Podcasts about chatgpt enterprise

Good Karma Brands gave every teammate ChatGPT Enterprise on Labor Day. Less than a year later, 65% of the company uses AI daily. In the first episode of our AI Transformations series, presented by Google Cloud, Senior Director of Innovation Ty Bauschek tells Mike Kaput how they did it: the pilot, the training cadence, and the automations already saving teammates 10 to 15 hours a week. It's a candid look at what real, fast, company-wide AI adoption takes: top-down urgency, a culture that rewards experimentation, and a new innovation team turning three-hour tasks into ten-minute ones. Show Notes: Access the show notes and show links here Timestamps: 00:01:00 — Introducing the AI Transformations Series 00:04:11 — Meet Ty Bauschek and Good Karma Brands 00:06:22 — Why AI became an urgent, top-down priority 00:08:23 — The rollout: a 50-person pilot and seven Tuesdays 00:10:17 — The tools: ChatGPT Enterprise, Claude, Codex 00:11:34 — How adoption evolved  00:13:43 — Use-case spotlight 00:18:09 — Driving real adoption, not shallow use 00:20:13 — Hitting 65% daily usage: training & the newsletter 00:22:42 — Building an innovation department & the "Cam" breakthrough 00:25:52 — How the innovation specialist role works day to day 00:29:33 — Deciding where to focus & freeing up partner time 00:32:41 — What's next & Ty's advice for other companies This episode is presented by Google Cloud: Google Cloud is the new way to the cloud, providing AI, infrastructure, developer, data, security, and collaboration tools built for today and tomorrow. Google Cloud offers a powerful, fully integrated and optimized AI stack with its own planet-scale infrastructure, custom-built chips, generative AI models and development platform, as well as AI-powered applications, to help organizations transform. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner. Learn more about Google Cloud here: https://cloud.google.com/ Visit our website Receive our weekly newsletter Join our community: Slack Community LinkedIn Twitter Instagram Facebook YouTube Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in our AI Academy 

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

In this episode of UC Today, host Kristian McCann sits down with Eric Wiggins, Product Marketing Director at Smarsh, to explore why AI capture is becoming the foundation of both compliance and business intelligence in financial services.As generative AI becomes embedded across everything from client communications and portfolio analysis to employee productivity, many firms still lack visibility into how these tools are being used.Throughout the discussion, Wiggins outlines why firms need a unified capture layer that records AI prompts, outputs, metadata, and related communications across platforms such as ChatGPT Enterprise, Microsoft Copilot, and Claude Enterprise.Key discussion points:Why the biggest AI governance gap is the lack of captured evidence—not a lack of AI policies.The record-keeping, supervisory, privacy, and discovery risks firms face when AI interactions are not captured.Why policy and employee training must be supported by comprehensive AI capture to deliver effective governance.How Smarsh creates a unified governance layer across AI platforms and communication channels.How captured AI interactions become a valuable source of business intelligence, helping firms identify adoption trends, workflow improvements, and new opportunities.Why organizations that build AI governance early will be able to innovate faster while maintaining regulatory trust and gaining a competitive advantage.

Hoy en 5 Minutos con Sammy: Samsung despliega ChatGPT Enterprise y Codex a gran escala, China responde a la guerra tecnológica con sanciones a empresas estadounidenses, ByteDance se dispara en mercados privados sin salir a bolsa, Aether AI quiere enseñar causalidad a robots físicos y Toto invierte en materiales para chips de un nanómetro.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

En af Claus' første gerninger efter en større fusion var at etablere et governance board. Ikke for at skabe mere styring eller flere møder, men for at træffe bedre beslutninger. Siden har boardet været en central del af NIRAS' arbejde med at prioritere, afveje og skabe retning på tværs af en kompleks organisation med høj faglig autonomi.Dagens gæst i Dataklubben er Claus Birkholm – CIO i NIRAS og årets CIO i 2025.Foruden governance boardet tager vi fat i et af de varmeste emner på CIO-agendaen lige nu: Copilot, ChatGPT Enterprise eller Claude? Claus deler sine erfaringer med at navigere i et marked, hvor AI-udviklingen går hurtigere end beslutningsprocesserne. For hvordan skaber man både frihed til innovation og kontrol med sikkerhed, økonomi og governance?Vi taler også om NIRAS' næste skridt på AI-rejsen. For personlig produktivitet er én ting. Noget andet er at flytte AI ind i værdikæden gennem agenter og løsninger, der skaber værdi i forretningen og ikke kun hos den enkelte medarbejder.Det blev den sidste episode, inden Dataklubben går på sommerferie – men vi vender selvfølgelig stærkt tilbage efter sommerferien.Du ønskes god lyttelyst & en dejlig sommer ☀️

Send us Fan MailGuest: Ivan Lee, Founder & CEO of DatasaurWe're looking at what happens when AI changes the market faster than the old SaaS playbook can keep up.Ivan Lee, founder and CEO of Datasaur, joins SaaS Backwards to share how his company navigated one of the most dramatic shifts in enterprise AI. Datasaur started as a data annotation platform before ChatGPT changed customer priorities, paused AI roadmaps, and forced the company to rethink its product, GTM strategy, and business model.Ivan explains why out-of-the-box tools like ChatGPT Enterprise and Microsoft Copilot can be useful starting points, but often hit a ceiling for regulated enterprises that need private AI trained on their own data, workflows, and processes.He also shares how Datasaur moved from a traditional SaaS model toward end-to-end AI solutions, what founders can learn from disrupted marketing channels, and why the future of SaaS may depend less on selling software access and more on solving the customer's actual job to be done.Key Takeaways:Why enterprise AI often breaks down when it lacks access to private data and internal workflowsHow ChatGPT disrupted Datasaur's original AI roadmap and customer baseWhy old SaaS GTM channels stopped working in a crowded AI marketHow Datasaur rebuilt around private, secure AI for regulated industriesWhat SaaS founders should measure when marketing “best practices” stop producing results---Stalled pipeline? Lost deals? Diagnose your GTM gaps with a free, actionable checkup. 

How much revenue is lost because the systems behind pricing, quoting, billing, and finance still do not talk to each other properly? In today's episode, I'm joined by Tina Kung, CTO and Co-Founder of Nue, the quote-to-revenue platform helping AI and SaaS companies rethink how they sell, bill, and grow. Tina brings more than two decades of experience across enterprise software, CPQ, billing, and revenue operations, with previous roles at Oracle, Zuora, SteelBrick, and Salesforce. Tina shares the story behind Nue and why she saw a growing gap between the systems that handle selling and the systems that manage revenue. As SaaS companies move from traditional subscriptions into usage-based pricing, credit burn-down models, product-led growth, partner channels, and enterprise sales, the old way of stitching together tools with manual work and spreadsheets starts to break down. We discuss how AI is changing go-to-market operations and why transaction-level intelligence matters. Tina explains how Nue connects quoting, billing, usage, and revenue data into a single system, then applies AI so teams can understand what is happening, spot opportunities, and take action faster. One of the standout stories is OpenAI, which rolled out Nue in just eight weeks to support the rapid growth of its ChatGPT Enterprise business. Tina shares what that process revealed about the speed of modern AI companies and why flexible revenue infrastructure is now a serious advantage. We also talk about the rise of agentic AI in revenue operations, from creating quotes and orders to handling subscription changes and surfacing upsell opportunities. As the SaaS model comes under pressure from AI, Tina offers a practical view of what needs to change behind the scenes for companies to stay competitive. If SaaS is entering a new chapter, are your revenue systems ready for how customers now buy, use, and pay for software?  

On this week's Good Morning Hospitality, A Skift Podcast: Hotels Edition, Sarah Dandashy and Steve Turk break down Hyatt's rollout of ChatGPT Enterprise across the company and what it signals about AI moving from experimentation to real operational impact in hospitality. They also explore rising travel costs tied to the upcoming World Cup, where higher prices for tickets, hotels, and transportation are starting to squeeze travelers, the rise of fossil fuel-free hotels across the industry and whether that model can scale, and BWH Hotels' new outdoor brand tapping into demand for glamping and experiential stays. This episode is brought to you by ⁠⁠⁠⁠Vrbo!⁠⁠⁠⁠ Learn how you can earn ⁠⁠⁠OneKeyCash⁠⁠⁠ today. Connect with Skift LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/skift/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ WhatsApp: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://whatsapp.com/channel/0029VaAL375LikgIXmNPYQ0L/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://facebook.com/skiftnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/skiftnews/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Threads: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.threads.net/@skiftnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Bluesky: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bsky.app/profile/skiftnews.bsky.social⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/skift⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Subscribe to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@SkiftNews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and never miss an update from the travel industry.

