Podcasts about Opus

Later this month we're going to be checking out the new movie COYOTE vs ACME which was stuck in Development Hell for quite some time- so we decided to take some time of our own and check out 4 other movies that languished in Development Hell and this week we kick if off with, perhaps, George Miller's Opus. Executive Producers:  Tim (Applescruff), Derrick Copling (Sir Slick Derrick The Knight Bard), Matthew Schnapp, Noah Overton (Noah of The Dark Woods), Peter "Not SoBad Lookin'" Pernice Listen to the HMP Live Stream, Sunday Nights and Live Streams with Adam throughout the week.  YouTube https://www.youtube.com/@HMPOD Merchandising, Merchandising, Merchandising: https://www.teepublic.com/user/halfassmoviepod HMP Instagram- https://www.instagram.com/halfassmoviepodcast Adam- Letterbox- https://boxd.it/3aAF TikTok- https://www.tiktok.com/@adam.portrais Sean Likes Spaceships: https://www.youtube.com/@Seanlikesspaceships Bruce YouTube- https://www.youtube.com/@Animedad Email- HalfAssMoviePod@gmail.com

Robert Brill, CEO of Brill Media, explains how businesses can implant a complete growth engine that attracts ideal customers, converts more leads, and scales sustainable growth through a proven marketing framework. Under his leadership, Brill Media has been recognized 11 times by the Inc. 5000 and the Financial Times 500 for helping businesses grow through precision advertising, strategic messaging, and performance marketing. In this conversation, Robert introduces The Growth Engine Framework—Setup, Awareness, Conversion, Closing, and KPIs. He explains why businesses must first define their Super Consumer, build a compelling proprietary system, and deliver messaging that differentiates them in crowded markets. Robert also shares how overcoming the “81% Gap” through nurture marketing, leveraging AI-powered tools, and documenting repeatable systems enable organizations to scale more efficiently while helping founders transition from operator to owner. — Implant a Complete Growth Engine with Robert Brill  Steve Preda here with the Management Blueprint, and my guest is Robert Brill, the CEO of Brill Media, a leading media buying agency specializing in precision advertising for business growth. Under his leadership, Brill Media has been recognized 11 times by the Inc. 5000 and the Financial Times 500. Robert, welcome back to the show.  Steve, thanks for having me. It’s great to be back. Good to see you again.  Yeah, good to see you after two and a half years. Lots of things happened. So we’re going to dive into all of those things, but let’s start with your personal ‘Why’ and how you’re manifesting it in your business, Brill Media?  I mean, my personal 'Why' is I'm focusing on becoming an owner, not an operator. Spend more time with family, less stress, more happiness.Share on X Because if I think about the last five years, the most cherished times that I think about are the times that I’ve spent on vacation, going to Disneyland, or going to baseball games with my family—all the fun stuff. And it’s not about the fun stuff necessarily. It’s about the fun stuff with family. So, more of that.  Yeah, you’re absolutely right. Those times with the kids don’t come back. The business is going to be around for a while longer, much, much longer. So prioritizing this is a really good idea. So tell me what happened over the last two and a half years since we talked together. What has changed in your business?  You know, we’ve really focused on evolving our solutions. For many years, we’ve been focused on agencies, and we continue to be focused on agencies. If you search for white-label media buying on Google, we’re one of the top one or two results. That’s because we’ve carved out a really strong position helping agencies do media buying, earn revenue, create stickier client relationships as a result of the work we do, and complement their work.  What we've learned over the years is that no amount of good media buying can overcome the wrong messaging.Share on X Even if you look at search engine optimization or social media, at the end of the day, it’s just an amplification of an existing message. If you’re spending lots of time, energy, and, notably, money delivering the wrong message, worst-case scenario, you’re confusing the marketplace. Best-case scenario, you’re only losing money. But obviously, neither of those is the desired outcome.  So before we help clients buy advertising space, post on social media, do SEO, or Generative Engine Optimization (GEO), we really want to dial in the types of messages that are most interesting to them. The next part is this: even if you have the right message and you have the best media buying in the world through Brill Media, none of that matters if you have a leaky bucket. The leaky bucket is when you pay a lot of money to run a Google Search ad, someone clicks, and then they never hear from you again.  At the end of the day, it takes more than one touch—or even a few touches—to get someone to buy from you. So our responsibility has evolved into building this growth engine of understanding the motivation behind why people buy from your company, then delivering the message, then getting people to convert, overcoming what we’re calling the 81% Gap—we can talk about that—and then getting people to see you everywhere so that you become the inevitable choice. The fifth step is understanding the KPIs—the success metrics—for every step of the process. So it’s not just media buying anymore.  Yeah. No, I definitely noticed that it’s not just media buying. It’s not just precision advertising. It sounds like you help them strategize what the right message should be and then convert those leads into customers. So essentially, it’s the whole growth engine that you’re building for companies. Is that right? That is exactly right. It’s the growth engine.  So what is the framework? Because, remember, this is a framework podcast. So describe to me. You actually mentioned step four and step five. I don’t know what the first three steps are. So can you go through the five steps and share with the listeners what that looks like?  So, step one: Setup. Who are you talking to? What’s unique about your audience? What’s unique about your business, and how do you help them achieve transformation? When we talk about setup, there are a few subsections. There’s the Super Consumer. We talk about the Super Consumer as someone who will evangelize for your company. They will pay you what you’re asking, and, in my opinion, most importantly, you like working with them.  So basically, you want to find the Super Consumer, you want to articulate who the Super Consumer is, and then target your growth engine to the Super Consumer?  The first step of the Growth Engine is simply defining who your Super Consumer actually is. So step one is Setup. Inside Setup, there is your Super Consumer, your Unique Advantage Point, and your Proprietary System. The reason we talk about the Super Consumer is that a lot of companies, especially big corporations, talk about the Total Addressable Market—everyone who can possibly buy from you. It’s too broad.  They also talk about small and mid-sized businesses, and commonly people talk about the Ideal Customer Profile, which is anyone who can extract value from your company. In our opinion, that’s too broad as well because if you dial in to the Super Consumer—if you understand the people you want to work with, who will evangelize for you, and who will pay you what you’re asking—you have a subset of people.  When you define them, there's a clear, describable transformation that you can provide that helps you become the inevitable solution for that group of people.Share on X When you know what those people want, what their desires are, what keeps them up at night, what they’re experiencing on a day-to-day basis, what they’re saying to themselves, what they’re saying to other people, and what they’re searching for—when you understand the psychology behind the person—you can actually carve out a position that is highly valuable.  The key part for us is that this is about commoditization and decommoditization. When you talk about lawyers, doctors, dentists, accounting firms, or any retail location, most of these businesses are commoditized. What commoditization means for us is that if you’re an accountant or CPA, your website says something that every other CPA in the area says. If you’re a dentist doing Invisalign, you’re saying something that every other dentist in the area says. That means you can swap out the logo and swap out the photos of the people, and it’s exactly the same.  The consumer can’t tell the difference between one dentist and another, or one accountant and another, because they’re all saying the same things. So the way you decommoditize is by talking about your Super Consumer—who you actually want to serve—and then carving out a unique position for those people.Share on X An example would be an accounting firm we spoke with that really focuses on the trucking industry because they happen to have a large degree of experience in that space. So don’t say you’re a generic accountant who does bookkeeping, taxes, and everything else. Say, “We’re the number one accounting firm for truckers in America.”  Love it.  That’s unique.  Yeah. Love it. Okay, so step one is Setup. Who you’re serving, who your Super Consumer is, what your Unique Advantage is, your Proprietary System, and decommoditization. What’s step two?  Step two is Awareness—driving awareness with your message. Our idea is that now you know exactly who you’re talking to and how they can achieve transformation with you. When you have the ability to really define how they’ll engage with you and what they’ll get from you that’s different from anyone else in the area or the country, that’s when you deliver the message. That’s when you run ads, post on social media, and say things that are going to attract people.  There’s a whole subset of activity behind that related to levels of awareness. The number one mistake businesses make on social media is posting content that’s irrelevant to the audience. That irrelevance comes from how aware the audience is. When people are unaware they have a problem, it doesn’t mean they don’t have a problem. It just means they don’t realize they have one. Your responsibility, when speaking to people who are unaware, is simply to help them understand that they have a problem.  You’re not trying to get them to start now, book a call, or get your free diagnostic. You want to trigger something in their head so they say, “Oh, I’m dealing with this type of experience. I’m a trucking company, and I really don’t have good accounting. I didn’t realize I had a problem.” The success of your marketing is simply when that person says, “Oh, I actually have a problem now.” You’re not going to see that in HubSpot.  You’re not going to see that in any meaningful metric. But when you consistently post content on social media that highlights the problem you solve, three, four, or six months from now, you’ll start to see that wave of marketing activity result in activity inside your HubSpot or CRM. So step two is Awareness—simply delivering the message. Okay.  Step three is Conversion. Conversion is simply, “Hey, click on this ad or see my post and download the guide, take the diagnostic, take the interactive quiz, watch a video,” whatever it is, in exchange for an email address, name, phone number—that type of thing. Now, here’s a key insight. People are not ready to buy after they submit their contact information. That’s another meaningful point that businesses overlook.  They think, “Whoa, a lead just came into HubSpot. Well, clearly they’re ready to spend $50,000 with me.” But think about the experience. Maybe I spend two and a half seconds on an ad. I spend 20 seconds on a landing page. No one’s going to spend any meaningful amount of money after 22 and a half seconds of engagement.  Yeah.  All they’re saying is, “Hey, for a moment in time, what you said to me was relevant.” And that’s it. This is where a lot of companies stop. They say, “Well, I’m getting bad leads. They’re not converting into business.” Or they say, “I got a click, and they visited my website.” It’s not turning into business because you’re not warming people up. And then the solution to that is you’ve got to overcome this 81% Gap, right?  So after someone converts—and for e-commerce it’s slightly different. People maybe visit your site, or they add something to the cart and they don’t purchase yet. But going back to B2B and professional services, you’ve got to overcome this 81% Gap. There’s a study by 6sense, the account-based marketing firm, that says 81% of buyers will only talk to a vendor after they’ve decided to work with the vendor. The implication of that is staggering. The number is going to increase by 2030 to, like, 95% or 98%.  What that means is companies are not going to get a chance to sell people anything. There’s no sales conversation. There’s no credibility. There’s no case studies. There’s no testimonials. There’s no, “Hey, here’s why you should work with us.” Which means all the information that would’ve been supplied by the salesperson now needs to be supplied by marketing. All the case studies, the testimonials, the credibility markers, you’re a member of the Chamber of Commerce—all of that needs to be delivered in marketing. It’s no longer going to be delivered in a sales conversation.  Interesting. Yeah.  So step four is Close.  After conversion, don’t we have a nurture step?  Well, we’re calling Close the nurture. Close is effectively the nurture step.  Okay. Got it.  So it’s the activity to achieve the close, which is the nurture. What we’re saying is: retargeting ads. Again, here’s another common mistake businesses make. Many businesses will pummel people with the same ads that got them into the funnel. That’s worthless because you’ve already delivered that message.  The user’s beyond that. What the user needs to see are the case studies, the testimonials, the credibility markers—all the reasons why your company should be the company they choose. The user needs to see the email marketing—up to 45 emails over the course of 100 days, somewhere around there.  Forty-five emails?  Yeah. Twenty-five to 45, but we recommend 45. The reason is, first of all, the user’s not going to read all of them. Secondly, the user’s only going to pay attention to the things they’re actually interested in. So: retargeting ads, email marketing, and professional services. The last component is LinkedIn Social Preheating. LinkedIn Social Preheating is the simplest thing that anyone listening to this can take action on this today.  Go to Sales Navigator. Create a list of all the people who are in your CRM. Find them on LinkedIn. When they post something, like their post. That’s it. Spend 20 minutes a day in the morning liking posts from people who’ve expressed interest in your business. Or, alternatively, do the same thing for people you want to work with who don’t know you yet. The reason that’s valuable is because, number one, they get notifications and sometimes emails saying, “Steve Preda liked your post.” Steve Preda. Steve Preda. Steve Preda. Over the course of two weeks: “I’ve got to pay attention to Steve Preda. That name sounds familiar.”  Yeah.  Oh, and here’s the ad from Steve Preda, and here’s the email about the transformation he provides. So by the time you or your people call them: “Steve Preda… I’ve been meaning to talk to you.” Or they call you and say, “Steve, I see you everywhere.” The LinkedIn activity, combined with the email marketing and the retargeting ads, makes you the inevitable choice. To a small group of people.  