Power User Advice: Push the Frontier of ImaginationAkshay Nathan [00:36:30]: I think a couple things that I've seen is like, one, that it really helps to broaden your imagination of what's possible, and this has been a learning even for me. Like, the technology has progressed so fast that, something that, like, even three months ago, like, no way the models can do this. Like, now it's like, wow, it's like it can. Like,Swyx [00:36:52]: Give an exampleAkshay Nathan [00:36:52]: We're going through right now our, like, review cycle internally, and, people always talked about this as, like, a thing that the models are good at and like, there's a cliché of like: Okay, like, no one wants to be writing reviews and, like, we just use AI to do it. But in all seriousnessSwyx [00:37:09]: And it can evaluate it as well.Akshay Nathan [00:37:10]: Yeah, exactly. In all seriousness, before it was, like, just, like, slop and, like, I think it was helpful, but, not super productive. Now I've found that, like, the model can do a much better job than me, especially in this environment of, like, pulling context on, like, what people are up to, how they've like the things that they've done to make a difference, highlighting like, wins that they've had that, like, I might may not even have seen. It has access to, like, everything, right? Like the code, like, things that they've caught, reviews, Slack, everything. And so it's, like, incredibly powerful in that domain and, like, just like six months ago, the last time we did this cycle, like, I didn't even I tried using it, but it was not at all helpful. And this time it's been, like, incredibly helpful and, like, so I think continuing to push the frontier of imagination of what's possible, even if you tried something before, I think is maybe the my biggest piece of advice. The other, thing is, like, the more you put in, especially in this environment where, like, the model has access to everything on your computer or in ChatGPT Work, like you can create, artifacts over time and save them in your library and, like, the model will continue having access to those. Like, the more information you give it about whatever domain you're in, whether it's your life or your work, the more valuable it becomes, and it'll become valuable in, like, ways that might surprise you. Like, it might pull from context in a way that, may be proactive and that you might not even have thought about. But it needs to have access to those, to that those tools or that context first.Reviews, Agentic Search, and Context GatheringSwyx [00:38:27]: One thing I just wanna talk about the review stuff because I'm still that's a very sensitive thing and you're, you're a founder, you've managed people, you've hired people. As manager myself, I'm very reticent to put out any LLM-generated things especially when it comes to people, ‘cause it feels like you don't care.Swyx [00:38:46]: Presumably at OpenAI, people are more open to being eval rated by GPT. But are there any unofficial rules around this? Like, what's the etiquette?Akshay Nathan [00:38:57]: Oh, I think the etiquette is that, like, I would never write something via, like, well, solely via AI and, like, present it as, like, a review for someone. What I was talking about is more, like, gathering context. That's the place where it's incredibly helpful.Swyx [00:39:08]: So it's just search.Akshay Nathan [00:39:09]: Yeah, exactly.Swyx [00:39:09]: It's agentic search. Yeah.Akshay Nathan [00:39:10]: It's like agentic search, but, that you can tailor and steer much more capably than you could before, ‘cause, like, the thing is it's all there's a flywheel happening, right? Because of Codex, people are able to do, and because of ChatGPT, people are able to do so much more now than ever before. And if you're able to do so much more, it's easy to miss things as well. And so, like, I think we need to use these same tools to keep up with all the impact that people are having and understand, where we can be helpful.Swyx [00:39:39]: I think the thing, like, I run a small company, so easy to search, but at the scale of OpenAI with the amount of messages that you guys put in Slack, do you think that it misses things?Remembering What Humans MissAkshay Nathan [00:39:50]: Probably, but I think that I also miss things.Swyx [00:39:52]: Like, it doesn't matter, right?Vibhu [00:39:53]: I think sometimes it'sSwyx [00:39:53]: Like it's, as it needs to be human-levelAkshay Nathan [00:39:54]: It's all relative, right? Yeah.Vibhu [00:39:56]: Sometimes it's nice when it finds things you wouldn't, right? Like right now, my Codex system prompts, they're set up in such a way that every project I have has a secret- separate, notes MD, and it just writes learnings to there. And then the global one can pull from all these. So sometimes it'll be like: Oh, there's this project you did like four months ago. Here's a note that we had, and it randomly pulls it back into context that I would never do, I haven't thought about.Vibhu [00:40:20]: And I'm like, okay, this is quite superhuman, right? Like, stuff that would. And, it'll save like hours on chunking of stuff or find something that's already been done. I'm like, as much as it might miss stuff, I would too, but it's very useful when it finds stuff. And I have like a very, non-super engineered solution to this. It's just marked down files that get pulled whenever they want.Akshay Nathan [00:40:41]: Yeah. I have a funny anecdote about this. Like, recently gearing up to this launch, the team has been, really cooking on it for a couple months, and over that time, like there's so much conversation and chatter going on in Slack and Docs and elsewhere. And, one of the members of the team set up this, scheduled tasks, like automation to like look at everything that's going on and, like, come up with the best memes and then post it in one of our shared channels. And like, there are two cool things about this. Like, the first is, like, I think the models are, over time, like starting to become like funny.Swyx [00:41:13]: Funny. Nice.Akshay Nathan [00:41:13]: Whereas like, a year ago, like that was not at all the case. The second is, it was what you were saying, like they find things that in surprising ways that you may not have thought of and like create connections that you may not have thought of. And that really helps with like the meme generation because then you can see something that, genuinely surprises you and, is funny in that way. So yeah, that's like not like the most productive, use of this the technology, but it does it does uncover this, like this capability that's emerging, which is just like to find information that you otherwise would not know of.Launch Momentum and the 10 Million User MilestoneSwyx [00:41:43]: Talking about the launch, I think, I have pretty much said this is the most successful launch in a long time. I think even more successful personally than 5.0, and they're announcing ten million users. Does it feel different? You've been through a lot of launches.Akshay Nathan [00:41:58]: I think it feels like a culmination. Well, I think two things. One, it feels like a culmination, like I was mentioning earlier, like this like vision mission that we've been on for a long time. Like I said, we saw the magic of Codex internally, and then we're like extremely excited to bring this to many more people and to see it working, to like see us reach, the distribution goal, numbers that you mentioned, like I think that's like huge and super exciting. The flip side of that is like, there's so much more to do too. Like, that's also really exciting. Like, ChatGPT as a whole, like the this product that, everyone almost equates to AI and like loves, has hundreds of millions of users. And so like ten million is really cool, but like we need to get this to everyone. Like, we need everyone to feel this magic. And so that's the next step from here. But yeah, I think extremely pumped about how it's going so far and the opportunities.Swyx [00:42:46]: Awesome. I did want to also Because I've, I've, I've been tracking the number closely, it transitioned at some point from just Codex users to Codex plus ChatGPT Work, because they're same harness. The whole point is that you don't, you can't, count them separately. Do you have roughly a billion, ChatGPT users? Why did it just jump to one billion right away? Like, isn't that the default on ChatGPT or no?Codex, ChatGPT Work, and the Developer BrandAkshay Nathan [00:43:11]: We don't default you into ChatGPT Work if you're on ChatGPTSwyx [00:43:14]: If you're free. YeahAkshay Nathan [00:43:15]: It's also only available to paid users right now. And I think there's like a process of, educating users of what is the value of this product, having them try it, learning from their feedback, and making it better over time. But the goal is to, get as many of the people who love ChatGPT today to like feel the power of ChatGPT Work. But I think it'll be a journey.Swyx [00:43:36]: Yeah. And Codex will still be alive as a brand for the foreseeable future. And we'll just toggle between them as needed for UI stuff.Akshay Nathan [00:43:44]: Yeah, I think it's even stronger point than that. Like, I think we fully intend to like, treat developer. Like, developers have been, a core market for us for so long, and like there's, there's so much more that we can do to make Codex great specifically for, software development, and we'll continue to do that. This doesn't take away from that at all. If anything, it should increase the utility of something like Codex, because now you can move seamlessly between writing a diff to creating an artifact or, doing a search over your factor.Swyx [00:44:11]: I do wonder how much this terminology leaks to the non-technical user. Like, do they have to learn to say artifact if I want artifact? Or.Akshay Nathan [00:44:20]: It's funny, like we call it artifacts internally ‘cause that's what the teams call it.Swyx [00:44:23]: It's nice. Yeah.Akshay Nathan [00:44:23]: But like externally, like no one says that, no one calls it an artifact. But I think that people like often, like describe things, whatever they're used to, right? So if, ChatGPT Work is good at creating slides, they'll say ChatGPT Work is good at creating slides, and that's what we want.OpenClaw, Personal OS, and Persistent ComputersSwyx [00:44:38]: One big Another, it's July of twenty-six. One big thing that also happens in, for OpenAI was OpenClaw, and that's I think a lot of people's first time really maxing a agent for personal stuff, but also crossing over to work in essence same way. As far as I understand, OpenClaw is still independent, but did you go through your own OpenClaw moments? Were there any lessons you took from OpenClaw to Codex or back? Whatever.Akshay Nathan [00:45:06]: I think there's a lot of inspiration. I did go through my own OpenClaw moment. I,Swyx [00:45:10]: Yeah, tell the storyAkshay Nathan [00:45:10]: Me and my wife like set up an OpenClaw to like try to manage everything in our house. Not that there's like a ton, but it was like quite useful. We gave it a calendar. It started, creating events for us and stuff. At some point, the laptop that we were running on, it died and never got a chance to pick it back up. But there was a lot of inspiration there, like, in ChatGPT Work, in web and mobile, like you get access to this like persistent computer environment where, you can store files, and those files stay around between sessions. And the idea is to be able to enable use cases like this. one of the members of our team uses ChatGPT Work for what they used OpenClaw from before, and then feel like it has like completely transitioned, which is like, workout planning and like meal tracking. which again, it's like a work-related thing, right? It's like not work necessarily, but it's like in personal productivity space. But it has all the same primitives. So it has scheduled tasks. It has the ability to store files on a file system. It has the ability to like reference those things over time. And so you start to see the same types of use cases emerge, which has been really cool.Swyx [00:46:14]: Is there a point that ChatGPT Work completely replaces OpenClaw? they're independent, so.Akshay Nathan [00:46:20]: Yeah, I'm, I'm not close to it, so I can't speak to the OpenClaw roadmap, but I don't think so. I think that there's gonna be, there's always a need for like this like incredible, like open source technology that team has built. And I think that we can draw inspiration, in the product and, ChatGPT, I think many more people have like heard about and used ChatGPT than have used OpenClaw. And if we can take the magic from OpenClaw and bring it to them, I think that'll be a success. I think that like one thing on the ChatGPT Work side that we feel strongly about is that like the core experience is that you come to this product and you have a conversation, start a session, whatever you wanna call it, with this agent. And the magic of the product is that you can do anything in that moment. And we would like to create a product where you don't have to click a button or to go to a different place, whatever, and you can get whatever functionality exists in, your finances app or where or any other product like in this one place. And so that's the goal. It's like it we want an extensible system with plugins where you can connect to the tools that you need in order to be able to accomplish like a financial task, where you can, if you're doing like science work, like we have an ability to like extend the system in such that you can like write the tech and it performs well. There'll always be like products that we support that are best in class at those things, but we want as much of the magic as possible in that core experience.Swyx [00:47:45]: Yeah. Do you think that you can do everything you used to do with Wealthfront in ChatGPT Finance?Finance, Data Access, and Centralized ContextAkshay Nathan [00:47:50]: I tried it. like ChatGPT doesn't yet custody, cash and assets for me. So that part, no, not yet. But I, there was like a whole component of like retirement planning and, like financial planning and budgeting and stuff that, we were looking into when I was there. And like with the finances plugin, like that's all possible with ChatGPT today. So, I feel