On this week's Good Morning Hospitality, A Skift Podcast: Hotels Edition, Sarah Dandashy and Steve Turk break down Hyatt's rollout of ChatGPT Enterprise across the company and what it signals about AI moving from experimentation to real operational impact in hospitality. They also explore rising travel costs tied to the upcoming World Cup, where higher prices for tickets, hotels, and transportation are starting to squeeze travelers, the rise of fossil fuel-free hotels across the industry and whether that model can scale, and BWH Hotels' new outdoor brand tapping into demand for glamping and experiential stays. This episode is brought to you by ⁠⁠⁠⁠Vrbo!⁠⁠⁠⁠ Learn how you can earn ⁠⁠⁠OneKeyCash⁠⁠⁠ today. Connect with Skift LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/skift/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ WhatsApp: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://whatsapp.com/channel/0029VaAL375LikgIXmNPYQ0L/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://facebook.com/skiftnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/skiftnews/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Threads: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.threads.net/@skiftnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Bluesky: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bsky.app/profile/skiftnews.bsky.social⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/skift⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Subscribe to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@SkiftNews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and never miss an update from the travel industry.

Hyatt is rolling out ChatGPT Enterprise across the company, American Airlines is shutting down merger speculation with United, and Google is adding new tools to keep travelers inside its ecosystem longer. On today's Skift Daily Briefing, Sarah Dandashy breaks down why Hyatt is treating AI like infrastructure, what American's response says about airline consolidation pressure, and how Google is quietly strengthening its role in the booking journey. This episode is presented by Lodgify! Articles Referenced:Honorable Mention: @AskAConcierge on IGHyatt Rolls Out ChatGPT Enterprise Across the CompanyAmerican Airlines Says It's Not Interested in a United MergerGoogle Adds Hotel Price Tracking for Individual Properties Connect with SkiftLinkedIn: https://www.linkedin.com/company/skift/WhatsApp: https://whatsapp.com/channel/0029VaAL375LikgIXmNPYQ0L/Facebook: https://facebook.com/skiftnewsInstagram: https://www.instagram.com/skiftnews/Threads: https://www.threads.net/@skiftnewsBluesky: https://bsky.app/profile/skiftnews.bsky.socialX: https://twitter.com/skift Subscribe to @SkiftNews and never miss an update from the travel industry.

In this episode, Jack Cochran sits down with Darlene Volas, a senior solutions engineering executive, to explore what it truly means to be an AI-enabled SE in 2025 and beyond. The conversation moves well past basic ChatGPT usage to examine sophisticated operational workflows, custom automation tools, and practical implementation strategies that enhance both efficiency and quality of work.    This episode was recorded during Presales Collective's 2026 AI-Powered Presales Summit on March 19th, 2026. Pro and Pro+ members can view all of the recorded sessions on-demand in the PSC Knowledge Hub: https://www.presalescollective.com/knowledgehub    Follow Us Connect with Jack Cochran: https://www.linkedin.com/in/jackcochran/  Connect with Matthe James: https://www.linkedin.com/in/matthewyoungjames/  Connect with Darlene Volas: https://www.linkedin.com/in/darlenevolas/  Links and Resources Mentioned Join Presales Collective Slack: https://www.presalescollective.com/slack  Sol/Con 2026 (Chicago, August 2026): https://www.presalescollective.com/solcon-2026  Presales Collective Podcast: https://www.presalescollective.com/podcast  Perplexity: https://www.perplexity.ai/  Claude by Anthropic: https://www.anthropic.com/claude  Cursor AI coding tool: https://cursor.sh/  GitHub Copilot: https://github.com/features/copilot  Gong conversation intelligence: https://www.gong.io/  ChatGPT Enterprise: https://openai.com/enterprise  Obsidian note-taking: https://obsidian.md/  Firebolt database: https://www.firebolt.io/  Key Topics Covered Personal AI Usage Evolution: Moving Beyond Google Replacement to Creative Applications Three Buckets of AI for SE Leaders: Operations, Team Workflows, and Technical Implementation Daily Meeting Preparation Automation and Custom-Built AI Applications Operationalizing SE Teams with Repeatable AI Workflows Quality vs. Efficiency Trade-off: Better Preparation Rather Than Less Time Building Technical Credibility Through Hands-On AI Coding The "One More Thing" Problem and Where Human Expertise Remains Essential Data Security, Governance, and Vendor Considerations for AI Tools Why AI Won't Replace SEs: The Irreplaceable Human Element Hiring AI-Native SEs: What to Look For Beyond Basic Tool Awareness Timestamps 00:00 Welcome 02:41 How AI conversations have evolved 06:30 Three buckets of AI usage 12:40 Efficiency versus quality improvements 18:40 Building credibility through AI coding 21:07 The one more thing problem 30:59 Why AI won't replace SEs 36:45 Q&A session 39:20 Closing remarks

Staff in the upper chamber of Congress now have the go-ahead to use Senate data with three popular generative AI chatbots thanks to approval from an office that oversees the legislative body's administrative operations. A recent notice from the Senate Sergeant at Arms' chief information officer announced the approvals for Microsoft's Copilot, Google's Gemini, and OpenAI's ChatGPT, expanding on previous policies. That memo was previously reported by the New York Times and independently obtained by FedScoop. According to the document, Copilot is integrated into the Senate's Microsoft 365 environment already, and more information about licenses for Gemini Chat and ChatGPT Enterprise will be coming within the next 30 days. Each Senate employee will be able to get one license for either Gemini or ChatGPT at no cost. Approval of the tools comes as entities across the federal government — including Congress, executive agencies, and the federal judiciary — have been navigating their own use of the growing technology to reduce administrative toil and assist staff. The Senate, for its part, previously allowed ChatGPT, Google Bard, and Microsoft's Bing AI chat in 2023 at “moderate” risk levels, but they were only for research and evaluation or use with non-sensitive data. The new approvals are less restrictive on the type of data that can be ingested, opening the door to more widespread use. The architect of the Department of Veterans Affairs' artificial intelligence program and digital modernization strategy is leaving the agency after nearly nine years. Charles Worthington, the VA's chief AI officer and CTO, said in a LinkedIn post Thursday that “the time is right” for him to step down from his posts. A Harvard grad, Worthington joined the federal government in 2013 as a Presidential Innovation Fellow. He parlayed that experience into a role as senior advisor to the federal CTO, where he co-created the U.S. Digital Service following the disastrous rollout of HealthCare.gov. After nearly three years with USDS, including as the White House tech office's acting deputy administrator, Worthington moved on to the VA in 2017. In addition to leading the agency's digital modernization work, he also supported its adoption of commercial cloud infrastructure, oversaw the creation of vets.gov, rebuilt va.gov and launched VA Notify, per a congressional bio and his LinkedIn profile. In addition to boosting digital services for veterans, Worthington worked in recent years to spur AI adoption across the agency. Under his watch, the VA emerged as one of the most prolific AI users in the federal government, with an inventory that's now 367 use cases strong. Included in that tally is the agency's VA GPT chatbot.Worthington, who also served on the Technology Modernization Fund board for four years, didn't reveal in his LinkedIn post where he's headed next. But he said his time with the VA “has been the most important work” of his career. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

Tashfeen Mahmud, senior technical writer at Samsung Research in Canada explains why curiosity is your best defense against technical aversion, and how to prepare for a future where technical writers are primarily AI trainers. 'Adapting to AI isn't like learning to cook from scratch. It's like walking into a kitchen that already knows how to cook: it just needs a human to guide it through the process. Your new role is not to execute every step, but to orchestrate an AI that already possesses the technical capability.' '[...]that takes you to decide which AI solution should you even use? If you're a large company, it's likely you will want to build your own solution or you'll get into a very expensive, almost exclusive contract with some AI provider, let's say on ChatGPT Enterprise or something like that. But if you are a small team, then that means you will probably gravitate towards a hosted solution, like a lower tier chatGPT account or something like that, or Claude or something else. Or if you're kind of picky about security and control, you will probably try hosting your own smaller open source model and training that, basically getting it to be workable for your purposes.'

Like 99% of companies are pushing AI.