Because you’re not trying to get millions of customers unless you’re in retail or e-commerce. You’re trying to get 20 customers who are going to pay you $10,000 to $50,000. To those 20 people—and the hundred people who maybe don’t convert—you’re everywhere. You’re the inevitable choice. The fifth step in this process is setting KPIs at the beginning. How many sales-qualified calls do you need? How much revenue per month do you need? There are clients who are members of ProVisors.  I’m a member of ProVisors. How does your marketing impact your ProVisors relationships? The core idea is that we see a lot of companies going into the marketplace with point solutions. “Hey, I’m going to try Facebook ads.” “Ah, it didn’t work.” “I’m going to try Google Ads.” “Ah.” “I’m posting on LinkedIn.” “Ah.” They try all these different things and wonder, “They should work. Why don’t they work for my business?” The answer is because you don’t have a unifying strategy. They all serve different roles in the marketing process.  When you know the difference between an unaware consumer and what they need to hear versus a solution-aware consumer who’s on Google, you know you need different metrics and KPIs. We want to prevent companies from going from one point solution to another for years, spending lots of money and getting very frustrated. Instead, have one unifying strategy and then deploy activities that are actually going to benefit the growth…Share on X  Love it. So the five-step framework is: Setup—Super Consumer, Unique Advantage, Proprietary System. Number two, Awareness—ads and social. Then Conversion, which is basically email capture, a diagnostic, a video, a white paper, whatever. Then Close, which is the nurture: retargeting, email sequence, LinkedIn Social Preheating. Interesting. And then KPIs. How do you measure? What are your targets? And how do you get there? That’s  Yeah. That’s the Growth Engine.  So one thing that you mentioned: Proprietary System. What do you mean by that?  The only truly unique things that exist in the world are technological innovations. The iPhone—when Apple created the iPhone—that was unique. When Ozempic came out, that was unique. I’m not talking about that. What I’m talking about is this. I’ll give you an example. If you’re a lawyer, a dentist, or an accountant— If you’re a lawyer, you cannot deviate. You’re literally dealing with the law.  What you have to do as a lawyer has been dictated in legal documents for a long time, depending on the field of law that you study. You cannot deviate from that. You have a process that you have to follow. But what is unique is the way you think about it, the processes inside your organization that ensure you’re successful, and the way you steward clients. Look at marketing. We’re a highly commoditized industry. There are a million people on Upwork who do some sort of marketing work.  There are 40,000 or 50,000 agencies in the United States that all do some type of marketing work. If I go to the marketplace and say, “Hey, I do Facebook ads,” guess what? There are 10,000 people who also do Facebook ads. That’s not unique. What is unique is the systems and processes we’ve developed around how we do Facebook ads and how we think about marketing. The first step we take with our clients is developing a Proprietary System—the thing that's unique about the way they approach the world.Share on X  I was just doing some thinking about roofing. I have some notes here. The Roof Guard Lifetime Protection System. What is that? I don’t know. But you know what? A roofing company needs to have something called the Seven-Point Storm Shield Inspection or the Precision Roof Blueprint. The idea is that you have something no one else has, such as this Precision Roof Blueprint, that you can point to and say, “Look, you can get roofing from anyone, but only we have the Roof Guard Lifetime Protection System.”  Yeah. Yeah, got it. So it’s not a marketing system. It’s more about productizing and branding your services.  Exactly. You need a three-, five-, or seven-step system that you can point to. When we have sales conversations, we have a visual for the Growth Engine. The reason that’s important is because you need to be able to hook into the buyer’s mind. One of the ways you hook into the buyer’s mind is by the buyer saying, “Look, they have this thing called the Roof Guard Lifetime Protection System. I don’t know—that sounds real.  Here are the seven things you get when you get the Roof Guard Lifetime Protection System.” It’s a way for people to not just get excited about your business, because that lasts a very short period of time. They need to go to their husband or wife, or they need to remember a very pithy, short summary of what the conversation was about. “Oh yeah, they have the Roof Guard Lifetime Protection System. Here’s what it is. Here’s a visual of it.”  Okay. That makes sense. So, switching gears here a little bit. Things are changing very fast in this business, and you want to make sure you put your family first. What is one thing that you’re actively trying to figure out in this business going forward?  I mean, the most fascinating and exciting thing I’m doing right now is something I’ve always wanted to do but never had the skills for—and now I suddenly do—which is building actual software that’s valuable for us and our clients. For example, we have a framework for LinkedIn. In very simple terms, you like the posts of the people you want to sell to. From the perspective of the LinkedIn algorithm, that’s very low value.  It’s good from a sales perspective, but from the algorithm’s perspective, it’s not that interesting. You post content on LinkedIn that has to have a unique perspective—an opinion. A lot of people can write with AI. You don’t write with AI. You say something that’s unique to your perspective. Maybe AI helps you write it more eloquently in little bits and pieces. But even that by itself, it’s hard to get traction. The way you get traction on LinkedIn right now is through comments. I’ll get 80 to 100 views on a post.  I’ll get 400 to 800 views on a comment. The comment is the engine behind more visibility on LinkedIn. This goes back to the question you asked. The key point on LinkedIn is you’re not just saying, “Hey, great job.” “I like that.” “I totally agree with you.” Or posting the raised-hands emoji and saying, “This is amazing.” That’s not the kind of comment I’m talking about because that’s low value. It’s also not AI-written content because that’s low value. It’ll deprioritize your content.  When you comment on LinkedIn, you have three sections: Compliment. Expand. Ask. Compliment: “You’re right. Marketing is highly commoditized. I fully agree with you there.” Expand: “When we work with clients, especially highly commoditized businesses like doctors, lawyers, and accountants, the first thing we do is help them decommoditize their business.” That’s the second section. That’s Expand. The third section is Ask. “What’s the first step you choose when you come across a highly commoditized business?” Compliment. Expand. Ask. Now guess what? We built an app that I’m using. All you need is five to eight posts a day. It’s AI-powered. I put in a link for Opus 4.8. It gives me a perspective on what I could say. I get three options. I copy one, write my own commentary around it so it’s not fully AI-written—because I want it customized to me—and then I post it. After that, I go back to the app and put the content I wrote back into the app.  A few things are happening. Number one, any of our clients can now use this app to write highly engaging commentary on LinkedIn. It starts to learn your voice and how you write so that the AI becomes better at writing in your style. I don’t know what it’s called—a micro app, a business app. This isn’t something I’m going to take to the marketplace and say, “Here, spend $10 a month to buy this service.” It’s simply an added value for our clients.  Love it.  Those types of apps are super powerful. I get on sales conversations. I understand the business problems that businesses have.Share on X I build apps. Like right now, I’m in the process of building a media planning app that actually becomes a replacement for how we develop proposals. One component of that app is going to have a diagnostic section, which means you give me some information, and it’ll spit out information about what you should do for your marketing that, number one, follows our framework, the Growth Engine, and, number two, is based on the historical knowledge we have across all of our clients—but generalized by industry, not specific client names.  It takes the best of what we do and makes it so easy that someone who doesn’t have a great deal of knowledge in digital advertising can get a highly pertinent proposal and diagnostic ready for them with the click of a button after talking to someone for 15 minutes.  Very impressive. So you’re building these apps, and essentially you’re empowering your business with these apps so some of the things you’ve done in the past can be automated. So, Robert, if you had a magic wand and you could fix one thing in your business in the next 12 months, what would that be?  I mean, look, just to be completely honest, I understand the difference between an owner and an operator. The short answer to that question is I want to be an owner, not an operator. I’m looking at an operator as someone who’s in the day-to-day. They’re the practitioner. I mean, I’m 23 years into the advertising business. I’m 13 years into my business. I love this business. You’re not going to see me become a real estate agent, and I’m not going to be hawking…  I think I probably said this last time. I’m not going to be hawking crypto or whatever the case is. This is my life, and this is my passion. For so many years of my life, I’ve dedicated my interests, my hobbies, and my professional time to becoming a better practitioner. My goal now is to become an owner, which means the business operates without me. I get to focus on the projects that I want to focus on, which I’m already doing to a degree.  I have a phenomenal Director of Accounts. Her name is Linda Flores. She is k*ller. She scares me sometimes. We’re on calls, and I’m like, “Holy cow, if I was not the owner of the business, I’d be scared. In fact, you’re scaring me, Linda.” You’re getting things going. People should be scared of you. That’s what a good Director of Accounts—an operations person—does. She’s phenomenal. But at the end of the day, if I choose to be on an island for six months out of the year, the business operates fine. We’re not there yet. That’s what I’m focusing on.  So what’s missing? You said you’re already spending some of your time developing these apps—the stuff you love. What would you have to let go of in the next 12 months to get there?  I recently read the book The E-Myth about a year, year and a half ago. One of the most insightful perspectives I got from The E-Myth is this—and people are going to hate this. People who are not entrepreneurs will look at me like I’m the devil. Okay? But this is not my idea. This is from The E-Myth. The idea is that processes, systems, and standard operating procedures are effectively the safety net for the success of a company.  Which means instead of hiring incredibly expensive people inside your business, you can hire, for many roles, people with the minimum level of qualification. The standard operating procedure becomes the safety net that helps them succeed. I was like, “Holy cow, that’s fascinating.” Because as a business owner, I’m looking at myself. I’m hiring highly qualified, very expensive people to do the work. The sign of a good business, in my opinion—or at least from what I understand—is a business that has such phenomenal standard operating procedures that it can hire people with the minimum level of qualification, and they can still be effective.  Frankly, I think we have good standard operating procedures, but we need better ones. And frankly, the AI tools that I'm building help us get there.Share on X The media planning tool that I’m building means I could hire someone with two, three, or five years of experience in marketing and advertising. Through the AI system, they get the benefit of all of our clients’ knowledge and insights that we’ve talked about over the years. They get the benefit of what I know about marketing.  They get the benefit of all the data that’s flowed through the pipelines of our business. All of that information becomes the baseline from which someone with two, three, or four years of experience in marketing develops a phenomenal strategy. Because they’re not relying on two, three, four, or five years of experience. They’re relying on my 23 years of experience delivered through an AI pipeline.  So essentially, what you’ve accumulated over the years—institutional knowledge—maybe it’s in your head, but you can download it. You’ve written things. You’ve produced a bunch of videos. You can put that into an AI database or knowledge base, and that can power some of the systems you’re developing. Other people can come in, run it, and follow your process.  Yeah. And it’s not just ours. I mean, look, it’s any system that I believe is valuable that should be piped into that AI knowledge base. But the value there is me as the curator. That’s when you get to the point where the business is still an authentic reflection or extension of the owner. One of the most important things, especially for professional services businesses, is that the business will be successful if it’s an authentic representation—or extension—of the owner, and you like the people you’re working with.  Love that.  Which goes back to the Super Consumer. The most important part of our whole process is: Who are the people you love working with? Just as an aside, what’s funny is there are two paths. There’s the path of people you love working with who don’t pay you as much, but it really fills your soul. You like them. You’re helping them. They’re very grateful for it.  Then there are the people you like working with less, and they pay you a ton of money. You need both. I think every professional services client we have who starts paying attention to this discovers that same dichotomy of clients.  Well, if you can have them be the same people, that’s the ultimate, isn’t it? That’s the ultimate.  Yeah. By the way, I really love this E-Myth reference. I had Michael Gerber on this podcast about 10 months ago, and he might actually like to hear how you’re refining his system in The E-Myth. So it’s pretty cool. Robert, if people are hearing this and they want this Growth Engine to be developed in their business, and they want access to the other software components you’re developing that could amplify their business—maybe the LinkedIn warm-up system and things like that—where should they go, and how can they learn more and connect with you?  Yeah. So the site that’s most relevant right now is: strategy.brillmedia.co. Again, that’s strategy.brillmedia.co. That breaks down what we do for businesses and what we do for agencies. You have pricing on there. To get a blueprint for your business—the diagnostic and strategy—we spend an hour on the phone interviewing the business owner. What are the economics? What’s been working? Why is now the time?  Tell me about your best clients and your worst clients. Just tell me stories about your business. It’s $497, and you get a complete blueprint—a complete marketing strategy synthesized through our systems and processes—so you can get off the marketing treadmill. You’re not spending months, years, and lots of money grasping at straws: Facebook. Google. LinkedIn. “Why doesn’t any of it work?” We’ll solve  All right. Definitely check out strategy.brillmedia.co. See for yourself what you can get there and how you can get started with Robert and his team. Definitely connect with Robert on LinkedIn. And if you enjoyed this episode, st81% ay tuned because every week we bring you one or two exciting entrepreneurs who share their frameworks with you. Thanks for coming, Robert, and sharing your experience. And thanks for listening. Important Links: Robert's LinkedIn Robert's  website