Episode 213: Can ChatGPT Manage Your Business? 3 Prompts Every Esthetician Needs! Can ChatGPT really help run your esthetics business? The answer may surprise you! In this episode, Stephanie Laynes shares how estheticians, spa owners, and beauty professionals can use AI to save time, increase revenue, improve customer service, and make better business decisions. You'll also learn the 3 ChatGPT prompts Stephanie uses that every esthetician can customize for their own business today. Whether you're struggling with marketing, social media, client retention, or growing your income, these prompts can help you work smarter—not harder. In This Episode You'll Learn: How ChatGPT can become your virtual business assistant The biggest mistakes estheticians make when using AI Three powerful ChatGPT prompts you can start using immediately Ways to create marketing content in minutes instead of hours How to generate more sales while reducing overwhelm Why AI will never replace great estheticians—but will help the ones who embrace it Mentioned in This Episode ✨ FREE Communication Masterclass ✨ Join Stephanie's Instagram Broadcast Channel ✨ Enroll in the SLI Online Esthetician SchoolOnly $30/month and includes: Advanced esthetic education The Money Podcast Beauty business training Marketing strategies Monthly business coaching And much more! Stephanie's Favorite Business Resources Payroll App Esthetician Insurance Esthetician Gameplan: Pay Myself Workbook Smooth Skin Supply LLC Wholesale Connect with Stephanie Laynes

Hello everyone. Welcome to the latest episode of The Matchbox Podcast powered by Ignition Coach Co. I'm your host, Adam Saban, and on this week's episode we're talking about our own perspectives on the integration of AI in the world of training and coaching.   As always, if you like what you hear, share this with your friends and leave us a five star review and if you have any questions for the show drop us an email at matchboxpod@gmail.com or head over to ignitioncoachco.com and fill out The Matchbox Podcast listener question form.    Alight let's get into it!   For more social media content, follow along @ignitioncoachco @adamsaban6 @dizzle_dillman @dylanjawnson @kait.maddox     https://patreon.com/MatchboxPodcast?utm_medium=unknown&utm_source=join_link&utm_campaign=creatorshare_creator&utm_content=copyLink   https://www.youtube.com/c/DylanJohnsonCycling https://www.ignitioncoachco.com  https://www.youtube.com/@DrewDillmanChannel   Intro/ Outro music by AlexGrohl - song "King Around Here" - https://pixabay.com/music/id-15045/    The following was generated using Riverside.fm AI technologies   Summary In this episode, the hosts dig into a listener question about whether self-coached athletes should use AI to help build training plans. The conversation explores where AI can be genuinely useful, where it falls short, and why foundational knowledge still matters.The discussion covers practical use cases for AI, including quick research, personalized training feedback, and blood work analysis. The hosts also talk about the limitations of AI-generated plans, especially when it comes to nuance, accountability, and long-term coaching decisions.A key theme of the episode is balance: AI can be a helpful tool, but it works best when paired with training knowledge, self-awareness, and human judgment. The hosts close by weighing whether AI is a 10/10 solution for self-coached athletes, ultimately landing on a more cautious, nuanced recommendation.   Timestamps 0:00 — Welcome back and listener question on AI in coaching 0:27 — The hosts react to a funny AI-coaching reel 1:42 — Concerns about relying on AI to generate thoughts and ideas 2:45 — AI for quick research and decision-making 4:34 — Why AI can feel “too good” for writing and outlining 5:47 — Why self-coached athletes need a foundation of training knowledge 6:25 — Can ChatGPT build a training plan? 7:23 — The importance of knowing how to prompt AI well 9:22 — Where AI struggles with edge-case or nuanced decisions 12:01 — Adam explains how he's been using an AI-generated training plan 13:01 — What an AI plan does well: simple, basic, and consistent 13:59 — Repetition and limitations in progressive overload 15:53 — Why a base level of knowledge still matters 16:11 — Joe Friel's Training Bible as a foundation for self-coaching 17:26 — Adam explains how he updates his AI plan daily 18:24 — Why coaching adds nuance that generic plans miss 19:15 — AI vs. human coaching and personalization 21:45 — Training AI to be more direct and less encouraging 23:31 — ChatGPT personalities and more advanced models 35:21 — Using ChatGPT to analyze blood work 37:13 — ChatGPT vs. doctors for athlete optimization 39:31 — How much better AI gets when it knows more about you 41:30 — Is AI training worth it for a self-coached athlete? 43:13 — Why accountability still matters for some athletes 44:25 — The human side of coaching before race day 45:43 — Final scores: how much the hosts recommend AI for training 48:34 — Wrap-up and closing thoughts Key Takeaways AI is useful for speed, research, and idea generation. Self-coached athletes need enough training knowledge to judge AI output. AI can build a decent plan, but it may miss individual nuance. Human coaching still has advantages in accountability and emotional support.