December 9, 2025: Today's episode brings together the biggest shifts shaping work right now: a global Gen Z unemployment crisis pushing the UK into a $965M skills investment, Amazon's surprising move to position AI agents as "teammates," Jamie Dimon's latest prediction on how AI will reshape jobs and society, new research showing young professionals falling behind in remote roles, fresh data revealing that ChatGPT Enterprise is saving employees nearly an hour a day, and Apple's market boost as investors grow tired of AI hype. These stories together reveal where work is breaking, where it's evolving, and what leaders need to pay attention to in order to stay future-ready.

Today's guests are Matt Berseth, Co-founder and CIO at NLP Logix, and Russell Dixon, Strategic Advisor at NLP Logix. NLP Logix is a fast-growing AI services firm based in Florida that serves both the public and private sectors. Berseth and Dixon join Emerj Editorial Director Matthew DeMello to discuss how enterprise leaders can successfully deploy AI collaboration tools like ChatGPT Enterprise and Microsoft Copilot, set the right foundations for adoption, and measure ROI. They also share practical takeaways on identifying high-value use cases, tracking meaningful usage and productivity metrics, creating feedback loops to share best practices, and embedding AI tools into workflows to deliver sustained business impact. This episode is sponsored by NLP Logix. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast!

Breaking: Google just released Gemini Enterprise.

Greg Leonardo is a Principal Cloud Architect, Certified Azure Solution Architect Expert, and Microsoft Azure MVP with over two decades of experience driving high-impact cloud transformations for global enterprises. Greg's work sits at the crossroads of architecture, innovation, and mentorship, where he crafts scalable, cost-efficient, and future-ready solutions that align technology with business strategy. He's a recognized authority in Azure-native architecture, FinOps optimization, and AI integration, known for delivering measurable results—from reducing cloud spend to accelerating DevOps agility through Terraform and infrastructure as code. His leadership extends beyond technical execution, as he actively cultivates cloud talent and fosters a culture of continuous improvement. A former Gulf War veteran, Greg brings discipline, resilience, and strategic foresight to every initiative — whether building global cloud ecosystems or leading high-performance engineering teams. He's also a passionate advocate for the cloud community, sharing insights daily through technical writing and open mentorship.   Topics of Discussion: [5:46] Greg discusses his approach to AI, emphasizing responsible AI and the importance of understanding its limitations. [8:12] AI's journey through the Hype Cycle. [11:09] Greg introduces the concept of AI as “virtual employees.” [16:44] Greg talks about how he uses both Microsoft 365 Copilot and ChatGPT Enterprise to compare their capabilities. [18:36] How Greg tests and compares AI tools. [20:21] Comparing AI to previous search and research methods. [23:31] Improving AI results through better prompts. [26:17] The agent framework, sharing, and limitations of AI agents. [36:47] AI's ability to generate architectural diagrams. [41:49] Exploring autonomous coding agents. [41:45] Why we aren't quite ready for the “fire and forget” side. [43:08] Struggling with the memory behind chat. [44:02] Closing thoughts — what can we expect in the future, and what are more practical applications of AI?   Mentioned in this Episode: Clear Measure Way Architect Forum Software Engineer Forum Gregory Leonardo LinkedIn Greg Leonardo Website Ep 326 with Greg Leonardo: The Latest in Azure Ep 282 with Greg Leonardo: Optimizing Cloud Budgets   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Although there were no huge LLM updates this week, the big AI companies were still making moves. ↳ Google avoided an AI breakup. ↳ The world's most prominent AI players met with U.S. President Trump. ↳ Apple had to get AI help from its biggest competitor. ↳ Anthropic suffered a $1.5 billion lawsuit loss. And that's barely the beginning of this week's AI news that mattered. Don't waste hours a day trying to keep up or miss an update that impacts your work. Tune in now!Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI AI-Powered Job Board AnnouncementOpenAI ChatGPT Certification Launch DetailsAtlassian Acquires Browser Company for $610MAI Agentic Browsers Market Competition UpdateOpenAI Research on LLM Hallucinations ExplainedApple Integrates Google Gemini in SiriApple-Google AI Partnership for World KnowledgeOpenAI Broadcom Partnership for AI ChipsWhite House AI Execs Meeting with TrumpMajor AI Industry Data Center InvestmentsWarner Bros Sues Midjourney Over CopyrightAnthropic $1.5B Author Copyright SettlementGoogle Wins DOJ Search Monopoly Court CaseAI Image Generator Ideogram Launches StylesClaude Rolls Out Chat Memory for UsersTimestamps:00:00 OpenAI Launches AI Job Platform03:43 AI Skills Boost Salaries, New Platform07:59 Atlassian Acquires The Browser Company12:54 AI Models and Guesswork Issues15:08 AI Hallucinations vs. Uncertainty17:49 Apple-Google AI Integration Unveiled22:07 OpenAI Pursues Custom AI Chips28:59 "Warner Bros. Sues Midjourney"32:38 Anthropic Settles Copyright Lawsuit35:04 Google Avoids Chrome, Android Sale37:47 AI News: Rumors and ReleasesKeywords:OpenAI, AI news, Google, Gemini, Apple, Siri upgrade, large language models, AI hallucinations, AI job board, LinkedIn competitor, AI certification, ChatGPT, ChatGPT Enterprise, prompt engineering, Walmart AI training, Microsoft, AI salary premium, multimodal learning, NotebookLM, Perplexity Comet browser, AI agentic browser, Atlassian, The Browser Company, DIA browser, AI-powered browsing, enterprise AI, Anthropic, AI copyright lawsuit, Warner Brothers Discovery, Midjourney, Disney, Universal, AI intellectual property, image generation AI, AI model training data, Broadcom, AI chips, NVIDIA alternative, custom AI chip, data centers, US AI investment, Mark Zuckerberg, Meta, Apple manufacturing, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

In this episode, Jacob sits down with Peter Deng, General Partner at Felicis and former Product Leader at OpenAI, Facebook, and Uber. Peter shares his insider perspective on building ChatGPT Enterprise in just seven weeks and leading voice mode development at OpenAI. The conversation covers everything from why traditional SaaS pricing models are broken for AI products to how evals became the new product specs, the "AI under your fingernails" test for founding teams, and why current agents are massively overhyped.They also explore how consumer AI will fragment across multiple winners rather than consolidate into a single super app, the coming integration between ChatGPT and apps like Uber, and why voice AI will unlock entirely new categories of applications. Plus, insights on the changing dynamics between foundation models and startups, and what it really takes to build defensible AI companies. It's a comprehensive look at AI product strategy from someone who's been at the center of the industry's biggest breakthroughs. (0:00) Intro(1:17) AI Business Models and Pricing Strategies(7:48) Product Development in AI Companies(18:36) The Role of Product Managers in AI(23:06) Voice Interaction and AI(26:43) AI in Education(30:39) Consumer and Enterprise Adoption of AI(33:36) The Impact of AI on Salaries and HR(40:37) The Role of Unique Data in AI Development(49:03) Challenges and Strategies for AI Companies(52:58) The Future of AI and Its Impact on Society(57:31) Reflections on OpenAI(58:38) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint