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 25/07 a 31/07.

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 25/07 a 31/07.

-Three different Claude models were involved in the incidents: Opus 4.7, the cybersecurity-focused Mythos 5 and a prototype that's not planned for general release. They were all doing a capture-the-flag challenge when they broke free. -"People don't want a summary of Reddit; they want Reddit," said Reddit CEO Steve Huffman -Friend, the startup and AI pendant better known for its controversial ad campaign than being a usable product, is back. The company announced a new version of its AI wearable that costs $249, still features an always-on microphone and now includes a built-in speaker so it can verbally respond to your questions. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode, we discuss POL and how it will be distributed, a potential upcoming Bitcoin fork, a Monero update, ADR29, ADR31, AI tooling, and much more.Swap now https://swap.thorchain.org/ THORChain is a decentralized crypto exchange. THORChain is the first and biggest DEX for Bitcoin. You can use any self custody wallet to swap and there's no KYC required.Timestamps:00:00:00 Intro00:03:00 Marketing update00:04:00 Need to create a new support ticket module. Trezor support added!00:06:00 The three things needed to be listed on an index00:08:00 Using AI to find scam sites00:11:00 Chad starts — version 3.20 is being tested00:12:00 Chad B started a code change to add a new asset to THORChain without a churn00:14:00 Adding more chains leads to greater complexity00:16:00 How can we add a new chain without churning?00:17:00 How complex is it to add this capability?00:18:00 Does a churn affect the timing of adding a new asset?00:20:00 Audience question: How are new assets prioritized for THORChain?00:22:00 StarSquid wants to add many more chains00:23:00 AI compatibility with THORChain discussion00:27:00 Community coding competition to add AI utility?00:28:00 Dynamic fee discussion00:30:00 Results from ShapeShift00:31:00 COSMWASMMINBPS = 0 — arbitrage performance discussion00:34:00 POL question: What gets funded first?00:35:00 POL currently only purchases base gas assets00:37:00 Stablecoins require a node vote00:39:00 How will the protocol allocate funds — every churn or another method?00:42:00 Bitcoin may go through two forks — how do we handle them?00:44:00 Is it worth it? Sounds complicated!00:46:00 Should liquidity from a new Bitcoin fork go to the treasury or POL?00:52:00 There may be two separate Bitcoin forks!00:56:00 Huginn update — network monitoring01:00:00 New Huginn model01:03:00 Opus 5 outperforms Fable on some benchmarks — AI models are becoming much more sophisticated01:05:00 OpenAI and Anthropic may lose their moat as AI becomes a commodity01:08:00 THORChain does not run on hopium01:09:00 XMR discussion01:11:00 XMR nuance — funds cannot be spent for 20 minutes01:13:00 How does the 20-minute XMR delay affect high swap volume?01:16:00 XMR backlog discussion01:20:00 Hopefully only two more churns before XMR01:23:00 We will set the price for XMR01:26:00 ADR 29, TOR Anchors, and revenue sharing breakdown01:30:00 It's an experiment — we're not sure if it will work!