People are already using AI during divorce whether attorneys like it or not.They're asking ChatGPT to:analyze texts from their exexplain legal documentshelp write co-parenting responsesbuild parenting schedulesorganize timelinesprepare for mediationand sometimes… emotionally spiral at 2amSo where's the line between using AI strategically and using it in a way that could quietly damage your case?Leave us a review!

On today's Party for Two, Jerry is at the party table with Brian Lilley, political columnist with the Toronto Sun, to break down the top stories of the day. Next, Jerry turns to Tech Topics with Francis Syms, Associate Dean of Information and Communications Technology at Humber Polytechnic, to explore the top tech topics of the day. Can ChatGPT be charged in a murder? Jerry speaks with Gavin Tighe, senior partner at Gardiner Roberts LLP and chair of the firm’s Litigation and Dispute Resolution Group, to unpack the legal implications of this. Liberal MP Nathaniel Erskine‑Smith has lost his nomination battle for an upcoming Ontario provincial byelection. Jerry speaks with CTV political commentator, Scott Reid, about this.

AI feels like a bubble. A bubble that keeps expanding until it fills the entire room—including the Off the Record podcast studio. I remain bullish about some aspects of this game-changing technology and intensely skeptical of others. Which makes it a fascinating topic. Worthy of a fascinating guest, who not only has opinions but has real-world applications for the tech you might not have thought of. Sharon Easterling has a towering, all-consuming passion for AI, specifically bridging the gap between technology and the mid-revenue cycle and navigating a technological future that can seem overwhelming. But she also leans into its creativity. She even sent me a new OTR podcast jingle created with AI! You can hear it on this episode. Listen in as we discuss: Who is Sharon Easterling, “Fractional AI Governance and Enablement Executive | AI and Digital Transformation Leader”? Are we lost in the wild west of AI? Coders are using ChatGPT to code and pass certification exams, and employers screening employees with AI bots.  How much has AI actually penetrated the mid-revenue cycle, use-wise? Can ChatGPT code? Will AI applications replace people? Where AI ais ctually making a tangible difference in the mid-revenue cycle: Denials management, surfacing diagnostic indicators, writing appeals letters, and more Some out-of-the-box suggestions of using AI in your daily workflow: From monitoring coding productivity to sending daily education to your inbox. How Sharon thinks people should view AI more broadly. Referenced on the show: Sharon's article “The Medical Record: How Artificial Intelligence (AI) Impacts Coding”:  https://icd10monitor.medlearn.com/the-medical-record-how-artificial-intelligence-aiimpacts-coding/  

THE TIM JONES AND CHRIS ARPS SHOW 0:00 SEGMENT 1: Using A.I. to write jokes 15:24 SEGMENT 2 :ZACK SMITH, Sr. Legal Fellow at The Heritage Foundation || TOPIC: Top legal headlines of the day || Can ChatGPT help you get away with murder? || Be thankful for stupid criminals || Louisiana v. Callais || Guns and Ganja update || Ed Martin faces ethics chargesx.com/tzsmithheritage.org 33:59 SEGMENT 3: Tim's military connections https://newstalkstl.com/ SHOW PAGE - https://newstalkstl.com/tim-jones-chris-arps/ FOLLOW TIM - https://twitter.com/SpeakerTimJones FOLLOW CHRIS - https://twitter.com/chris_arps 24/7 LIVESTREAM - http://bit.ly/NEWSTALKSTLSTREAMS RUMBLE - https://rumble.com/NewsTalkSTL See omnystudio.com/listener for privacy information.

What doctor or hospital TV shows do you enjoy? Which do you think are most real?Can ChatGPT be trusted for credible information from reliable and verifiable sources?Can GLP-1 drugs help with fatty liver disease?

Can ChatGPT replace my therapist?As people are turning to AI for mental health support and relationship advice, could chatbots replace the role of a trusted friend, or even a therapist?Writer: Ada BarumeProducer: Amalie SortlandHost: Tomini Babs Hosted on Acast. See acast.com/privacy for more information.

Can ChatGPT dethrone Gemini? Is Tim Cook capable of leading Apple into the next wave of AI? As 2025 winds down, journalist and podcast host Kara Swisher joins Rapid Response to cut through the noise and decode what's really happening across OpenAI, Meta, Google, and more. Swisher also sizes up the state of Disney, Netflix, and the escalating bidding war for Warner Bros. Discovery. And in classic Swisher fashion, she doesn't hold back — weighing in on Elon Musk's eye-popping potential pay package, Mark Zuckerberg's costly misfires at Meta, and what the future of AI means for human health and cognition.Visit the Rapid Response website here: https://www.rapidresponseshow.com/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Can ChatGPT dethrone Gemini? Is Tim Cook capable of leading Apple into the next wave of AI? As 2025 winds down, journalist and podcast host Kara Swisher joins Rapid Response to cut through the noise and decode what's really happening across OpenAI, Meta, Google, and more. Swisher also sizes up the state of Disney, Netflix, and the escalating bidding war for Warner Bros. Discovery. And in classic Swisher fashion, she doesn't hold back — weighing in on Elon Musk's eye-popping potential pay package, Mark Zuckerberg's costly misfires at Meta, and what the future of AI means for human health and cognition.Visit the Rapid Response website here: https://www.rapidresponseshow.com/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this community episode, we discuss the role of AI in planning your retirement. Can ChatGPT provide us with the answers? Also, how early should we start planning for retirement day? We are joined by Bill Yount from The Catching Up to FI Podcast and community member SuzyB. Learn more about your ad choices. Visit megaphone.fm/adchoices