An iPhone survives a 2,600-foot fall, sparking debate on durability and user habits between Chuck Joiner, David Ginsburg, Eric Bolden, Brian Flanigan-Arthurs, Marty Jencius, Web Bixby, Jim Rea, and Jeff Gamet.  A Texas startup launches a telescope-hosting data center, enabling astronomers to control gear remotely under pristine skies. Meanwhile, OpenAI stirs controversy by offering ChatGPT Enterprise to government workers for just $1, and AOL finally ends its dial-up service, marking the close of a digital era.  Today's MacVoices is supported by Insta360 and their new GO Ultra, the tiny 4K camera that goes everywhere with you. Visit store.Insta360.com and use the come “MacVoices” for a free set of Sticky Tabs. Show Notes: Chapters: [0:00] iPhone falls from plane and survives[2:28] Past stories of dropped phones[4:47] Debate on cases, lanyards, and durability[5:36] Telescope hosting data center in Texas[7:26] Renting vs. hosting telescopes[8:39] OpenAI offers ChatGPT Enterprise for $1[10:32] Government AI adoption strategies[12:18] AOL finally ends dial-up service[15:35] Reflections on modems, faxes, and internet history[19:17] Reminiscing about AOL, Prodigy, Earthlink, and NetZero[23:38] Vintage modems and retro computing memories Links: AirDrop IRL: iPhone 16 Pro falls from plane and keeps filminghttps://9to5mac.com/2025/08/08/iphone-16-pro-falls-from-airplane-keeps-recording/ This Texas startup built a data center for the night sky with 400 telescopes https://www.fastcompany.com/91377334/this-texas-startup-built-a-data-center-for-the-night-sky-with-400-telescopes OpenAI is giving ChatGPT Enterprise to the executive branch workforce for $1https://www.engadget.com/ai/openai-is-giving-chatgpt-enterprise-to-the-executive-branch-workforce-for-1-165812036.html You had mail: AOL finally discontinues dial-up Internet service https://appleinsider.com/articles/25/08/09/you-had-mail-aol-finally-discontinues-dial-up-internet-service Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Eric Bolden is into macOS, plants, sci-fi, food, and is a rural internet supporter. You can connect with him on Twitter, by email at embolden@mac.com, on Mastodon at @eabolden@techhub.social, on his blog, Trending At Work, and as co-host on The Vision ProFiles podcast. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Jeff Gamet is a technology blogger, podcaster, author, and public speaker. Previously, he was The Mac Observer's Managing Editor, and the TextExpander Evangelist for Smile. He has presented at Macworld Expo, RSA Conference, several WordCamp events, along with many other conferences. You can find him on several podcasts such as The Mac Show, The Big Show, MacVoices, Mac OS Ken, This Week in iOS, and more. Jeff is easy to find on social media as @jgamet on Twitter and Instagram, jeffgamet on LinkedIn., @jgamet@mastodon.social on Mastodon, and on his YouTube Channel at YouTube.com/jgamet. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession ‘firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon.   Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

An iPhone survives a 2,600-foot fall, sparking debate on durability and user habits between Chuck Joiner, David Ginsburg, Eric Bolden, Brian Flanigan-Arthurs, Marty Jencius, Web Bixby, Jim Rea, and Jeff Gamet.  A Texas startup launches a telescope-hosting data center, enabling astronomers to control gear remotely under pristine skies. Meanwhile, OpenAI stirs controversy by offering ChatGPT Enterprise to government workers for just $1, and AOL finally ends its dial-up service, marking the close of a digital era.  Today's MacVoices is supported by Insta360 and their new GO Ultra, the tiny 4K camera that goes everywhere with you. Visit store.Insta360.com and use the come “MacVoices” for a free set of Sticky Tabs. Show Notes: Chapters: [0:00] iPhone falls from plane and survives [2:28] Past stories of dropped phones [4:47] Debate on cases, lanyards, and durability [5:36] Telescope hosting data center in Texas [7:26] Renting vs. hosting telescopes [8:39] OpenAI offers ChatGPT Enterprise for $1 [10:32] Government AI adoption strategies [12:18] AOL finally ends dial-up service [15:35] Reflections on modems, faxes, and internet history [19:17] Reminiscing about AOL, Prodigy, Earthlink, and NetZero [23:38] Vintage modems and retro computing memories Links: AirDrop IRL: iPhone 16 Pro falls from plane and keeps filming https://9to5mac.com/2025/08/08/iphone-16-pro-falls-from-airplane-keeps-recording/ This Texas startup built a data center for the night sky with 400 telescopes  https://www.fastcompany.com/91377334/this-texas-startup-built-a-data-center-for-the-night-sky-with-400-telescopes OpenAI is giving ChatGPT Enterprise to the executive branch workforce for $1 https://www.engadget.com/ai/openai-is-giving-chatgpt-enterprise-to-the-executive-branch-workforce-for-1-165812036.html You had mail: AOL finally discontinues dial-up Internet service  https://appleinsider.com/articles/25/08/09/you-had-mail-aol-finally-discontinues-dial-up-internet-service Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Eric Bolden is into macOS, plants, sci-fi, food, and is a rural internet supporter. You can connect with him on Twitter, by email at embolden@mac.com, on Mastodon at @eabolden@techhub.social, on his blog, Trending At Work, and as co-host on The Vision ProFiles podcast. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Jeff Gamet is a technology blogger, podcaster, author, and public speaker. Previously, he was The Mac Observer's Managing Editor, and the TextExpander Evangelist for Smile. He has presented at Macworld Expo, RSA Conference, several WordCamp events, along with many other conferences. You can find him on several podcasts such as The Mac Show, The Big Show, MacVoices, Mac OS Ken, This Week in iOS, and more. Jeff is easy to find on social media as @jgamet on Twitter and Instagram, jeffgamet on LinkedIn., @jgamet@mastodon.social on Mastodon, and on his YouTube Channel at YouTube.com/jgamet. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession ‘firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon.   Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

welcome to wall-e's tech briefing for monday, august 25th! dive into today's top tech stories: meta & midjourney partnership: meta collaborates with midjourney to enhance ai image and video generation capabilities, integrating advanced tech into meta's future models to outpace rivals like openai and google. apple's new chatgpt options: apple announces customizable configuration options for chatgpt, coming in september, enabling businesses to manage ai provider interactions and align with private cloud strategies. u.s. government's stake in intel: plans for a 10% equity stake in intel as part of a strategic move to support the company's restructuring and compete with industry leaders like nvidia. nvidia's h20 chips production halt: nvidia halts production of its h20 ai chips due to security concerns raised by beijing, impacting sales to the chinese market, while asserting the security of its products. stay tuned for tomorrow's tech updates!

Ian Krietzberg joins guest host Julia Ioffe to discuss Sam Altman's latest gambit: offering ChatGPT Enterprise to U.S. government agencies for next to nothing, in hopes of building muscle memory inside the government and promoting the widespread adoption of A.I. in day-to-day operations. Yet, as adoption grows, so do the questions and concerns—about security, reliability, and the costs of running energy-hungry systems prone to unpredictable errors. 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

The General Services Administration has been on a roll lately, negotiating what it calls OneGov agreements with some of the federal government's biggest IT vendors. On Thursday, GSA announced it has negotiated a governmentwide purchasing agreement with Amazon Web Services that could save agencies up to $1 billion through credits for AWS services. The deal is the latest in a flurry of OneGov agreements GSA has initiated under the Trump administration to consolidate and centralize IT purchasing at scale and unlock greater, consistent savings for civilian agencies, rather than agencies negotiating one-off contracts with vendors themselves. As part of the governmentwide package, AWS has come to the table offering direct incentive credits that could total up to $1 billion in value for cloud services, modernization support and training. The deal will run through Dec. 31, 2028. In addition to streamlining federal IT procurement by working as a single, unified federal entity, GSA's OneGov initiative also aims to work directly with technology developers themselves, rather than intermediaries such as value-added resellers. As such, GSA touts the potential for additional savings by contracting directly with the cloud giant for its services. That deal comes just a day after GSA announced a similar one with OpenAI that will offer its ChatGPT tool to federal agencies for just $1. It marks the artificial intelligence firm's latest effort to expand use of its generative AI chatbot across the federal government. Like the AWS deal, GSA said the agreement with OpenAI supports the White House's AI Action Plan, which encourages widespread adoption of AI in the federal government. Through the partnership, OpenAI's ChatGPT Enterprise product can be purchased by federal agencies for $1 per agency for one year. GSA called this a “deeply discounted rate.” Commenting on the deal, OpenAI CEO Sam Altman said in a statement: “One of the best ways to make sure AI works for everyone is to put it in the hands of the people serving the country.” The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

Over 2 million civilian workers at dozens of agencies will have access for at least one year. Learn more about your ad choices. Visit podcastchoices.com/adchoices