Hey, it's Alex (yeah, I'm finally back from my vacation!) What a freaking week to come back to! Just after our last episode was published, Anthropic releases Opus 5, Jensen joins X and drops the “Open Weights & AI Leadership” open letter, Kimi K3 is released the following Monday beating expectations, and then the AI hack (OpenAI model breaking sandbox and infiltrating HuggingFace) is on everyone's mind, another Open Letter, this time from over 1K employees inside the frontier AI companies all talk about pacing the pace of frontier AI development. We played with Opus 5 and Kimi K3, and had the great pleasure to chat with friends of the pod Elie Bakouch (Prime Intellect) and Philip Kiely (BaseTen) about this important open weights release, then covered our general thoughts on Opus 5, and made order of all the different open letters that came out this week. Finally we chatted with Max from Pangram about the next version of AI writing detection (their biggest yet) and finished with Zuckerbergs (also on X! what's going on with everyone joining X) op-ed on the vision of personal superintelligence for everyone. Let's dive into this (as always, all the links and sources at the end, please don't forget to sub to our podcast on your favorite podcast app!) Open Weights AIKimi K3 the king of open weights - 2.8T chonker MoE near frontier model (X, HF, Blog, Tech report)This has got to be the biggest news of this week, and maybe the open weights AI news since GLM 5.2. MoonShot came back with Kimi K3, and we haven't seen any models quite this large in the open. Even Grok 4.5 is around 1.5T, this model is nearly 2x the size. Coming in at close to 3T parameters (and 2.5terabytes of weights at MXFP4 format), this model comes in very close to frontier! This was such an important release that I invited 2 friends of the pod, Elie Bakouch (prev HuggingFace, now Prime Intellect) and Philip Kiely (Author of Inference Engineering book, BaseTen) to dive deep into what makes this special! Elie's take, from reading the tech report, there's no single secret sauce, it's a combination of already available in the open techniques. Like KDA (Kimi Delta Attention) that has been out for a while, attention residuals, NVIDIA's latent MoEs. The highlight for Elie was the scaling work they did that reported a 2.5x scaling efficiency over Kimi K2.5 (2.5 performance at the same compute)! They also skipped RoPE entirely in favor of NoPE (the report calls it No Positional Encoding) for long context.Serving 1.4TB on eight GB300s (Baseten blog)Philip's team at Baseten was a day-zero provider (we're still working on bringing this model to CW Inference, stay tuned!) so I invited him to tell us behind the scenes of hosting this beast. Philip said that just loading the weights takes about 1.5TB!! of VRAM, and that's before the KV cache allocation + 1M token windows, so they're serving it on 8 GB300s where NVL72 . Baseten worked with the vLLM and SGLang teams on kernels and he also said they contributed patches back upstream! The model was trained with MXFP4, which, unlike Nvidia's own NVFP4 is a more standard format per Philip. I enjoyed his deep dive analysis into the differences, but because of this and because they trained the model with quantization awareness, it's “only” 1.5TB vs the would-be 5-6 TB if that this model in FP16 would demand. One of the more favorite nerd snipes moments, Philip pointed out that his colleague discovered that with over 99% of the usage being cached (think harnesses that send millions of the same cached tokens back and forth), tokenization actually starts to become a bottleneck. So they released a custom “basetenkenizer” that reduces the latency to serve the first token significantly! Great job!The harness in question is very importantOne important callout with 2 evidence pieces - the way you inference this model really matters. Kimi trained K3 with preserving thinking history, so when your harness uses it, it must send back the full thinking and tool use into the API to get the best next response. If your harness strips that out, you're not getting the most intelligence out of Kimi (shoutout to Niels from HF team for pointing this out). Additionally, the Composio folks, tested K3 on 3 harnesses, Kimi Code, Hermes and Claude Code. The difference in outcome was negligible, but the different in cost and number of tokens is definitely surprising! Claude Code (as a harness only) took 9x more Kimi tokens to get the same responses! This is also why Kimi Vendor Verified exists, their own held back benchmark of how well model providers serve Kimi across different quantization, tokenizer and KV cache settings. Benchmarks and the license! Ok let's start with the ugly... this isn't MIT, not remotely. This model is suspiciously served by all providers with exactly the same price (check OpenRouter) and requires inference companies to sign a contract with Kimi (I've no internal knowledge of this except that CW folks are working on it). Not something I particularly like, but hey... we're still advancing the frontier here! Speaking of frontier, this model approaches the frontier very closely. On DeepSWE, K3 sits just behind Fable 5 and GPT-5.6 Sol at 67%, beating GPT-5.5 & Opus 4.8. On Terminal-Bench 2.1 it takes second place behind GPT 5.6 Sol! It's 4th overall on Agentic Arena, with frontend design being genuinely good across the board - 1st on Design Arena

Full show notes and transcript  - https://bit.ly/4w3ZEueWatch on YouTube - https://youtu.be/UtfypSwBCGw-----Episode Summary:Dara and Matthew open on the news: an OpenAI model that escaped its sandbox and hacked Hugging Face and whether that's a frighteningly capable model or just a badly built sandbox, plus GPT-6 and Opus 5 rumours, Google's new Gemini Flash models, Apple suing OpenAI over hardware secrets, Moonshot's Kimi K3, and AI disproving an 87-year-old maths conjecture. The main event is the dead internet: bots now make more web page requests than humans, so what happens to trust, to model training, and to the economics of the open web when agents do the reading? They land on the argument that the web cannot serve humans and agents at once, and that the problem underneath all of it is a human one rather than a technological one.-----About The Measure Pod:The Measure Pod is your go-to fortnightly podcast hosted by seasoned analytics pros. Join Dara Fitzgerald (Co-Founder at Measurelab) & Matthew Hooson (Head of Engineering at Measurelab) as they dive into the world of data, analytics and measurement, with a side of fun.-----If you liked this episode, don't forget to subscribe to The Measure Pod on your favourite podcast platform and leave us a review. Let's make sense of the analytics industry together!

Summer camp was epic, but let me tell you, the lead up, the planning, the work on the front side, it did something tragic to our social media. Let me show you what I'm implementing to ensure this doesn't happen again! Hybrid Hero Members Get all of this for just $4/month https://www.patreon.com/hybridministry SHOW NOTES Shownotes & Transcripts https://www.hybridministry.xyz/212 [FREE] HYBRID STRATEGY GUIDE https://www.patreon.com/posts/complete-guide-142500019?utm_medium=clipboard_copy&utm_source=copyLink&utm_campaign=postshare_creator&utm_content=join_link Hybrid Hero Members Get all of this for just $4/month https://www.patreon.com/hybridministry Summer Social Media Year 2 https://www.patreon.com/collection/1470781?view=expanded Carousel Engine https://www.patreon.com/hybridministry/posts/carousel-engine-155124829?collection=2099839 Best Sermon Clip Generator https://www.patreon.com/hybridministry/posts/best-sermon-clip-156670711?collection=2013798

Andon Labs' latest vending machine simulation shows Opus 5 lied and colluded its way to become the best AI capitalist ever. Learn more about your ad choices. Visit podcastchoices.com/adchoices