Can ChatGPT become your new therapist?  A growing trend shows more and more people trying it out, and Anna decided to find out for herself! A recent poll equated an individual's attractiveness to the color of their car.  Anna & Raven discuss the appeal of white, black and silver cars (and their drivers)! Anna was asked by a stranger to help take a locker room “before” picture!  What other unusual things go on in the private space of gym locker rooms? Anna and Raven think that self-checkout shouldn't be a thing! Find out why they can't stand it! Anna, Raven and Producer Justin tried to go all weekend without their phones! Find out how long they were able to stay disconnected! A report of an escalating fight between neighbors over a driveway easement sparked a conversation about the best way to handle drama on the block!  Anna & Raven find out what makes good and bad neighbors! Are you up to date on this week's biggest news stories?  Anna and Raven will get you caught up on what's trending, including a terrifying twin mix up! Pick'em news - Anna picks three crazy news stories, and Raven picks one to talk about.  His options are: Demi Lovato's questionable criticism of frozen yogurt, a teacher getting charged a small fortune for being a nice guy, and a death metal singer doing something nice for the kids! With the prices of everything constantly rising, Anna & Raven find out what peoples' breaking point is regarding one essential daily staple!  Couples Court – Nick's parents live in Greece and usually travel to stay with them for a week or two around the holidays. This year they've notified Nick and his wife, Linda, that they would like to come stay with them for about seven weeks, from Thanksgiving through New Years. Linda thinks it's too much, they don't drive, it's a lot of cooking with her mother-in-law, it's just too much to have them around the whole time. Nick thinks you can't say no, they're so excited to spend time with the kids! What do you think? Can't Beat Raven – Lou has a chance to win $3000!  All he has to do is take down Raven in pop culture trivia!

Can ChatGPT really replace McKinsey? The hype says yes—but the truth? Not even close. In this episode of Smart Consulting Sourcing, Hélène Laffitte cuts through the noise and reveals how Generative AI is truly reshaping the consulting world. AI isn't killing consulting—it's killing bad consulting. From flashy claims to “10 prompts to replace McKinsey” memes, Hélène explains why technology can't substitute for real expertise, context, and judgment. She breaks down how Gen AI actually works, where it genuinely accelerates consulting delivery, and why understanding its limits is just as important as embracing its power. From spotting “AI-washing” in proposals to knowing when to lean on human insight, this episode uncovers how consulting's real value is evolving—from decks to decisions, insights, and execution. Tune in to discover how to make AI your consulting ally—not your replacement.

Can ChatGPT transform the future of banking UX design — or will it replace designers altogether?In this episode of the UXDA Podcast, we dive into how generative AI, like ChatGPT, is reshaping the way digital banking products are researched, designed, and optimized. From simulating user personas and analyzing feedback to crafting accessible interfaces and personalized microcopy — AI is becoming an integral design partner.But here's the catch: while AI can accelerate workflows and spark innovation, it can't replicate human empathy, ethics, or strategic vision — especially in an industry built on trust.Discover how forward-thinking designers are harnessing AI as a collaborator, not a competitor, to create smarter, more human-centered financial experiences.Find out:How ChatGPT enhances financial UX design from research to prototypingWhy empathy and ethical judgment keep humans irreplaceable in designHow to use AI to deepen user understanding and stay ahead of market shiftsRead the full article on UXDA's blog: https://www.theuxda.com/blog/banking-innovations-using-chatgpt-prompts-in-digital-product-design* AI podcast on UXDA article powered by Google NotebookLM

There's a woman charging between $200 and $10,000 to name your baby. Can ChatGPT do a better job capturing the vibes and aesthetics of a name? We find out with Ask A.I.!

Can ChatGPT really help manage your budget? Join Canna Campbell - a financial planner for 20 years - and Fear & Greed's Michael Thompson as they put AI through its paces to see whether it can help a household manage its money. --- The information in this podcast is general in nature and does not take into account your personal circumstances, financial needs or objectives. Before acting on any information, you should consider the appropriateness of it and the relevant product having regard to your objectives, financial situation and needs. In particular, you should seek independent financial advice and read the relevant Product Disclosure Statement or other offer document prior to acquiring any financial product.​Canna Campbell is an Authorised Representative and Financial Adviser of Links Licensee Services Pty Ltd AFSL No. 700012 ABN 97 678 975 589.See omnystudio.com/listener for privacy information.

A recent study called into question a core assumption about the generative AI revolution: that these tools, at the very least, will make us more productive. In this episode, Cal dives deep into the study and argues that when it comes to efforts that require deep work, AI can sometimes make things worse. He then answers listener questions and then takes a closer look at an article claiming that the lack of Wi-Fi in a West Virginia school is making their students dumber. Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here's the link: bit.ly/3U3sTvoVideo from today's episode:  youtube.com/calnewportmediaDeep Dive: Deep Work in the Age of AI [0:38]Can ChatGPT chats act as single purpose notebooks for projects? [26:16]When should I apply active recall? [29:34]Do you have insights into AI's environmental impact? [31:16]What would you do if you left academia? [38:40]CASE STUDY: Using strategies to develop a Deep Life [43:04]CAL REACTS: Does lack of Wi-Fi make students dumber? [53:09W]Links:Buy Cal's latest book, “Slow Productivity” at calnewport.com/slowGet a signed copy of Cal's “Slow Productivity” at peoplesbooktakoma.com/event/cal-newport/Cal's monthly book directory: bramses.notion.site/059db2641def4a88988b4d2cee4657ba?metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/theatlantic.com/economy/archive/2025/09/ai-bubble-us-economy/684128/marginalrevolution.com/marginalrevolution/2025/08/the-school-without-wifi.htmleducationrecoveryscorecard.org/wp-content/uploads/2025/02/report_WV_5401140_pocahontas-county-schools.pdfThanks to our Sponsors: This show is sponsored by BetterHelp:betterhelp.com/deepquestionscozyearth.com/deepshopify.com/deepmybodytutor.comThanks to Jesse Miller for production, Jay Kerstens for the intro music, and Mark Miles for mastering. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Failing to cite your secondary sources in briefs is poor form. But is it plagiarism? Jeff and Tim debate. And when the Supreme Court The publishes a case, should it explain itself? PJ Gilbert and Tim say yes, Supreme Court and Jeff disagree.Also in this episode:Can copying from a CLE article really get you sanctioned? Kelly v. Tao suggests… maybe.Presiding Justice Gilbert rails (again) against the Court's silent de-publishing practices.Deny a request for admission in a one-way fee-shifting case? You might still owe fees—Gammo v. Morrell.$105k in sanctions after failing to abandon claims disproven in discovery—Atlantic v. Baroness.The perils of citing the wrong fee statute—Martin v. Hogue.Gibson Dunn bills $1.8M for May alone in public interest litigation over LA homelessness.Can ChatGPT testify against you? OpenAI's CEO says maybe.How AI tools are reshaping billing, ethics, and expectations for appellate lawyers.Tune in for AI ethics, briefing blunders, and why even your RFA denials could cost you.

Can chatGPT do Christian scholarship?

Can chatGPT do Christian scholarship?

Host Mikalyn DeFoor, MD Guest interviewee Arianna L. Gianakos, DO, discussing her research article, “Can ChatGPT-4 Diagnose and Treat Like an Orthopaedic Surgeon? Testing Clinical Decision Making and Diagnostic Ability in Soft-Tissue Pathologies of the Foot and Ankle” from the August 15, 2025 issue Article summarized from the August 1, 2025 issue Research article “Patients With Diabetes on Sodium-Glucose Cotransporter-2 Inhibitors Undergoing Total Knee Arthroplasty Are at Increased Odds for a Number of Postoperative Adverse Events But Reduced Risk of Transfusion” Articles summarized from the August 15, 2025 issue Review article “Management and Return to Play of the Elite Athlete for Common Sports-Related Injuries About the Ankle” Follow this link to download these and other articles from the August 1, 2025 issue of JAAOS and the August 15, 2025 issue of JAAOS. The JAAOS Unplugged podcast series is brought to you by the Journal of the American Academy of Orthopaedic Surgeons and the AAOS Resident Assembly.