This episode covers a massive amount of AI-related news and research, especially developments over the past week, including ChatGPT's new "study mode," major platform announcements from Google, Microsoft, and OpenAI, generative video and music tools, and the implications of AI on jobs and education. The episode also highlights a new Stanford GenAI for Education hub and discusses current AI policy and access initiatives globally. News   ChatGPT Study Mode: https://openai.com/index/chatgpt-study-mode/  Simon Willison info on the system prompt for Study Mode: https://simonwillison.net/2025/Jul/29/openai-introducing-study-mode/  Dr Philippa Hardman's LinkedIn post on Study Mode: https://www.linkedin.com/posts/dr-philippa-hardman-057851120_as-a-member-of-openais-educator-advisor-ugcPost-7356234831929696256-OF6k   Google announced “Guided Learning” mode for Gemini https://blog.google/products/gemini/google-ai-pro-students-learning/    Open models by OpenAI https://openai.com/open-models/    Google released Gemini Storybooks https://gemini.google/overview/storybook/   ElevenLabs dropped a new multi-lingual music generation model https://elevenlabs.io/music    OpenAI giving ChatGPT Enterprise to every US Federal Government department for $1 a year https://openai.com/index/providing-chatgpt-to-the-entire-us-federal-workforce/   Microsoft Copilot released for 13+ students  https://techcommunity.microsoft.com/blog/EducationBlog/microsoft-365-copilot-chat-for-students-13/4412957    18 months. 12,000 questions. A whole lot of anxiety. What I learned from reading students' ChatGPT logs https://www.theguardian.com/technology/2025/jul/27/it-wants-users-hooked-and-jonesing-for-their-next-fix-are-young-people-becoming-too-reliant-on-ai  The Presidential AI Challenge https://orise.orau.gov/ai-challenge/    Research GenAI for Education Hub at Stanford University https://scale.stanford.edu/genai/repository  Working with AI: Measuring the Occupational Implications of Generative AI https://arxiv.org/abs/2507.07935  Prompting Science Report 3: I'll pay you or I'll kill you - but will you care? https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5375404 

Ceo Sam Altman van OpenAI heeft een overeenkomst gesloten met de Amerikaanse General Services Administration (GSA) voor het gebruik van zijn chatbot binnen de overheid. Voor slechts 1 dollar mogen federale instanties die zijn opgenomen in de deal ChatGPT Enterprise gaan gebruiken, een aparte dienst speciaal voor organisaties. Rosanne Peters vertelt erover in deze Tech Update. De overeenkomst komt een dag nadat OpenAI samen met concurrenten Google en Anthropic op de lijst staan met goedgekeurde AI-leveranciers voor de Amerikaanse overheid. President Trump gaf enkele weken geleden al aan dat hij meer AI-tools binnen de overheid wil integreren. Dat gebeurt via de Multiple Award Schedule, een nieuw federaal aanbestedingsplatform. Verder in deze Tech Update: Google komt met nieuwe tool voor chatbot Gemini die als tutor moet helpen met studeren Odido biedt klanten in Noord-Holland en Rotterdam een vergoeding aan na storing See omnystudio.com/listener for privacy information.

A daily Chronicle of AI Innovations in August 07th 2025Hello AI Unraveled Listeners,In today's AI Daily News,

In this episode of The ASHHRA Podcast, co-hosts Bo Brabo and Luke Carignan welcome back Alyson Parker Gordon, now serving as Vice President of HR Shared Services at AdventHealth. Alyson brings fresh perspective from her new role, leading enterprise-level change across shared services, employee relations, talent, and the implementation of Workday HCM.This conversation dives into the heart of modern HR transformation—where people, process, and technology converge to elevate the employee experience and optimize operational efficiency.

Subscribe at ⁠www.thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.In episode 4 of This New Way, Aydin sits down with Andrew Waitman, CEO of Assent, to explore how a billion-dollar B2B SaaS company is transforming operations, product development, and team productivity with AI. Andrew shares how Assent went from under $1M to nearly $200M ARR, became one of the earliest adopters of GitHub Copilot and ChatGPT Enterprise, and how they now embed AI-driven OKRs across every team.You'll hear real use cases: from summarizing messy trip reports, generating synthetic bills of materials for secure testing, and accelerating supplier document reviews — to measuring impact on productivity and profitability. Andrew also offers actionable insights on how to drive AI adoption across teams, how CEOs should personally lead the AI charge, and which tools he uses daily to stay ahead.You'll walk away knowing how to start small, scale fast, and turn AI into a measurable force multiplier across your org.⁠⁠Click here⁠⁠ to check out the AI-generated timestamps, episode summary and transcript.. . .Like this episode? Be sure to leave a ⭐️⭐️⭐️⭐️⭐️ review and share the episode with someone who will benefit from listening.. . .TIMESTAMPS:00:35 Andrew's background and Assent's growth journey02:37 The scale: 18,000 suppliers, 200 compliance topics05:07 The post-ChatGPT transformation and Vista Equity OKRs06:09 Early adoption of GitHub Copilot & ChatGPT Enterprise08:51 Trip report improvements using AI synthesis09:35 Generating synthetic bills of materials for safe testing12:26 Where AI drives efficiency: entity resolution, part matching, document validation13:12 Measuring AI's impact: productivity, quality, and profitability17:32 Expanding customer success capacity without adding headcount20:37 How to drive company-wide AI adoption (hackathons, Slack, evangelists)24:10 Andrew's personal AI workflows & deep research routinesTOOLS & RESOURCES MENTIONED:AI Tools & PlatformsGitHub Copilot (Microsoft) → adopted early for engineeringChatGPT (OpenAI, including Enterprise license) → used across teams for synthesis, rewriting, summarizationPerplexity AI (Pro) → used for deep research reportsInternal AI Use Cases & SystemsSynthetic bills of materials → generated using AI to safely test software without exposing sensitive customer dataAutomated document review → handling millions of supplier documents for complianceEntity resolution → using AI to match the right supplier or part across massive datasetsPart resolution & document validation → automating complex checks in the supply chainCompany-Wide AI Adoption Tools & MethodsOKRs (Objectives & Key Results) → embedded AI goals at company, team, and functional levelsAI hackathons → internal competitions to inspire creative use casesSlack channels → for sharing, evangelizing, and discussing AI applications internallyPersonal CEO Tools & WorkflowsPerplexity deep research → running 12–15 deep research reports per dayAI summarization & rewriting → e.g., turning multi-page trip reports into professional one-page summaries

Stay in control as GenAI adoption accelerates across your organization using Data Security Posture Management for AI in Microsoft Purview. With built-in visibility into how AI apps and agents interact with sensitive data—whether inside Microsoft 365 or across unmanaged consumer tools—you can detect risks early, take decisive action, and enforce the right protections without slowing innovation. Monitor usage trends, investigate prompts and responses, and respond to potential data oversharing or policy violations in real time. From compliance-ready audit logs to adaptive data protection, you'll have the insights and tools to keep data secure as AI becomes a part of everyday work. Shilpa Ranganathan, Microsoft Purview Principal Group PM, shares how to balance GenAI innovation with enterprise-grade data governance and security. ► QUICK LINKS: 00:00 - GenAI app security, governance, & compliance 01:30 - Take Action with DSPM for AI 02:08 - Activity logging 02:32 - Control beyond Microsoft services 03:09 - Use DSPM for AI to monitor data risk 05:06 - ChatGPT Enterprise 05:36 - Set AI Agent guardrails using DSPM for AI 06:44 - Data oversharing 08:30 - Audit logs 09:19 - Wrap up ► Link References Check out https://aka.ms/SecureGovernAI ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft.  • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics  

In this dynamic clip, thought leaders Morgan Debaun, Troy Millings, Rashad Bilal, and Ian Dunlap break down the monumental impact of AI on today's workforce and industries. Morgan Debaun doesn't sugarcoat the reality — AI is rapidly replacing traditional roles, and it's time to adapt or risk getting left behind. The conversation covers which jobs and industries are most at risk (think graphic design, video editing, project coordinators), and which ones offer new opportunities in the age of AI, including cybersecurity and roles for critical thinkers and solopreneurs.Morgan shares practical examples from her own company, Blavity, illustrating how AI tools have increased productivity and accountability. She highlights how their custom AI-powered writing tool has allowed writers to produce higher quality articles, faster, and why staying up to speed with AI tools is now essential for all professionals.If you want to future-proof your career or business, this clip is a must-watch. The panel dives into specific AI tools transforming workflows — including Google Gemini, ChatGPT Enterprise, Salesforce/Slack integrations, Asana, and the latest AI features in Canva.Get ahead of the curve: discover where AI is creating new industries and how you can leverage these tools to become a more strategic, in-demand professional.*Hashtags:* #AI #ArtificialIntelligence #FutureOfWork #CareerAdvice #MorganDebaun #TechTalk #Solopreneur #Productivity #AItools #CareerDevelopment #MediaInnovationOur Sponsors:* Check out NerdWallet: https://www.nerdwallet.comSupport this podcast at — https://redcircle.com/marketmondays/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

BBVA está revolucionando la banca con inteligencia artificial. A través de su competición interna Bot Talent, el banco ha desafiado a sus empleados a idear soluciones innovadoras con ChatGPT Enterprise, y los resultados son realmente transformadores. Vanessa Pombo, compañera de BBVA Creative, presenta los tres proyectos ganadores: una plataforma que potencia la atención al cliente en BBVA Perú, un sistema que agiliza la concesión de créditos a pymes en BBVA México y un detector de ciberfraude en BBVA España. Estos desarrollos demuestran cómo la IA generativa está transformando la operativa bancaria y mejorando la experiencia del usuario.