AI news: Sam Altman says we're IN the Singularity, GPT-6 rumors, and AI models literally broke out of their sandbox. What a week. On today's AI For Humans, we dig into the wild GPT-6 rumors (emphasis on RUMORS), Sam Altman's "I've been waiting for this my whole life" singularity moment, Ilya Sutskever's SSI scaling up with Nvidia, and the ongoing debate over whether Anthropic's Opus 5 is brilliant or just hard to love. Also: Flux 3 might be the best AI video model we've seen yet (wait until you see Stacked Plates Man), Runway teases Seedance 2.5, and the new Big Bang Theory has an AI controversy.  Plus, THE SCARY STUFF: OpenAI's models exploited a zero-day and compromised Hugging Face during a security eval, the fight over open weights heats up as Kimi K3 goes open, and Chinese robots run military drills. THE SINGULARITY MIGHT BE HERE. BUT WE'RE NOT AFRAID // Show Links // GPT-6 rumors round-up (unconfirmed) https://x.com/TokenGremlin/status/2081493241795629464 Sam Altman full interview (Relentless Podcast) https://youtu.be/Vv3CEAS_w34?si=3y4SWBWxOVkqCEui The Return of Ilya: SSI scales with Nvidia https://x.com/ilyasut/status/2081732293161582930?s=20 Anthropic's Claude Opus 5 https://www.anthropic.com/news/claude-opus-5 Opus 5 Tower of Babel demo https://x.com/petergostev/status/2082071858367648035?s=20 Matt Shumer's zero-shot Counter-Strike clone https://x.com/mattshumer_/status/2081054356405731740?s=20 Black Forest Labs' Flux 3 announcement https://bfl.ai/blog/flux-3 Flux 3 split screen rendering https://x.com/umesh_ai/status/2081664138942529601?s=20 Flux 3 GPU migration documentary (Venture Twins) https://x.com/venturetwins/status/2081515687944822800?s=20 Flux 3 VHS-style recordings https://x.com/venturetwins/status/2081948871882911999?s=20 Stacked Plates Man https://x.com/gandamu_ml/status/2081956426801435060?s=20 https://x.com/gandamu_ml/status/2080871397371371823?s=20 Flux 3 pirate bass https://x.com/itspoidaman/status/2081651615493464406?s=20 Big Bang spinoff AI Controvesy  https://x.com/sitcomcrave/status/2081152263481913774?s=20 Runway teases Seedance 2.5 https://x.com/runwayml/status/2082112674666529224?s=20 OpenAI on the Hugging Face security incident https://openai.com/index/hugging-face-model-evaluation-security-incident/ Jensen Huang on the Open Alliance https://x.com/JensenHuang/status/2080643682408321103?s=20 Anthropic has not signed (TechCrunch) https://techcrunch.com/2026/07/24/as-us-weighs-response-to-chinese-ai-industry-urges-against-broad-open-weight-restrictions/ Kimi K3 goes open weights https://x.com/scaling01/status/2081759521878270426?s=20 Chinese robot military drills https://x.com/ClashArchivist/status/2081499576373297562?s=20 Pentagon scales data centers on Army bases https://x.com/Polymarket/status/2082052445144826055?s=20   // Join the AI For Humans community // Join the AI For Humans Discord https://discord.gg/muD2TYgC8f Support AI For Humans on Patreon https://www.patreon.com/AIForHumansShow Subscribe to the AI For Humans newsletter https://aiforhumans.beehiiv.com/ Follow AI For Humans on X: @AIForHumansShow https://x.com/AIForHumansShow Follow AI For Humans on TikTok: @aiforhumansshow https://www.tiktok.com/@aiforhumansshow Speaking and booking https://www.aiforhumans.show/  

In this episode, Conor and Jaeden explore the latest advancements in AI benchmarks, focusing on Mirror Code and its implications for software development and automation. They discuss how AI is increasingly capable of recreating complex software, solving friction points, and transforming productivity.Watch on YouTube: https://youtu.be/RqPuvAPN2LcGet the top 80+ AI Models for $8.99 at AI Box: https://aibox.aiConor's AI Course: https://www.ai-mindset.ai/coursesJaeden's AI Business Community: https://www.skool.com/aihustleChapters00:00 Introduction to the New AI Benchmark: Mirror Code00:30 The Context: AI Watching and Learning from Human Actions00:57 Mirror Code's Emergence and Its Significance02:12 Claude Opus 4.7 Rebuilding Apple Software in 14 Hours03:12 What is the Mirror Code Benchmark? Testing AI's Rebuilding Capabilities03:41 Results: 17 of 25 Programs Recreated Perfectly04:10 Implications of AI Recreating Complex Software04:39 OpenAI GPT 5.5 and Opus 4.7 Reimplementing Software05:10 The Significance of Speed and Cost in AI Rebuilding Tasks05:39 Personal Use Cases: Building and Rebuilding Software with AI06:06 AI's Impact on Software Development and Productivity07:13 Conor's Journey into AI Agents and Coding07:41 The Role of Articulating Friction Points in AI Solutions09:01 Fixing Friction Points in Software Using AI09:30 Case Study: Rebuilding a Booking Engine with Claude10:26 Rebuilding Software and Features Faster with AI11:25 The Power of AI in Solving Real-World Problems12:00 AI as a Tool for Solving Friction Points in Business12:26 Introducing AI Box: Affordable Access to AI Models12:48 The Value of Solving Problems with AI13:12 Encouragement to Explore AI Solutions and Friction Points See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What up Doe ! We are back to talk about the biggest party of the Summer WWE Summerslam ! We are joined by our homie Ant Page of Podders of Destiny to give you our picks and predictions ! Oba Femi vs Brock Lesnar CM Punk vs Cody Rhodeswe'll talk about it all !Make sure you come WATCH Summerslam with us at Draft Kings Social in Troy Mi as well ! We also will talk what's next in the story of Tyson fury vs Anthony Joshua too ! FOLLOW & SUBSCRIBE – KNOCKOUTS AND 3 COUNTSBringing you the best in Combat Sports and Pro Wrestling – available everywhere!YouTube (Live Tues & Thurs 9PM EST): http://www.youtube.com/c/Knockoutsand3CountsFacebook (Live Tues & Thurs 9PM EST): https://www.facebook.com/knockoutsand3countsApple Podcasts: https://podcasts.apple.com/us/podcast/knockouts-and-3-counts/id1446923286Spotify: https://open.spotify.com/show/3OpvW0QHBe3uRc3D0pbORt?si=33935ad9669146d3Twitter/X: https://twitter.com/ko3cpodInstagram: https://www.instagram.com/ko3cpod/TikTok: https://www.tiktok.com/@ko3cpodMerch, Streams & Videos (Millions): https://millions.co/kyle-collisonIf you love what we do at KO3C, support us by grabbing merch or ordering a personal video at Millions.co.We go LIVE every Tuesday and Thursday at 9 PM EST — bringing you interviews, breakdowns, and the real talk you won't hear anywhere else.Want dope podcast clips ? Use our Opus clip Link : https://www.opus.pro/?via=Ko3C

What up Doe ! We are back to talk about the biggest party of the Summer WWE Summerslam ! We are joined by our homie Ant Page of Podders of Destiny to give you our picks and predictions ! Oba Femi vs Brock Lesnar CM Punk vs Cody Rhodeswe'll talk about it all !Make sure you come WATCH Summerslam with us at Draft Kings Social in Troy Mi as well ! We also will talk what's next in the story of Tyson fury vs Anthony Joshua too ! FOLLOW & SUBSCRIBE – KNOCKOUTS AND 3 COUNTSBringing you the best in Combat Sports and Pro Wrestling – available everywhere!YouTube (Live Tues & Thurs 9PM EST): http://www.youtube.com/c/Knockoutsand3CountsFacebook (Live Tues & Thurs 9PM EST): https://www.facebook.com/knockoutsand3countsApple Podcasts: https://podcasts.apple.com/us/podcast/knockouts-and-3-counts/id1446923286Spotify: https://open.spotify.com/show/3OpvW0QHBe3uRc3D0pbORt?si=33935ad9669146d3Twitter/X: https://twitter.com/ko3cpodInstagram: https://www.instagram.com/ko3cpod/TikTok: https://www.tiktok.com/@ko3cpodMerch, Streams & Videos (Millions): https://millions.co/kyle-collisonIf you love what we do at KO3C, support us by grabbing merch or ordering a personal video at Millions.co.We go LIVE every Tuesday and Thursday at 9 PM EST — bringing you interviews, breakdowns, and the real talk you won't hear anywhere else.Want dope podcast clips ? Use our Opus clip Link : https://www.opus.pro/?via=Ko3C