Kristan Hawkins goes head-to-head with ChatGPT to debate the most important human rights issues of our time: abortion.    Can ChatGPT hold its own?   Then, Kristan reads some of the most unhinged DMs she's received recently from abortion supporters.    Spoiler alert: it's not pretty.   JOIN MY TEXT LINE:    Text "KRISTAN" to 53445 for daily pro-life updates from me.   Don't forget to like, subscribe, and share this episode to stay informed and spread the word!   Instagram:  https://www.instagram.com/kristanmercerhawkins/ X: https://x.com/KristanHawkins Facebook:   https://www.facebook.com/HawkinsKristan

Is technology ruining our connection with our kids, or can it actually enhance it? In this eye-opening episode, Michelle Dempsey-Multack sits down with Zoe Moed, tech-savvy mom and creator of @technically.mama, to explore how artificial intelligence can reduce the mental load, improve co-parenting communication, and deepen the joy of everyday parenting. From ChatGPT bedtime stories to emotionally intelligent texting, this conversation is a masterclass in modern motherhood and digital resilience. What You'll Learn: How to use ChatGPT as your parenting assistant, co-parenting coach, and bedtime story creator Why screen intent, not screen time, is the new north star for tech-conscious parenting The truth behind “Botox, Lothox” and how social media pressures distort motherhood Tactical tips for reducing conflict with a toxic ex using AI-generated responses Creative ways to bond with your kids using AI-driven activities and lessons Episode Chapters & Highlights: 4:12 – What inspired the viral "Botox, Lothox" post about the contradictions of modern motherhood 07:34 – Why doing less often leads to more connection with your kids 11:40 – Can ChatGPT help co-parents manage toxic texting without emotional exhaustion? 15:22 – Step-by-step: How Zoe uses AI to generate bedtime stories, complete with teaching moments 18:01 – Creating personalized coloring sheets and activity bundles with your kids' favorite themes 21:09 – Tech boundaries and how Zoe teaches her kids that “phones are tricky” 25:45 – Why parents must model healthy tech habits before policing their children's screen use About our Guest: Zoe Moed (@technically.mama) is a former tech marketer turned content creator focused on helping moms integrate AI tools into parenting with intention and humor. Her viral insights bring together empathy, digital literacy, and a no-nonsense approach to motherhood. Tools, Frameworks, or Strategies Mentioned: "ChatGPT as Personal Assistant" framework – Use AI to plan meals, manage schedules, write emails, and craft co-parenting texts Prompting Language Tips – How to give ChatGPT specific roles (e.g., “Act as a pediatric psychologist”) to get high-quality output The Phone Box Ritual – A tangible method for reducing parental screen time and modeling tech mindfulness AI-Powered Bedtime Routine – Custom story prompts to generate kid-friendly, value-based narratives with images Emotional Detachment Protocol – AI-assisted texting for conflict-free co-parenting communication Closing Insight: "Let ChatGPT be the texter. You are the copy-paster." — Zoe Moed Technology isn't the enemy, it's the opportunity. With a little prompting and a lot of intention, moms can reclaim their time, protect their peace, and still show up as deeply connected parents. Want to learn more? This in-depth and informative course from Michelle was created to address this topic: How to Safeguard Your Relationship With Your Children When You Have a High-Conflict Ex Spouse Course Get one-on-one coaching from Michelle: https://michelledempsey.com/coaching/ Learn more about The Moving On Method® https://michelledempsey.com/shop-courses/ Subscribe to our YouTube Channel: https://www.youtube.com/@TheMichelleDempsey Website - https://michelledempsey.com/ Facebook - https://www.facebook.com/michelle645 TikTok - https://www.tiktok.com/@themichelledempsey1 LinkedIn: https://www.linkedin.com/in/mldempsey/ LINK TO TRANSCRIPT: http://michelledempsey.com/253 Learn more about your ad choices. Visit megaphone.fm/adchoices

"AI is coming for everyone's jobs." In this thought-provoking episode of Got Somme, host Angus O'Loughlin puts artificial intelligence to the test in a head-to-head wine tasting battle against one of Australia’s top Master Sommeliers, Carlos Santos. Can ChatGPT hold its own in a blind tasting of red wine? How does AI fare in analysing the nuances of a French Chardonnay? The episode explores how technology in wine—particularly AI—could shape the future of wine assessment, wine pairing, and sommelier culture. With both participants sharing their insights, tasting notes, and predictions, this is a must-listen for anyone curious about the intersection of AI and the wine industry. Listen now to explore the bold new frontier where technology meets terroir—and find out who really knows their wine: man or machine? Sponsors: RIEDEL Veloce Chardonnay: https://www.riedel.com/en-au/shop/veloce/chardonnay-633000097 Grays.com Buy the wine, drink the wine where we get ours: https://www.grays.com/search/wine Socials: TikTok: https://www.tiktok.com/@gotsommepodcast Instagram: https://www.instagram.com/gotsomme Key Takeaways:

Can ChatGPT accurately analyze a GI Map stool test? I put it to the test using my own stool test results—and the outcome was… shocking.Because more people rely on AI for lab interpretation and even protocols, I thought it would be valuable to see how its advice compares to that of a seasoned clinical nutritionist (with over 8 years of experience). In this episode, I walk you through my stool test results, ChatGPT's interpretation, and lastly – the protocol suggested by ChatGPT.Before you upload any testing to AI – you need to listen to this!⭐️Mentioned in This Episode:- Get access to my tested protocols to FIX your skin

In this episode of Tank Talk, Shannon and Cassie dive into the hot topic of AI and environmental compliance. Cassie Kuzis, part of the Integrity Environmental team, joins the podcast for the first time with Shannon to weigh in on AI. With AI tools becoming more common in operations, Shannon decided to run a little experiment: Can ChatGPT write a Spill Prevention, Control, and Countermeasure (SPCC) Plan? Spoiler alert - it didn't go well. Shannon walks us through the results of three AI-generated SPCC plans, revealing the major compliance failures, regulatory inaccuracies, and risky oversights that came with each attempt. From missing signatures and misapplied containment definitions to false statements and oversimplified training requirements, the experiment highlights why environmental plans and permits should always be developed by qualified professionals. Tune in to hear: Why SPCCs are legal documents - and why that matters Where AI went wrong (and what it surprisingly got right) What you should do when considering tech support for environmental planning This is a must-listen for facility managers, compliance officers, and anyone curious about the limits of AI in regulated industries. Support the showintro/outro created with GarageBand