In this packed episode of Generation AI, hosts Ardis Kadiu and Dr. JC Bonilla break down three major developments shaking up AI in higher education. They analyze California State University's groundbreaking partnership with OpenAI to provide ChatGPT Enterprise to over 500,000 students across 23 campuses. The hosts also dig into DeepSeek's stunning $6 million AI model that's disrupting the market and sparking what some call AI's "Sputnik moment." Finally, they explore OpenAI's latest innovations including Operator and Deep Search, showing how these AI agents are transforming research and automation. This episode offers essential insights for higher education professionals trying to understand how these rapid AI developments will impact their institutions.CSU's Game-Changing OpenAI Partnership (00:01:36)Partnership brings ChatGPT Enterprise to 500,000+ students across 23 campusesCreation of AI Common Hub for centralized tools and trainingFocus on faculty empowerment and workforce development through AIImplementation challenges across a large, distributed systemThe Past Three Weeks in AI (00:13:23)Discussion of recent developments in AI technologyAnalysis of rapid acceleration in AI capabilitiesImpact on higher education and institutional adoptionDeepSeek: AI's Sputnik Moment (00:13:55)Introduction of DeepSeek's new AI model and its capabilitiesAnalysis of the $6 million training cost breakthroughDiscussion of geopolitical implications and US-China AI competitionExplanation of open source model vs. hosted service distinctionsOpenAI's New Agent Technologies (00:25:11)Introduction of OpenAI's scheduled tasks featureAnalysis of Operator: AI-powered browser automationDiscussion of security and trust considerationsReal-world applications in higher educationDeep Search: The Research Revolution (00:34:52)Detailed breakdown of OpenAI's Deep Search capabilitiesComparison with Google's Gemini Deep ResearchReal-world example of ICP research automationCost-benefit analysis of AI research toolsImpact on academic and professional researchLooking Ahead: AI in Higher Education (00:41:11)Discussion of future implications for institutionsIntegration challenges and opportunitiesImportance of AI literacy and trainingUpcoming AI Engaged Summit announcement - - - -Connect With Our Co-Hosts:Ardis Kadiuhttps://www.linkedin.com/in/ardis/https://twitter.com/ardisDr. JC Bonillahttps://www.linkedin.com/in/jcbonilla/https://twitter.com/jbonillxAbout The Enrollify Podcast Network:Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too! Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com. Attend the 2025 Engage Summit! The Engage Summit is the premier conference for forward-thinking leaders and practitioners dedicated to exploring the transformative power of AI in education. Explore the strategies and tools to step into the next generation of student engagement, supercharged by AI. You'll leave ready to deliver the most personalized digital engagement experience every step of the way.Register now to secure your spot in Charlotte, NC, on June 24-25, 2025! Early bird registration ends February 1st -- https://engage.element451.com/register

En este episodio del Blink, Guillermo Vieira e Isabel Pérez del Caño, del equipo de Adopción Global de IA de BBVA, comparten cómo ChatGPT Enterprise está revolucionando el banco. Con más de 3.000 GPTs creados y 1.400 casos de uso identificados, BBVA ha optimizado procesos en áreas como legal, marketing y desarrollo de ‘software', reduciendo tiempos y mejorando la eficiencia. Además, iniciativas como la GPT Store y roles clave como los ‘champions' y ‘wizards' impulsan la adopción global de la IA, garantizando un uso ético y seguro mientras el banco sigue ampliando su alcance.  

Send Everyday AI and Jordan a text messageAnthropic recently announced Claude Enterprise. But, you shouldn't be using it. Yet. We'll tell you the 3 reasons that your company probably shouldn't be using Anthropic Claude.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on Anthropic ClaudeUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Features of Claude Enterprise2. Criticism of Claude Enterprise3. Enterprise AI Adoption ConsiderationsTimestamps:02:00 Daily AI news05:45 What is Claude Enterprise?09:06 Discussing AI training and implementation for enterprises.13:53 Large language models unsuitable for most enterprises.15:06 Rogue users start, later enterprise formalizes use.19:25 Build websites, apps easily with Claude AI.21:05 Claude enables easy, no-code model customization.24:31 Claude missed the mark for enterprise strategy.28:07 OpenAI's limited rollouts vs. Claude's widespread releases.33:43 Claude for enterprise with upcoming GitHub integration.35:20 Microsoft 365 Copilot integration mostly limited to chat.39:27 Claude 35 no longer top chatbot model.42:29 Companies choose a large language model.Keywords:AI implementation, custom pricing, enterprise customers, pricing strategy, transparency, product launch, competition analysis, Microsoft 365 Copilot, GPT-4, ChatGPT Enterprise, Google Gemini, Anthropic Claude, real-time data, large language models, no-code tool, enterprise go-to-market strategy, third-party integrations, Enterprise product, enterprise pricing, release announcement, Everyday AI podcast, AI news, Safe Superintelligence Funding, Michael Dell, AI demand, token capacity, collaboration tools, team control, private beta. 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/

Send Everyday AI and Jordan a text messageIt's the trillion dollar AI question. When will we achieve Artificial General Intelligence? (And what the heck is it, anyway?) We'll give you the 101 on what you need to know, and one secret that could be holding the official discovery back.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AGIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Definition of AI, AGI and ASI2. Evolution of AGI3. Impacts of Advancements in AGI4. Future of AGITimestamps:02:00 When is AGI coming?09:54 Machines performing tasks requiring human intelligence.13:10 Generative AI brings impressive outputs through language.14:04 Generative AI democratizes US AI capabilities; narrow compared.19:00 Correct prompting with PPP course at podpp.com.20:52 Big tech companies openly working toward AGI now.25:37 AGI development inevitable, desirable, surpassing human capabilities.28:16 Pre-2020, experts said AGI was 80 years away.31:25 Criticism of experts in generative AI misunderstandings.33:49 Has AI's definition of AGI changed?37:21 Definition of AGI has evolved over time.40:45 Partnership between Microsoft and OpenAI pivotal.45:21 OpenAI benefits from important Microsoft partnership changes.47:08 Tech companies must focus on AGI development.Keywords:AGI, Artificial General Intelligence, OpenAI, Microsoft, partnership, AI development, AI startup, Anthropic, copyright infringement, Google's Gemini team, Token offering, AI models, USAID, ChatGPT Enterprise, AI pace estimation, AI evolution, Artificial Superintelligence, AI prediction chart, ARK Invest, GPT 3 technology, Traditional AI, Generative AI, AI democratization, AGI benchmark, ChatGPT course, AI startups, Big tech companies, AGI cost reduction, Future of work, Everyday AI podcast. 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/

ICYMI: Later, with Mo'Kelly Presents – A look ‘Beyond the Box Score' with regular guest contributor Jackie Rae; Long Beach Post/WNBA Reporter and host of ‘The Jackie Rae Show,' weighing in on USC unprecedented partnership with CBD company ‘Cookies' and MORE…PLUS – Thoughts on UCLA offering ChatGPT Enterprise accounts AND a look at your weekly horoscope and your Fall sex and love horoscopes - on KFI AM 640…Live everywhere on the iHeartRadio app

From autonomous agents to specialized robotics, AI is transforming supply chain. But next-gen tech requires a next-gen workforce to maximize its potential. In the latest episode of the podcast, the Zero100 team discuss the mechanics of building human-machine teams and a skills profile for the supply chain worker of tomorrow. Featuring: Chief Content Officer Matt Davis and VP Research Lauren Acoba.Reflecting on one year of ChatGPT Enterprise (1:51)AI's swift transition from tool to teammate (3:35)The logic of divvying up tasks on hybrid human-machine teams (5:17)How AI is changing roles and helping employees at Unilever, BMW, and Walgreens (7:16)The risks of letting an AI agent do a supply chain novice's work (9:19)Introducing Andi: the “new-collar” supply chain worker of the future (11:00)Supply chain's most in-demand skills (11:54)How the APAC region and the West stack up on digital skill (14:47)The rise of the product manager and data manager in supply chain (15:43)How to integrate AI into your team and grow AI literacy (19:48)