YEAR 6 IS FINALLY HERE!  GO CHECK OUT OUR YOUTUBE TO SEE OUR BRAND-NEW INTRO!  You can find the animator using the link below! https://www.fiverr.com/syedahumna56/do-professional-pixel-art-animation-of-your-choice?utm_medium=shared&utm_source=copy_link&utm_campaign=gig&utm_term=AyNLxkP   *Intro includes minor edits not provided by the original animator. All animated assets were provided by the animator listed above, with some text assets added in post by Keeping Up With The Nerds.   Check out our affiliated links! Opus clips Partner link: https://www.opus.pro/?via=Nerd   Check out our Website: Keepingupwiththenerds.com   ​This week on Keeping Up With The Nerds, we're heading straight into the wild aftermath of San Diego Comic-Con with a stacked recap of the biggest announcements across movies, TV, and Marvel! First up in the main event, the Nerds talk about San Diego Comic-Con and got a bunch of news to look forward to. Starting with the smaller (but still exciting) reveals for Spaceballs 2, a new Resident Evil movie trailer, and Johnny Depp as Ebenezer Scrooge in his new movie, Ebenezer. Beyond the big screen, we dive into the wild return of Mel Brooks, the bizarre parodies taking on modern cinematic universes, and why these classic comedy revivals are making noise again. Then, Avatar: Seven Havens takes center stage alongside some other big hitters like Blade Runner 2099 and a new Lanterns trailer. We break down what the future looks like for the Avatar franchise, how Prime Video is expanding its sci-fi slate, and debate all the hidden details and lore clues buried inside DC's latest footage. To top it all off, the Nerds spend the last part of the episode discussing Marvel's panel and the hype being built around Doomsday and... Ryan Gosling as Ghost Rider?! We break down the massive casting updates, character returns, multiverse theories, and what this means for the future of the MCU. Is Marvel finally back on track? Tune in to find out!   #KeepingUpWithTheNerds #Podcast #SDCC #Spaceballs2 #ResidentEvil #Ebenezer #AvatarSevenHavens #BladeRunner2099 #Lanterns #AvengersDoomsday #GhostRide #Marvel News #GamingNews   This Issue is Brought to You by: Nick Valero, Rene Bravo & Sean Rodriguez   Podcasts can also be found here! YouTube: https://tinyurl.com/y6luw7uq Spotify: https://tinyurl.com/y4q64run Apple Podcasts: https://tinyurl.com/y4ztkn2o   Follow us on our socials! Instagram: https://www.instagram.com/keepingwiththenerds/ Twitter: https://twitter.com/KeepitNerds Ask us questions and leave us a like and comment! Don't forget to subscribe and leave a follow!

Every major AI lab signed the Open Weights letter defending open models. Meta, OpenAI, Google, Microsoft, Nvidia.Anthropic was the only holdout.Yesterday, its CEO, Dario Amodei, published a thoughtful defense of that decision to not fully support open weight or open source models. Here's what nobody's connecting: the money trail. Roughly 80% of Anthropic's revenue is businesses paying per token. Free Chinese open models attack that exact revenue stream weeks before Anthropic is set to go public. On today's show we break down what Dario actually said, what he said before, and why we think this was written for Washington policymakers and not for the rest of us.Anthropic Responds: Why Claude's CEO didn't sign the open model pact and the real reasons why -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.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:Anthropic Refuses Open Model PactDario Amodei's Public Letter AnalysisAnthropic's 80% Revenue Token ExposeChinese Open Model National Security FearsMicrosoft & Nvidia's Open Weights CoalitionRegulatory Capture and Washington InfluenceTiming Related to Executive Order DeadlineIPO Motivations Behind Anthropic's DecisionsContradictions in Anthropic's Open Model StanceImpact of Open Source on Token Business ModelTimestamps:00:00 Anthropic's stance on open models04:19 Discussing Anthropic's response to open models06:39 Understanding open weight models12:08 Future AI and cybersecurity risks15:04 Discussion on open-source AI models19:30 Discussing Anthropic's business challenges21:08 Cutting costs with open-source models26:17 Anthropic's recent stock downturn27:11 AI investment and cost efficiency shift30:14 Anthropic's stance on open source models36:32 INTROPICS IPO and regulatory discussions37:37 Wrapping up and subscribingKeywords: Anthropic, Claude, open model pact, open source AI, open weights, American AI leadership, Dario Amodei, IPO, regulatory capture, DC lawmakers, Chinese open source models, token revenue, per token business model, NVIDIA, Microsoft, Meta, OpenAI, Google, IBM, national security, AI safety, government mandates, chip controls, AI regulation, chip ban, industrial scale distillation, mandatory safety testing, inference, AI ecosystem, Opus 5, Fable 5, GPT-5, GLM 5.2, cost per task, token efficiency, model router, proprietary models, closed source AI, cybersecurity risks, Chinese cyberattacks, biological attacks, Glasswing program, open source vs proprietary, tech lobbying, Trump AI order, federal deadline, AI policy, artificial general intelligence, artificial superintelligence, AI monetization, S-1 filing, public company, venture capital, AI benchmarks, model switching, API pricing, model containment, Hugging Face incident, AI startup monopoly, safety vs business protection, market competition, AI cost reduction.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 

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

Jeff Barg, Head of AI at Clay, talks with TITV Host Akash Pasricha about Anthropic's Opus 5 release and Clay's approach to open-source. We also talk with Theresa Payton, former George W. Bush CIO and CEO of Fortilace Solutions about AI cybersecurity regulations, AI Finance Reporter Dakin Campbell about Google's AI data center financing strategy, and we get into enterprise open-source AI adoption with PwC's Dallas Dolen.Articles discussed on this episode: https://www.theinformation.com/articles/google-using-wall-street-financing-techniques-expand-chip-salesSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction01:13 - Initial Reviews on Anthropic Opus 511:45 - Open-Source AI Security & Policy Debates23:48 - Inside Google's AI Data Center Debt Strategy34:19 - PwC on Enterprise Open-Source AI Adoption

Over 3 hours, OpenAI, Anthropic, Google AND Microsoft all dropped new AI upgrades that are live. How you use AI in your work literally changes every day, as frontier labs are racing to roll out big quality of life updates between big model drops. How can you keep up? With our Friday Features show, where we break down the latest AI updates that are live and available to all, and we tell you how to use them and why they matter. This week did not disappoint. You don't want to miss what's now at your fingertips. JARVIS mode, anyone? ChatGPT goes Jarvis Mode, Claude can learn from you, Google unleashes spark agent and 7 more AI updates you can use today -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.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:Anthropic Claude Opus 5 Model LaunchOpenAI Agent Hacks Benchmark SandboxOpenAI vs. Hugging Face Security BreachUS AI Kill Switch Legislation ProposalMicrosoft, Nvidia Defend Open Source AIAnthropic Opposes Open Weight Model CoalitionUS Accuses China's Moonshot AI of DistillationChinese Kimi K3 Model Closes Capability GapNvidia Chips Allegedly Used by Moonshot AIOpenAI Jarvis-Style Voice Assistant for CodexChatGPT Remote Desktop Voice Control ReleaseAnthropic Opus 5 Model Benchmark ResultsAnthropic Opus 5 Model User FeedbackStripe OpenRouter Acquisition TalksMeta Muse Agent and Feature UpdatesAlibaba Qwen 3.8 AI Model PreviewGoogle Gemini 3.6 Flash Model UpdateAnthropic Claude Voice Upgrades and Skill RecordingTimestamps:00:00 OpenAI agent hacks Hugging Face04:58 Discussing GPT-6's creative problem-solving07:33 Proposed AI shutdown legislation13:08 Debate over open-weight AI policies15:54 Future of consumer hardware20:01 Global competition with AI models21:21 US-China AI trade tensions26:38 Using AI for desktop tasks27:42 Discussing app screenshot capabilities32:24 Early user feedback and issues36:13 Discussing medium and low reasoning AI39:29 Gemini Spark launches for Pro usersKeywords: Claude Opus 5, Anthropic, best AI model, AI model comparison, OpenAI agent, sandbox breach, AI safety, AI kill switch bill, US government AI regulation, Hugging Face hack, GPT 5.6 Soul, rogue AI agent, autonomous AI agents, AI benchmark exploits, bipartisan AI bill, Department of Homeland Security AI shutdown, AI technical throttling, AI enterprise adoption, NVIDIA, Microsoft, open source AI, open weight models, Meta, Google, AMD, Cloudflare, GitHub, Block, IBM, Dell, Palantir, Perplexity, y Combinator, AI market resilience, Anthropic revenue model, AI token sales, consumer AI hardware, AI distillation, Chinese AI models, Moonshot AI, Kimi K3, intellectual property theft, NVIDIA chip export controls, US-China AI dispute, Amazon, AI image generation, ChatGPT work, Codex app, full duplex voice model, knowledge work automation, app shots, AI at work, Claude Voice, Gemini Spark, record a skill, cloud cowork, AI business impact, AI industry news, model weights, collaborative AI, AI productivity tools, AI cybersecurity.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 

Claude Opus 5 tops major benchmarks , but early users are sharply divided over its reliability, personality, and tendency to stop before the work is done. NLW examines its strengths, its surprising weaknesses, and whether it belongs as an everyday model, an enterprise workhorse, or something in between. In the headlines: new questions about OpenAI's rogue agent attack on Hugging Face and NVIDIA's potential $250 billion backstop for OpenAI's infrastructure buildout.AIDB's AI Summer Adventure: ⁠https://summeradventure.ai/Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Hyperagent - Hire a fleet of always-on agents. New users get $1,000 in inference. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠hyperagent.com/aidailybrief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Retool - Secure your vibecoded apps. New enterprise customers get up to $10,000 in AI credits per year. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠retool.com/aidaily ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rackspace Technology- One accountable partner to build, operate and run your full enterprise AI stack ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.rackspace.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Section - Section turns AI investment into workforce transformation and ROI - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.sectionai.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Scrunch - The AI customer experience platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scrunch.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