Gehörst du auch zu den Menschen, die nach jeder ChatGPT-Anfrage erstmal "bitte" und "danke" sagen und sich vielleicht fragen, ob das überhaupt notwendig ist? In dieser Folge tauchen wir ein in dieses spannende Thema an der Schnittstelle zwischen Technik, Pragmatik und Gesellschaft: Wie gut kann künstliche Intelligenz Höflichkeit erkennen – und vielleicht sogar selbst höflich agieren?Dafür schauen wir in die Höflichkeitsforschung und klären zunächst, was Höflichkeit eigentlich ist. Mit der Theorie von Penelope Brown und Stephen Levinson schauen wir uns im Detail an, wie wir höflich kommunizieren und warum wir dafür manchmal einen Umweg der Kommunikation wählen. Abschließend schauen wir uns zwei aktuelle Studien genauer an, die untersucht haben, ob und wie KI Höflichkeit verstehen und selbst produzieren kann. Das Ergebnis ist spannend, denn es ist nicht alles Gold, was glänzt...Ein Podcast von Anton und Jakob. Instagram: https://www.instagram.com/sprachpfade --- Grundlagenliteratur: Ehrhardt, Claus (2018): Höflichkeit. In Frank Liedtke & Astrid Tuchen (Hrsg.), Handbuch Pragmatik, 282–292. Stuttgart: J.B. Metzler. doi:10.1007/978-3-476-04624-6_28.Brown, Penelope & Stephen C. Levinson (2007): Gesichtsbedrohende Akte. In Steffen K. Herrmann, Sybille Krämer & Hannes Kuch (Hrsg.), Verletzende Worte. Die Grammatik sprachlicher Missachtung, 59–88. Bielefeld: transcript Verlag. doi:10.1515/9783839405659-003. Dynel, Marta. 2023. Lessons in linguistics with ChatGPT: Metapragmatics, metacommunication, metadiscourse and metalanguage in human-AI interactions. Language & Communication 93. 107–124. https://doi.org/10.1016/j.langcom.2023.09.002.Studien:Andersson, Marta & Dan McIntyre. 2025. Can ChatGPT recognize impoliteness? An exploratory study of the pragmatic awareness of a large language model. Journal of Pragmatics 239. 16–36. https://doi.org/10.1016/j.pragma.2025.02.001.Lee, Soo-Hwan & Shaonan Wang. 2023. Do language models know how to be polite? Society for Computation in Linguistics. University of Massachusetts Amherst Libraries 6(1). https://doi.org/10.7275/8621-5w02. --- weitere Links: Chomsky, Noam, Ian Roberts & Jeffrey Watumull. 2023. Opinion | Noam Chomsky: The False Promise of ChatGPT. The New York Times, sec. Opinion. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html. Zugriff am 04.05.2025. Marino, Andru. 2025. Oh no, I turned everything into an AI podcast. The Verge. https://www.theverge.com/video/663196/oh-no-i-turned-everything-into-an-ai-podcast. Zugriff am 11.05.2025. Gegenüber Themenvorschlägen für die kommenden Ausflüge in die Sprachwissenschaft und Anregungen jeder Art sind wir stets offen. Wir freuen uns auf euer Feedback! Schreibt uns dazu einfach an oder in die DMs: anton.sprachpfade@protonmail.com oder jakob.sprachpfade@protonmail.com --- Grafiken und Musik von Elias Kündiger https://on.soundcloud.com/ySNQ6

Can ChatGPT replace us? Also, who will win the 2025 Masters? We talk about players refusing to kill Sabrina Carpenter in Fortnite, Luka Doncic getting emotion and then going off in his return to Dallas, and lots more!

Hey Folks, and welcome to Drinking Alone, With Friends! This episode we imagine, what would our podcast sound like if AI did it? Can ChatGPT tell us our on air personalities? And would you chose on a time traveling, dimension hopping bar crawl? Three Handles on Our Frosty Mug of Wisdom Grammarly American Primeval Mickey 17 Follow us: Instagram YouTube Facebook Discord  Support our Beer Buying Habits on Patreon (don't forget to subscribe to drink with Chris while he drinks a Bud Light Chelada!) Chris' Twitch Stream e(nvelope)-mail us! Click here to let Jordan know your breakfast choices Special Thanks to the following for being AWESOME! Jordan, known only for making great Jingles! Jake for being a great Friend, Twitch Mod and Trader of Beers! Sal for being the best letter writer/Tud challenger/beer sender ever! Larissa for being the ULTIMATE handle giver of the podcast! Shea for becoming a ROCKSTAR patron!

Can ChatGPT save a relationship? Also, what is cockroach milk? We talk about the new public domain horror movie called Bambi: The Reckoning, Monopoly coming out with an app banking version marketed to kids, and lots more!

This New Year's Day, Mijal and Noam introduce our “Top 5 Staff Picks” in a special countdown to Wondering Jews' first birthday. They reflect on 2024 and introduce the re-release of one of Unpacked staff's favorite episodes, "Can ChatGPT replace my Rabbi?" Mijal and Noam discuss the evolving role of rabbis and whether artificial intelligence can replace or supplement these roles. At the same time, they explore various responsibilities of rabbis, such as providing information, teaching, offering care and support, making decisions, and serving as role models. Listen again or for the first time. Get in touch at WonderingJews@jewishunpacked.com, and call us, 1-833-WON-Jews. Follow @jewishunpacked on Instagram ------------ This podcast was brought to you by Unpacked, a division of OpenDor Media. For other podcasts from Unpacked, check out: Jewish History Nerds Unpacking Israeli History Soulful Jewish Living Stars of David with Elon Gold 

Back on Liron's Doom Debates podcast! Will we actually get around to the subject of superintelligent AI this time? Is it time to worry about the end of the world? Will Ben and Vaden emotionally recover from the devastating youtube comments from the last episode? Follow Liron on twitter (@liron) and check out the Doom Debates youtube channel (https://www.youtube.com/@DoomDebates) and podcast (https://podcasts.apple.com/us/podcast/doom-debates/id1751366208). We discuss Definitions of "new knowledge" The reliance of deep learning on induction Can AIs be creative? The limits of statistical prediction Predictions of what deep learning cannot accomplish Can ChatGPT write funny jokes? Trends versus principles The psychological consequences of doomerism Socials Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani, @liron Come join our discord server! DM us on twitter or send us an email to get a supersecret link The world is going to end soon, might as well get exclusive bonus content by becoming a patreon subscriber here (https://www.patreon.com/Increments). Or give us one-time cash donations to help cover our lack of cash donations here (https://ko-fi.com/increments). Click dem like buttons on youtube (https://www.youtube.com/channel/UC_4wZzQyoW4s4ZuE4FY9DQQ) Was Vaden's two week anti-debate bro reeducation camp successful? Tell us at incrementspodcast@gmail.com Special Guest: Liron Shapira.

When it comes to preparing for an interview or making an important life decision, more and more people are turning to AI for advice. ChatGPT's new voice interface, Advanced Voice Mode, allows users to speak out loud and converse with a chatbot as they would with another human — but is it really as seamless as a chat with a friend? Bilawal runs a series of experiments with Advanced Voice Mode to test the limits of this new technology and its potential uses, from weighing the pros and cons of a cross-country move to coaching an intense personal workout. He and producer Dominic Girard discuss the potential benefits and dangers of this new advancement, and ask perhaps the most important question of all: Can ChatGPT pronounce Bilawal's name?  For transcripts for The TED AI Show, visit go.ted.com/TTAIS-transcripts    

We have all seen the news articles that ChatGPT and other AI models can pass the MCAT and LSAT. As educators, we worry about computers passing tests, not students. However, is there an opportunity for AI to help us in the classroom, not by taking the test but by writing the explanations for the correct answers? Join us this month for Journal Club, where we will discuss exactly that and review the article: Can ChatGPT generate practice question explanations for medical students, a new faculty teaching tool?https://www.tandfonline.com/doi/full/10.1080/0142159X.2024.2363486

October 25, 2024: What happens when AI starts making medical decisions? A recent UCSF study reveals startling insights into ChatGPT's performance in emergency departments, showing that AI overprescribes treatments and tests. Are we on the verge of a healthcare breakthrough or creating more problems? Join Kate Gamble and Sarah Richardson as they explore the risks and potential of AI in emergency care, and what it means for the future of patient outcomes. Can ChatGPT be trusted with life-or-death decisions? Tune in to find out.Subscribe: This Week HealthTwitter: This Week HealthLinkedIn: Week HealthDonate: Alex's Lemonade Stand: Foundation for Childhood Cancer

Can ChatGPT pick who we vote for? Will AI steal our jobs? This episode explores the conversation of fears, facts, and future of Artificial Intelligence.