Send Everyday AI and Jordan a text messageOpenAI just shocked us all with the release of its o1 model, previously codenamed as Strawberry and Q* We break down what's new, 5 things you need to know and more! Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Hanan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Introducing OpenAI's New Model: O1 PreviewO1 Preview: Chain of Thought ReasoningComparison: GPT-4 and O1 Preview PerformanceAnticipated Frequent Language Model UpdatesOpenAI O1: Features, Limitations, and PricingUser Experience Concerns with O1 SeriesBenchmark Performance: O1 Surpassing PhDsThe Current and Future State of AIPractical Testing of Large Language ModelsReal-Time Application of AI ModelsAGI and Chain of Thought in AI EvolutionExclusivity of O1 Preview to ChatGPT AccountsO1 Preview: Shift in AI Approach to Problem-SolvingLive Testing Demonstrations on PodcastRegulation Needs for Safe AI Development.Timestamps:00:00 Everyday AI: Learn generative AI for growth.03:46 Free, Plus, Teams, Enterprise accounts available soon.07:50 GPT tech simplifies skilled tasks with agentic workflow.10:51 OpenAI creates two distinct series for GPT.13:10 Expensive and limited OpenAI's API preview.18:06 MMLU: Multitask language understanding benchmark for AI.21:14 Anthropic raised $4B; OpenAI holds back GPT-4.5.22:40 Corporate revenues mainly from subscriptions and APIs.26:39 Man and dog cross in one trip.29:41 Many correct answers exist, including 153.32:24 Large language models struggle with this question.35:47 Future: Many small companies, fewer traditional jobs.38:34 Q Star impressive, expensive, limited, large model updates.Keywords:OpenAI, o1 series, AGI, Artificial General Intelligence, GPT-4, ChatGPT Plus, ChatGPT Teams, ChatGPT Enterprise, EDU accounts, API access, reasoning-based model, large language models, everydayai.com, numerical code, word count task, world hunger plan, Anthropic, Google, Meta, performance benchmarks, MMLU, subscription costs, message limits, user experience, AI development, AI regulation, real-time tests, agentic processing, code-named Q Star Strawberry, prompt engineering 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/ 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/

Send Everyday AI and Jordan a text messageWin a free year of ChatGPT or other prizes! Find out how. Anthropic just announced Claude Enterprise. But, you shouldn't be using it. Yet. We'll tell you the 3 reasons that your company probably shouldn't be using Anthropic Claude. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on Anthropic ClaudeUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Features of Claude Enterprise2. Criticism of Claude Enterprise3. Enterprise AI Adoption ConsiderationsTimestamps:02:00 Daily AI news05:45 What is Claude Enterprise?09:06 Discussing AI training and implementation for enterprises.13:53 Large language models unsuitable for most enterprises.15:06 Rogue users start, later enterprise formalizes use.19:25 Build websites, apps easily with Claude AI.21:05 Claude enables easy, no-code model customization.24:31 Claude missed the mark for enterprise strategy.28:07 OpenAI's limited rollouts vs. Claude's widespread releases.33:43 Claude for enterprise with upcoming GitHub integration.35:20 Microsoft 365 Copilot integration mostly limited to chat.39:27 Claude 35 no longer top chatbot model.42:29 Companies choose a large language model.Keywords:Scott White, AI implementation, custom pricing, enterprise customers, pricing strategy, transparency, product launch, competition analysis, Microsoft 365 Copilot, GPT-4, ChatGPT Enterprise, Google Gemini, Anthropic Claude, real-time data, large language models, no-code tool, enterprise go-to-market strategy, third-party integrations, Enterprise product, enterprise pricing, release announcement, Everyday AI podcast, AI news, Safe Superintelligence Funding, Michael Dell, AI demand, token capacity, collaboration tools, team control, private beta. 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/

Send Everyday AI and Jordan a text messageWin a free year of ChatGPT or other prizes! Find out how.It's the trillion dollar AI question. When will we achieve Artificial General Intelligence? (And what the heck is it, anyway?) We'll give you the 101 on what you need to know, and one secret that could be holding the official discovery back. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AGIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Definition of AI, AGI and ASI2. Evolution of AGI3. Impacts of Advancements in AGI4. Future of AGITimestamps:02:00 Daily AI news06:15 When is AGI coming?09:54 Machines performing tasks requiring human intelligence.13:10 Generative AI brings impressive outputs through language.14:04 Generative AI democratizes US AI capabilities; narrow compared.19:00 Correct prompting with PPP course at podpp.com.20:52 Big tech companies openly working toward AGI now.25:37 AGI development inevitable, desirable, surpassing human capabilities.28:16 Pre-2020, experts said AGI was 80 years away.31:25 Criticism of experts in generative AI misunderstandings.33:49 Has AI's definition of AGI changed?37:21 Definition of AGI has evolved over time.40:45 Partnership between Microsoft and OpenAI pivotal.45:21 OpenAI benefits from important Microsoft partnership changes.47:08 Tech companies must focus on AGI development.52:37 Future work, business, career with AI impact.Keywords:AGI, Artificial General Intelligence, OpenAI, Microsoft, partnership, AI development, AI startup, Anthropic, copyright infringement, Google's Gemini team, Token offering, AI models, USAID, ChatGPT Enterprise, AI pace estimation, AI evolution, Artificial Superintelligence, AI prediction chart, ARK Invest, GPT 3 technology, Traditional AI, Generative AI, AI democratization, AGI benchmark, ChatGPT course, AI startups, Big tech companies, AGI cost reduction, Future of work, Everyday AI podcast. 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/

As OpenAI looks to make inroads with the federal government, it has struck a deal with the U.S. Agency for International Development as the first agency partner to use its ChatGPT Enterprise platform. Anna Makanju, OpenAI's vice president of global affairs, told FedScoop that USAID plans to use the technology to help reduce administrative burden and “make it easier for new and local organizations” to partner with the agency. Meanwhile, multiple sources told DefenseScoop that Pentagon leadership selected Anduril's Dive-LD autonomous underwater vehicles as part of the second tranche of capabilities to be quickly mass-produced via the high-profile modernization effort known as Replicator. This news marks the first public report of technologies that made the Defense Department's cut for Replicator 1.2 — and it also follows the company's recently revealed plans to launch a new factory in Rhode Island to speed up the manufacturing of these advanced uncrewed platforms. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast on on Apple Podcasts, Soundcloud, Spotify and YouTube.

In this episode, Steve Fretzin and Karl Seelbach discuss:The way you do one thing is the one way you do everything.Building out and being consistent with expectations through SOPs and accountability charts.Setting aside time specifically to work on your business, not just in it.Hiring a coach to remove your blinders. Key Takeaways:Focus on the solutions - if something goes wrong, look at why and see how it can be fixed.Everyone and every firm is a work in progress. The little things that are sometimes forgotten are the things that need the most attention because they will make the biggest results.You don't have to be the one to wear every hat. You don't have to execute on every idea. Delegate what you can't (or don't want to) do.Attorneys are responsible for the work they file with the court. If you utilize AI the same way you would utilize a paralegal or law assistant, you can let the tech work for you."You can't just keep doing the same thing, it's not going to change, and you're going to burn out and end up in a bad spot. You have to hit the brakes and say, ‘Okay, look, I've got to figure out how to solve this.'" —  Karl SeelbachTake the BE THAT LAWYER challenge at Fretzin.com/BTLChallenge! Thank you to our Sponsors!Ready to go from good to GOAT? Attend PIMCOM, the inaugural personal injury mastermind conference Sept 15-17, 2024. Use promo code BeThatLawyer to get $200.00 off at https://www.pimcon.org/ Get Staffed Up: https://getstaffedup.com/bethatlawyer/Lawmatics: https://www.lawmatics.com/bethatlawyer/ Episode References: Traction: https://www.eosworldwide.com/traction-bookeMyth: https://www.emyth.com/Who Not How: https://whonothow.com/ChatGPT Enterprise: https://openai.com/chatgpt/enterprise/Casetext: https://casetext.com/Lexis+ AI: https://www.lexisnexis.com/en-us/products/lexis-plus-ai.pageUnreasonable Hospitality by Will Guidara: https://www.amazon.com/Unreasonable-Hospitality-Remarkable-Giving-People/dp/0593418573Mention Steve's name and get $500 off your first deposition or upload at Skribe: https://skribe.ai/ About Karl Seelbach: Karl Seelbach is a LegalTech founder and seasoned litigation attorney with over 17 years of experience in the courtroom, representing clients in personal injury, business, and employment litigation. He is a skilled advocate and a tenacious fighter who handles cases with precision and an eye toward trial from day one. His adversaries describe him as "skilled" and "whip-smart." But Karl's legal expertise doesn't stop there - he's also the founder of Skribe.ai, a software platform for capturing testimony that's changing the game for attorneys and their clients. Prior to launching his own law firm in 2015, Karl worked as a litigation partner at one of Texas' largest law firms, Winstead PC, where he was mentored by some of the state's top litigators, including former appellate judges and veteran trial lawyers. Karl received his law degree from South Texas College of Law in Houston and his undergraduate degree from Stephen F. Austin State University. In his free time, Karl enjoys spending time with his wife and daughters in Dripping Springs, Texas as a #GirlDad who proudly cheers on his kids in volleyball, basketball, and more!  Connect with Karl Seelbach:  Website: https://skribe.ai/Email: karl@skribe.aiLinkedIn: https://www.linkedin.com/in/kwseelbach/LinkedIn: https://www.linkedin.com/company/skribe-ai/Twitter: https://x.com/KarlSeelbach Connect with Steve Fretzin:LinkedIn: Steve FretzinTwitter: @stevefretzinInstagram: @fretzinsteveFacebook: Fretzin, Inc.Website: Fretzin.comEmail: Steve@Fretzin.comBook: Legal Business Development Isn't Rocket Science and more!YouTube: Steve FretzinCall Steve directly at 847-602-6911 Show notes by Podcastologist Chelsea Taylor-Sturkie Audio production by Turnkey Podcast Productions. You're the expert. Your podcast will prove it. 