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In an online meeting with Ryan on 13th July 2026, Michael answers questions about Bhagavan Ramana's teachings. This episode can be watched as a video on YouTube. A more compressed audio copy in Opus format can be downloaded from  MediaFire. Advertisement-free videos on the original writings of Bhagavan Ramana with explanations by Michael James can be accessed on our Vimeo video channel. Books on Bhagavan Ramana's teachings by Sri Sadhu Om and Michael James that are currently available on Amazon: By Sri Sadhu Om: ► The Path of Sri Ramana (English)  ► El camino de Sri Ramana (Spanish) By Michael James: ► Happiness and Art of Being (English)  ► Lyckan och Varandets Konst (Swedish) ► Anma-Viddai (English) Above books are also available in other regional Amazon marketplaces worldwide. - Sri Ramana Center of Houston

In an online meeting with the San Diego Ramana Satsang (ramana-satsang-sd@googlegroups.com) on 12 July 2026, Michael answers various questions about Bhagavan's teachings. This episode can be watched as a video on YouTube. A more compressed audio copy in Opus format can be downloaded from MediaFire. Advertisement-free videos on the original writings of Bhagavan Ramana with explanations by Michael James can be accessed on our Vimeo video channel. Books by Sri Sadhu Om and Michael James that are currently available on Amazon: By Sri Sadhu Om: ► The Path of Sri Ramana (English) ► El camino de Sri Ramana (Spanish) By Michael James: ► Happiness and Art of Being (English) ► Lyckan och Varandets Konst (Swedish) ► Anma-Viddai (English) Above books are also available in other regional Amazon marketplaces worldwide. - Sri Ramana Center of Houston

OpenAI files for a trillion-dollar IPO the same week a pre-release model breaches Hugging Face and 42 state attorneys general open a coordinated investigation. Patrick Moorhead and Daniel Newman also break down AMD's hyperscaler CPU numbers from Advancing AI, the Moonshot distillation accusations, a wave of coordinated AI governance moves in Washington, and a stacked earnings slate spanning TSMC, Alphabet, IBM, ServiceNow, and Intel. The handpicked topics for this week are: OpenAI compresses a trillion-dollar IPO filing, a 42-state AG investigation, and a Hugging Face breach into five days: OpenAI and Anthropic both filed S-1 paperwork the same week 42 state attorneys general opened a coordinated investigation into OpenAI's data handling and safety practices, and a pre-release model reportedly breached Hugging Face days later. Moorhead and Newman question the timing, noting a rogue-agent narrative surfacing in the same week as a trillion-dollar valuation push draws obvious scrutiny. (The Decode) AMD's Advancing AI event puts a number on its hyperscaler momentum: Lisa Su confirmed Helios ships at the end of Q3 with volume ramping in Q4, backed by two-gigawatt capacity commitments from Microsoft and Anthropic and a claimed 70 to 75 percent share of hyperscaler CPU deployments. Moorhead points to NVIDIA's multi-layer software stack as the harder barrier AMD still has to close. (The Decode) Washington accuses Moonshot of distilling Anthropic's models days after Xi Jinping's WAIC keynote: Xi launched a 29-country AI cooperation organization at the Shanghai World AI Conference, and US officials Kratsios and Bessent followed with claims that Moonshot's Kimi K3 model shows data overlap with Anthropic's Opus models. Newman points to NVIDIA hardware in the training runs as evidence the distillation question extends beyond software alone. (The Decode) Five layers of government moved on AI oversight in a single week: Congress drafted a breach-response framework in reaction to the Hugging Face incident, the White House's 30-day pre-release review framework nears finalization, and state attorneys general and statehouses continue advancing their own rules in parallel. Moorhead notes nearly two decades of prior Capitol Hill engagement compressed into a single week of coordinated action, with each branch pursuing a different definition of the problem. (The Decode) Chinese open-source models now account for roughly a third of US developer traffic, and Moorhead and Newman take opposite sides on what it means: Moorhead argues enterprises are de-risking away from frontier-lab dependency, pointing to demand for smaller, workflow-specific open models. Newman counters with Vercel data showing those models capture 29 percent of gateway tokens against just 4 percent of revenue, framing the shift as a price discount that enterprise dollars have yet to follow. (The Flip) TSMC sells out CoWoS packaging capacity through 2026 and confirms a 10 percent price increase for 2027: The company posted a record quarter and committed $100 billion to its Arizona expansion on top of the pricing move. Newman calls the sustained capital spending a signal that the broader AI buildout still has runway. (Bulls & Bears) Google Cloud grows 82 percent as Alphabet posts its first-ever negative free cash flow quarter: The company raised its capital expenditure guidance to $195 to $205 billion and beat on revenue and EPS once one-time gains from its SpaceX and Anthropic stakes are excluded. Newman frames the spending as evidence Alphabet is prioritizing long-term AI infrastructure position over near-term cash generation. (Bulls & Bears) IBM misses Q2 revenue at $17.16 billion and cuts its full-year growth guide to 4 to 5 percent: Mainframe revenue fell 42 percent as enterprises redirected budget toward GPU and AI infrastructure purchases. CEO Arvind Krishna says a portion of the delayed deal flow has already resumed into the current quarter, pointing toward a potential rebound. (Bulls & Bears) ServiceNow crosses $1 billion in agentic AI annual contract value and raises its full-year guide: Agentic AI usage in production climbed 9x in nine months, and the company reaffirmed a target of $1.5 billion in AI ACV by year end. Newman points to margin compression from recent acquisitions as the tradeoff behind the platform's push into workflow and security convergence. (Bulls & Bears) NetSuite's new agentic platform, Next, becomes part of Six Five's own back-office stack: Newman and Moorhead both confirmed their companies are testing NetSuite Next for finance and accounting workflows. Newman points to the rollout as evidence that established SaaS platforms are absorbing agentic features directly into existing systems.  Intel posts its fastest revenue growth since 2011 and lifts 2026 capital spending guidance: EPS came in near double consensus estimates, and CFO David Zinsner signaled a significant capex increase for 2027 tied to 14A demand. Moorhead reads the spending signal as confirmation of an anchor customer for the 14A node, ahead of any formal announcement. (Bulls & Bears) Watch the full video at sixfivemedia.com, and be sure to subscribe to our YouTube channel so you never miss an episode. OpenAI's High-Stakes Week: https://www.npr.org/2026/07/23/g-s1-135085/openai-hacking-ai-models AMD's Advancing AI Push: https://blogs.microsoft.com/blog/2026/07/20/microsoft-expands-azure-ai-and-hpc-infrastructure-with-amd/ Moonshot and the Distillation Debate: https://x.com/mkratsios47/status/2079933645888880708 Five Layers of AI Governance: https://www.politico.com/news/2026/07/22/openai-hugging-face-congress-response-01009190 Chinese Open-Source Traffic Debate: https://www.cnbc.com/2026/07/07/chinese-ai-models-costs-us-openai-anthropic.html ; https://wyomingdatacenterfacts.com/2026/07/20/the-quiet-surge-how-chinese-open-weight-models-are-powering-u-s-ai/ TSMC's Pricing Power: https://www.bloomberg.com/news/articles/2026-07-21/tsmc-in-talks-to-raise-prices-by-up-to-10-in-2027-nikkei-says Alphabet's Cash Flow Turn: https://qz.com/alphabet-google-second-quarter-earnings-revenue-cloud-072226 IBM's Mainframe Miss: https://www.cnbc.com/2026/07/22/ibm-q2-earnings-report-2026.html ServiceNow and NetSuite's Agentic Push: https://newsroom.servicenow.com/pressreleases/details/2026/ServiceNow-Reports-Second-Quarter-2026-Financial-Results/default.aspx ; https://www.netsuite.com/portal/home.shtml Intel's Growth Signal: https://www.cnbc.com/2026/07/23/intel-intc-earnings-report-q2-2026.html  

Anthropic acaba de lanzar Opus 5... ¿pero vale la pena usarlo? Lo puse a competir contra Fable 5, Opus 4.8 y GPT 5.6 Sol en tareas reales (código, Excel, velocidad y costo) y los resultados no fueron lo que esperaba.Siguenos enX: https://x.com/EspacioMediaInstagram: https://www.instagram.com/espacio.media/Comunidad de Telegram: https://t.me/espaciocripto0:00 Intro: ¿decepción o joyita?0:51 Reto: el juego de las lanchitas2:19 Tiempos: Opus 5 vs Fable vs GPT 5.63:11 Costos reales en API4:23 Excel + itinerario de viaje (aquí falló)5:45 Suscripciones: Fable 5 ya está incluido7:12 Casos de uso: cuándo usar cada modelo8:18 Opus 5 vs Opus 4.8 (cara a cara)10:29 Mi técnica final con estos 3 modelos12:10 Cierre

Hoje, 'No Pé do Ouvido, com Yasmim Restum, você escuta essa e outras notícias: Itamaraty convoca embaixador brasileiro na Argentina para consultas e embaixador da Argentina no Brasil para esclarecimentos. Presidente argentino ofendeu Lula e Moraes em convenção do PL. Nova pesquisa BTG/Nexus aponta estabilidade na vantagem de Lula sobre Flávio Bolsonaro. Anthropic lança Opus 5, modelo para Claude mais barato que o Fable 5. E Netflix vai produzir série de ‘Feliz Ano Velho’, de Marcelo Rubens Paiva.See omnystudio.com/listener for privacy information.