This week, we're talking about artificial intelligence. Can the TikTok algorithm diagnose our queerness? Can ChatGPT be our therapist? Is AI any more accurate than a good old fashioned “Am I Bisexual” internet quiz? Support us on Patreon and get exclusive access to cool stuff here: https://www.patreon.com/thebipod Prefer to get social first? Follow us on Instagram @TheBiPod. Want to be included in future mail bag episodes, or just give us your thoughts? You can leave us a voicemail at (480) Hi Bi Pod (480-442-1763) or email us at hey@thebipod.com.

Can ChatGPT diagnose Clint's current health problems? What is helping Dr. Jenn dig deeper in her sexual vulnerability? Plus, Clint offers terrible advice to Dr. Jenn about attending an elementary school's talent show. 

AI is creating an impact on privacy, security, and jobs. And this is what we discussed with our guest Jan Anisimowicz and host Punit Bhatia in this episode. We explore how technologies like ChatGPT have revolutionized data privacy practices, telling both opportunities and challenges. Analyzing the major risks AI poses to information security and the ethical concerns that arise in the wake of AI-powered systems.   KEY CONVERSATION POINT  00:02:48 How has AI transformed privacy practices? 00:04:00 How is AI evolution crucial to handling volumes of data?  00:04:43 What are the major AI risks?  00:06:23 Would this create ethical concerns?   00:07:53 Is the algorithm biased?   00:11:28 What is the current state of AI regulations?   00:11:28 Are they also revolutionizing cyber security? How is it working?  00:14:38 Is there consent for data usage? What are the potential solutions to ensure transparency when it comes to data processing?  00:18:00 Is there a risk that Al would take all the jobs of the people around the world?  00:20:11 Can ChatGPT substitute auditors?    ABOUT THE GUEST  Jan Anisimowicz, experienced senior IT Executive with an impressive career spanning over 23 years. Jan's expertise encompasses a wide spectrum, including Governance, Risk and Compliance (GRC), Data Warehousing, Business Intelligence, and Data Analysis. Throughout his professional journey, he has contributed significantly to the telecommunication, banking, pharmaceutical, and insurance sectors, leveraging his comprehensive business and technical acumen. He is particularly skilled in orchestrating the creation and development of IT products and services tailored to suit specific business needs. His philosophy is centered around a pragmatic end-to-end product lifecycle that seamlessly integrates various aspects such as technical design, marketing, digital campaigning, sales, solution delivery, and maintenance. He is a proponent of lean, cost-effective approaches toward implementing regulatory requirements within organizations. His work also extends to the analytical evaluation and validation of the role of Artificial Intelligence (AI) in assisting auditors, particularly within Big Data and cloud IT landscapes. He is a firm believer in the potential of blockchain technology, particularly its capabilities with Smart Contracts concerning data privacy principles. Furthermore, He is an ardent supporter of Quantum Computing and AI, including LLM models supporting solutions akin to ChatGPT. His professional certifications include CISM and CRISC from ISACA, PMP from PMI, and membership with the Institute of Internal Auditors (IIA). Additionally, He is an ESG Approved Officer, a credential awarded by the Institute of Compliance.  ABOUT THE HOST  Punit Bhatia is one of the leading privacy experts who works independently and has worked with professionals in over 30 countries. Punit works with business and privacy leaders to create an organization culture with high privacy awareness and compliance as a business priority. Selectively, Punit is open to mentor and coach privacy professionals.  Punit is the author of books “Be Ready for GDPR'' which was rated as the best GDPR Book, “AI & Privacy – How to Find Balance”, “Intro To GDPR”, and “Be an Effective DPO”. Punit is a global speaker who has spoken at over 30 global events. Punit is the creator and host of the FIT4PRIVACY Podcast. This podcast has been featured amongst top GDPR and privacy podcasts.  As a person, Punit is an avid thinker and believes in thinking, believing, and acting in line with one's value to have joy in life. He has developed the philosophy named ‘ABC for joy of life' which passionately shares. Punit is based out of Belgium, the heart of Europe.   RESOURCES: Websites: www.fit4privacy.com , www.punitbhatia.com  Podcast: www.fit4privacy.com/podcast  Blog: www.fit4privacy.com  YouTube: youtube.com/fit4privacy   --- Send in a voice message: https://podcasters.spotify.com/pod/show/fit4privacy/message