Cybercriminals are increasingly utilizing artificial intelligence (AI) for sophisticated attacks and fraud, as discussed in the podcast episode. One notable application of AI by cybercriminals is in phishing attacks, where generative AI tools like ChatGPT are being integrated into spam-generating services. This enables cybercriminals to craft more convincing and personalized phishing emails, heightening the success rate of their attacks. Moreover, AI is being harnessed in deepfake audio scams, allowing scammers to convincingly mimic someone's voice. This technology can be exploited to circumvent identity checks and manipulate AI systems, posing a significant threat to individuals and organizations.The proliferation of AI in cybercrime poses challenges for cybersecurity professionals and organizations. With the capacity to generate realistic content and manipulate information, cybercriminals can execute more sophisticated and targeted attacks, making it increasingly difficult to detect and prevent such threats. As AI technology advances, it is imperative for cybersecurity measures to evolve to effectively counter these emerging threats. Organizations must implement robust security protocols, such as multi-factor authentication and regular vulnerability patching, to defend against AI-powered cyberattacks and protect sensitive data from malicious actors.PwC has taken a significant step by becoming the first reseller of ChatGPT Enterprise through a partnership with OpenAI. This strategic move allows businesses to procure the generative AI service through PwC instead of directly from OpenAI. The primary objective behind this partnership is for PwC to enhance its services to clients interested in leveraging AI to optimize their workloads. PwC already employs custom GPTs for various tasks and views AI as a means to drive increased impact and productivity for their clients. Three things to know today00:00 Cybercriminals' Use of AI for Sophisticated Attacks and Fraud  03:28 Congress passes a privacy law – just not the one you think05:39 The First Reseller of ChatGPT Enterprise Supported by:  https://timezest.com/mspradio/https://skykick.com/mspradio/   All our Sponsors:   https://businessof.tech/sponsors/   Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/ Support the show on Patreon: https://patreon.com/mspradio/ Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessoftech.bsky.social

There's a constant battle happening with cyber security and GenAI. While AI can benefit the evolution of cyber, it also can be a double-edged sword. Glen Pendley, Chief Technology Officer at Tenable, joins us to discuss GenAI's impact on cyber security.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Glen questions on GenAI and cyberUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:01:45 Daily AI news04:45 About Glen and Tenable08:06 Attackers are opportunistic, protect yourself proactively.12:12 Chrome vulnerability CVE-2023 poses significant threat.14:06 AI expedites data mining for cyber threats.20:13 AI tools enhance security features for software.22:14 Keep software updated and limit user access.25:17 Preventative security is crucial, don't overlook basics.29:13 Previewing GPT store launch & daily AI updates.Topics Covered in This Episode:1. Tenable and Its Role in Cybersecurity2. Impact of Generative AI on Cybersecurity3.  Role of Public and Private Sectors in Cybersecurity4. Phishing Attacks and Cyber Hygiene Practices5. Personal Cybersecurity Best PracticesKeywords:OpenAI, ChatGPT Enterprise, Pennsylvania, Amazon, Alexa skills, artificial intelligence, historical figures, custom songs, Rabbit, Rabbit R1, generative AI, cybersecurity, Tenable, vulnerabilities, proactive security measures, public sector, private sector, small businesses, AI devices, deep fake technology, GPT, GPT store, CISA, phishing attacks, ransomware, cyber hygiene, end users, evolving threat landscape. 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/

This Week in Startups is brought to you by… Squarespace. Turn your idea into a new website! Go to Squarespace.com/TWIST for a free trial. When you're ready to launch, use offer code TWIST to save 10% off your first purchase of a website or domain. OpenPhone. Create business phone numbers for you and your team that work through an app on your smartphone or desktop. TWiST listeners can get an extra 20% off any plan for your first 6 months at openphone.com/twist Fitbod. Tired of doing the same workouts at the gym? Fitbod will build you personalized workouts that help you progress with every set. Get 25% off your subscription or try out the app for FREE when you sign up now at fitbod.me/TWIST. * Today's show: Sunny Madra joins Jason to discuss Sunny's All-In Summit experience (1:34), OpenAI's race to beat Google in launching the first multimodal LLM (9:07), whether generative AI needs a UI shift (33:00), and much more! * Time stamps: (0:00) Sunny Madra joins Jason (1:34) All-In Summit 2023 recap and Sunny's experience (7:44) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://Squarespace.com/TWIST (9:07) OpenAI's race to beat Google in launching the first multimodal LLM (14:42) Experiences with image-generating AI and Midjourney's interface (19:23) The culture at Apple and where risk aversion sets them back (22:32) OpenPhone - Get 20% off your first six months at https://openphone.com/twist (24:03) Google's advantages and chances against OpenAI in multimodal LLMs (31:30) Fitbod - Get 25% off at https://fitbod.me/twist (33:00) UI developments and what sets multimodal LLMs apart (44:22) ChatGPT Enterprise (45:37) Sunny demos Canva's ChatGPT plugin (55:00) Code LLaMa's potential and Falcon 180B's unique features (59:41) Sunny demos Headshots AI * Follow Sunny: https://twitter.com/sundeep * Check out Headshots AI: https://headshots-starter.vercel.app/overview Check out Falcon 180B: https://falconllm.tii.ae/ * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason's suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Dive deep into the transformative world of AI in this compelling episode. Unravel the controversies surrounding Tesla's self-driving lawsuits and discover groundbreaking insights into how DoorDash is leveraging AI for a futuristic food delivery experience. From the intricacies of OpenAI's Chat GPT & its enterprise implications to the fascinating intersection of Chomsky's linguistic theories and AI's language processing, we traverse the landscape of modern AI applications and debates. Plus, the legal intricacies of 'Wugs' and their relevance in today's tech-savvy world are laid bare. Join Ash Bennington and Mikhail Voloshin as they shed light on AI's monumental role in our future. Subscribe for more insights on AI's impact on our economy, job market, and daily lives. CHAPTERS 00:08.55 - Introduction with Ash Bennington 01:11.383 - Tesla lawsuit: Driver fatalities '19 03:58.751 - Data: Self-driving vs. Human drivers 06:53.707 - Ethics: Self-driving & the trolley issue 13:16 - DoorDash and AI's role 13:41 - AI's impact on food delivery jobs 20:15 - AI implications in job market 21:00 - AI's impact on future economy 22:18 - Intro to Chat GPT & OpenAI Enterprise 24:11.345 - ChatGPT Enterprise features & benefits 27:59.631 - Future of GPT & Competitions 31:11.238 - Why discuss Wugs? 32:38.247 - Wugs: Legal Controversy 34:56.53 - Chomsky theories & AI's language process 39:38.89 - Ash's closing thoughts Learn more about your ad choices. Visit podcastchoices.com/adchoices