Happy Holiday Movie Season, Wholigans! In celebration of the tortuous season of cheerful movies made for $23.99 each, we're bringing you an episode-length game show during which we quiz each other about alllllll the offerings from fonts of content like Great American Family, Lifetime, Hallmark, BET+, Roku, QVC, Freevee, and more! Which Desperate Housewife is in multiple movies this year? Can ChatGPT come up with convincing ideas? Why is QVC releasing Christmas movies at all? Yule learn a lot more than just that in today's episode. It's giving sleigh!!!!!!!!! Grunch Grunch!!!!! Call 619.WHO.THEM to leave questions, comments & concerns, and we may play your call on a future episode. Support us and get a TON of bonus content over on Patreon.com/WhoWeekly. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Welcome back to part 2 of building a brand live with AI! Can ChatGPT and other AI tools actually help you build your company from scratch? We're picking up where we left off in part 1 and showing you how to create a competitive SWOT, generate product photos, and even set up an entire website in seconds! Buckle up and get ready to ride!Watch Part 1: Build a Brand Live with AI (Part 1)Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions about AI and brand buildingUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:[00:01:15] Daily AI news[00:05:20] Part 1 recap[00:10:00] Competitive SWOT and landing page copy in ChatGPT[00:16:00] Generating product photos with Midjourney and DALL-E[00:28:30] Using ChatGPT custom instructions with DALL-E[00:45:10] Logo touch ups with Canva's AI[00:50:35] Creating professional product photos with Flair.ai[00:55:50] Generating a website with Durable[01:04:00] Final takeawaysTopics Covered in This Episode:1. Creating a competitive SWOT analysis 2. Generating Marketing Copy with ChatGPT3. Generating Image Prompts using ChatGPT4. Using ChatGPT and DALL E to Create Product Images5. Creating a Website Using AIKeywords:mug design, modified mug, pictures of man, digital nomad, entrepreneur, feedback, image preferences, zooming in, upscaling image, interactive presentation, ChatGPT, image prompts, MidJourney, DALL E, text-based image prompt, StableSit mug, travel mug, spill-proof, on the go, remote lifestyle, sturdy base, vacuum-sealed top, target audience, marketing copy, AI regulation, executive order, job displacement, privacy concerns, plug-in packs, proper prompting, CentML, AI chip shortage. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Can ChatGPT write just like you? The answer is yes! We're breaking down 5 tips to make ChatGPT sound human and write exactly how you want it to.  Newsletter: Sign-up for our free daily newsletterMore on this: Episode PageJoin the discussion: Ask Jordan questions about ChatGPTUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:[00:01:45] Daily AI news[00:6:10] AI can write as well as humans and faster[00:10:55] Using the right ChatGPT mode[00:13:00] Give it writing samples and resources[00:15:40] Make sure to Prime, Prompt, Polish[00:17:40] Train ChatGPT like an employee[00:20:45] Keep chat memory in mind and recall[00:24:35] Final takeaway Topics Covered in This Episode:- Recap of recent AI news:- Zoom using customer data for AI training- Meta's focus on generative AI models- Microsoft's expansion of Bing AI chat to more browsers- Main topic: How to make Chat GPT write like a human- Importance of using Chat GPT effectively for human-like writing- Five tips for using Chat GPT effectively:- Understand the prompts and goals- Provide context and specific instructions- Be an active editor and reviewer- Iterate and improve your conversation with the model- Utilize additional tools and resources for extra support- Demonstration of effective interaction with Chat GPT to produce a well-written postKeywords:Everyday AI, podcast, live stream, newsletter, AI, business growth, career growth, ChatGPT, human-like writing, AI news, Zoom, customer data, AI training, Meta, generative AI models, Microsoft, Bing AI, browsers, effective use, writing, AI writer tips, interaction, well-written post Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Can ChatGPT stand up to the task of being our host today? That's what we're going to find out! We're using ChatGPT to provide the inside scoop on the latest AI news and follow-up questions for Jordan and co-host/producer Brandon!Time Stamps:[00:00:00] How we're using ChatGPT for today's episode[00:02:53] Anderson Horowat says AI is going to save the world[00:05:25] Invisible AI's new AI cameras watch you work[00:08:50] AI writing for WordPress[00:14:01] Business Insider's 10 roles that AI will replace[00:15:02] Is ChatGPT the future of the workplace?[00:18:30] Companies crashed surfing the GPT wave[00:22:05] AI monitoring may not need humans soonFor full show notes, head to YourEverydayAI.comTopics Covered in Today's Episode:- Uncertainty around ChatGPT's impact on the workplace- Goldman Sachs study suggests that up to 300 million jobs could be impacted by AI- AI implementation needs to be approached correctly to benefit companies and jobs- Should AI editing and proofreading in the office always be monitored by a human?- Discussion of using AI agents to monitor work- WordPress' new AI technology- Significance of GPT 3.5 and GPT 4 in AI technologyKeywords:ChatGPT, AI writing assistant, Hemingway, Jasper, WordPress, productivity, workplace, small and medium-sized businesses, Goldman Sachs, job titles, technological advancements, data, Automatic, Jetpack AI assistant, selectable writing tones, grammar, spell checking, fear, decision-makers, editing, proofreading, technology, agents, fact-checking, AI-generated output, WordPress version, GPT 3.5, GPT 4. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

The regulators have not been sleeping on the AI revolution. Everybody wants to get in on the blue checkmark game. But this time, with actual utility. Airbnb now offers to rent out single rooms. Can ChatGPT out invest professional money managers? And the return of the flip phone. No, not a foldable phone. The flip phone from your youth.Sponsors:Bloomberg.com/careersThe Traceroute PodcastLinks:“We must regulate AI,” FTC Chair Khan says (ArsTechnica)UK competition watchdog launches review of AI market (Financial Times)Microsoft's Bing chatbot gets smarter with restaurant bookings, image results, and more (The Verge)Gmail is adding a blue checkmark to better verify senders (9to5Google)Airbnb Revamps Site to Ease Tensions Between Guests, Hosts (Bloomberg)ChatGPT ‘portfolio' outperforms leading UK funds (Financial Times)Gen Zers Are Snapping Up Flip Phones. They Might Be Onto Something. (WSJ)See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Picture of the Week. Microsoft and Fortra go on the offensive. Can ChatGPT keep a secret? Apple updates their OS's. Wordpress under attack... again. Mozilla's Site Breach Monitor. Another ChatGPT investigation. Samsung handsets reaching EoL. Less access for loan apps. The right to be forgotten. SpinRite. A Dangerous Interpretation. Show Notes: https://www.grc.com/sn/SN-918-Notes.pdf   Hosts: Steve Gibson and Jason Howell Download or subscribe to this show at https://twit.tv/shows/security-now. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can submit a question to Security Now! at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Sponsors: joindeleteme.com/twittv meraki.cisco.com/twit kolide.com/securitynow

In this episode of The More You Know, we discuss the latest in pop culture, including our initial thoughts on Prince Harry's memoir Spare, our favorite seasons of the Bachelor / Bachelorette, and our casting ideas for the next installment of Puss In Boots. Plus Erin shares how she was shaped by the film 8 Mile. MENTIONSNew! There's so much new stuff coming your way if you become a BFOTS on Patreon. Sign up for the annual plan and get our Harry Potter recaps at knoxandjamie.com/annualIt's real: MILF ManorComing up: The Mandalorian (cute: see Pedro and Bella interview)Fact check: Raven's Home > That's So Raven2014 Throwback: This Is Where I Leave You (HBO)Our favorite Bach seasons: Hannah Brown, Petey 4 Times, Ari, Rachel Lindsay, TayshiaWhat's the Word? // 8 Mile series | In Da Club | Eminem in Funny People | (I may regret linking this NSFW scene but…) Brittany Murphy licks her hand | Casting: Bad Bunny, The Spice Girls, Barenaked Ladies, Pete Wentz, Ashlee Simpson married Evan Ross (brother to Tracee Ellen Ellis Ross)? | Can ChatGPT write our script?How do we feel? // Spare by Prince Harry | Jamie's favorites celebrity memoirs: Jessica Simpson, Andre Agassi, Carrie Fisher, Tina TurnerBox Office Recap // Avatar 2 | M3GAN | Puss in Boots 2 | A Man Called Otto (listen: Episode 1 of What Should I Read Next, read: A Man Called Ove) | Black Panther | Plane | Dog Gone (Netflix) | The Hatchet Wielding Hitchhiker (Netflix) | Skinamarink | The Last of Us | MILF ManorNepo babies commentary: bad (Tom Hanks) vs. good (Allison Williams)Trailer Park // Renfield (IMDb: Nicholas Hoult, Nicolas Cage, Chris McKay photo) | You People (Green light: Stutz, IMDb: Kenya Barris, Crazy Stupid Love, Eddie Murphy, Jonah Hill, Seth Rogan, Moneyball)Red light mentions // Chris Harrison podcast | Bobby Petrino motorcycle accident | Jordan Davis leads the UGA bandBONUS SEGMENTOur Patreon supporters can get full access to this week's The More You Know news segment. Become a partner. This week our BFOTS can get the audio for last month's AUA and catch last night's replay. GREEN LIGHTSJamie: (book) Nettle & Bone by T. Kingfisher | (documentary) The Volcano: Rescue From Whakaari (Netflix)Knox: (movie) M3GANSHOW SPONSORSBabble: Get up to 55% off your subscription at babbel.com/popcastOlive & June: Get 20% off with oliveandjune.com/popSubscribe to Episodes: iTunes | Android Subscribe to our Monthly Newsletter: knoxandjamie.com/newsletterShop our Amazon Link: amazon.com/shop/thepopcast | this week's featured itemFollow Us: Instagram | Twitter | FacebookSupport Us: Monthly Donation | One-Time Donation | SwagSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.