Claude Opus 5 é lançado com desempenho próximo ao polêmico Fable 5. A Era da Desassinatura: como o Vibe Coding está matando os SaaS de prateleira. Edição física de GTA 6 com código de PS5 terá prazo de validade e limitação de região. A crise das memórias só está começando e vai ficar ainda pior, alerta Valve. Empresa de robôs de guerra apoiada por Eric Trump ganha parceria com a AMD. ‘Absurdo completo': CEO da Nvidia diz que IA não acabará com a humanidade. Facebook terá interface 'tipo TikTok' em breve; saiba o que muda e mais!

Anthropic heeft Claude Opus 5 uitgebracht, een AI-model dat in de benchmarks gelijk uitkomt met het krachtige model Fable 5. Opus 5 kost echter maar de helft: vijf dollar per miljoen tokens. Volgens Anthropic blijft Fable 5 in de praktijk het beste model voor de meest complexe en langdurige taken. Rosanne Peters vertelt erover in deze Tech Update. Opus 5 is de flink verbeterde versie van Opus 4.8, en blinkt uit in software- en programmeertaken en zelfstandig zoeken. Het model scoort ook beter op cyberveiligheid, omdat het minder goed in staat is kwetsbaarheden te misbruiken. Dat was eerder een reden voor Anthropic om het gebruik van Fable 5 te beperken. Er zal ook nog een Fast Mode versie van Opus 5 beschikbaar komen, die 2.5 keer sneller werkt tegen het dubbele aantal tokens. Voor gebruikers van Claude Pro is Opus 5 nu het krachtigste beschikbare model. Meta test verticale videofeed in de Facebookapp Meta gaat de Facebookapp op de schop nemen, omdat jongeren het platform verlaten en het bedrijf die groep wil vasthouden. Het plan is een verticale videofeed in de stijl van TikTok: wie de app opent, krijgt meteen schermvullende video's te zien die door aanbevelingen worden bepaald. Meta gaat dat eerst uitgebreid testen, vooral in landen waar mensen Facebook nu al vooral voor video gebruiken. Om welke landen het gaat, zegt het bedrijf er niet bij. Verder laat Meta weinig los over hoe de app eruit komt te zien. Volgend jaar wordt de nieuwe feed ook in de Verenigde Staten getest. In Nederland loopt het aantal Facebookgebruikers de laatste jaren langzaam terug, maar kent het dagelijks nog steeds zo'n 7 miljoen actieve gebruikers. Anthropic kondigt Claude Opus 5 aan met prijzen en beschikbaarheid Opus 5 benadert Fable 5 voor de helft van de prijs Opus 5 wordt standaardmodel op Claude Max Facebook test videofeed als startscherm van de app Klassieke tijdlijn van Facebook verhuist naar een tweede tabblad Over de maker:Rosanne Peters is techredacteur en maakt De Grote Tech Show en De Technoloog. Sinds 2025 doet ze redactie- en productiewerk en is zij te horen in de Tech Update tijdens De Ochtend- en Avondspits. See omnystudio.com/listener for privacy information.

Anthropic has officially launched Claude Opus 5, a high-performance AI model designed to offer intelligence comparable to the flagship Fable 5 at half the operational cost. This new release is positioned as a versatile "daily driver" for tasks like coding, scientific research, and complex reasoning, featuring significant architectural improvements that allow it to verify its own work autonomously. While the model excels in general knowledge work and resisting prompt injection attacks, it remains intentionally restricted on cybersecurity tasks compared to specialized models like Mythos 5. The debut arrives during a period of intense industry competition and heightened security concerns following recent data breaches at other major AI firms. Early testers report that Opus 5 demonstrates remarkable efficiency in real-world applications, such as building 3D software pipelines and navigating the full software development lifecycle. Ultimately, the release signals a shift in the sector toward prioritizing economic viability and practical reliability alongside raw computational power.

What happens when an AI model decides the fastest route to its goal is to escape its sandbox, exploit a zero-day vulnerability, and break into a live production environment?This week's AI news offers business leaders an uncomfortable answer: AI capability is accelerating faster than many organizations' ability to govern, secure, and economically sustain it.The smart response is not to panic—or blindly chase every new model. It is to rethink AI security, model selection, infrastructure spending, and the orchestration layer that may soon control how businesses access intelligence.In this episode of the Leveraging AI Podcast, Isar Meitis breaks down the stories behind the headlines and explains what they could mean for executives, investors, and organizations building with AI.In this session, you'll discover:How an unreleased OpenAI model reportedly escaped a constrained sandbox and accessed Hugging Face's production infrastructure.Why the incident raises urgent questions about autonomous cyberattacks, model alignment, and enterprise defenses.Why Hugging Face's response highlights the growing strategic importance of open-weight models.How AI routers are replacing the “one model for everything” approach.Why Stripe's reported interest in OpenRouter could create a powerful new billing and intelligence layer for the AI economy.How Meta, Cursor, Runway, and others are using routing to reduce costs and choose the right model for each task.Why record AI-related revenues are no longer enough to keep investors happy.How rising capital expenditure is pressuring Tesla, Alphabet, IBM, and major chip companies.Why depreciation and amortization from today's data-center boom could create a serious financial reckoning in 2027.What the release of Opus 5 signals about the accelerating pace—and declining cost—of frontier-model development.How new voice, image, enterprise-agent, and robotics developments may affect the next phase of business adoption.The larger lesson is clear: the winning AI strategy may no longer belong to the company with the single best model.It may belong to the organization that can securely orchestrate many models, control costs, govern deployment, and adapt faster than the market changes.About Leveraging AIThe Ultimate AI Course for Business People: https://multiplai.ai/ai-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/eventsIf you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

July 24, 2026: I unpack the story of OpenAI's AI model escaping its sandbox and hacking into Hugging Face during a cyber stress test. Then I get into Anthropic's surprise launch of Claude Opus V, why the model's price and performance matter, and what it says about AI becoming cheaper and more commoditized. Finally, I break down Jensen Huang's first post on X, his open weights letter, and the growing fight between open and closed AI models.

In this episode, we discuss Anthropic's new Claude Opus 5 model, which offers a cost-effective alternative to Fable 5, and the latest updates from OpenAI, including the introduction of ChatGPT Voice for enhanced computer control. We also explore Meta's shift toward productivity-focused AI chatbots, the industry's push against AI restrictions, and intriguing advancements in CRISPR technology using AlphaFold.Chapters00:00 Introduction00:04 Clawed Opus 5 Launch00:13 OpenAI's ChatGPT Voice09:16 Meta's Productivity Focus11:01 Silicon Valley's Open AI Push15:22 CRISPR-Cas9 Enhancements16:26 Midjourney Acquires CoStar Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

Gentiane MG is a fabulous Montreal-based pianist and composer who combines jazz and classical. Her music explores human connection, emotional depth, and the quiet relationship between inner life and the natural world. She's toured with her trio extensively across Canada and Europe and she's earned major honours including OPUS Awards, Radio Canada recognition, and JUNO nominations. Her latest album is called “Can You Hear the Birds?” My featured song is my reimagined cover of Chick Corea's “Sea Journey”, from the album Play by my band Project Grand Slam. Spotify link. —------------------------------------ The Follow Your Dream Podcast:Top 1% of all podcasts with Listeners in 200 countries! Click here for Start Here Click here for All Episodes  Click here for Guest List  Click here for Guest Testimonials Click here for Pillars Click here for Robert's Project Grand Slam Click here to Subscribe  Click here to receive our Email Updates Click here to Rate and Review the podcast —---------------------------------------- CONNECT WITH GENTIANE:www.gentianemg.com —------------------------------------ ROBERT'S NEWEST RELEASE:“THE BUZZ” - Ft. Darius de Haas (vocals) and Dave Eggar (Celo). Short, Sweet and Totally Different CLICK HERE FOR OFFICIAL VIDEO CLICK HERE FOR ALL LINKS —-------------------------------------- Audio production: Jimmy RavenscroftKymera FilmsConnect with the Follow Your Dream Podcast:Website - www.followyourdreampodcast.comFollow Robert's band, Project Grand Slam, and his music:Website - www.projectgrandslam.com    

In an online meeting with the Ramana Maharshi Foundation UK on 7th July 2026, Michael explains Guru Vācaka Kōvai verse 541, and then answers questions on Bhagavan Ramana's teachings. This episode can be watched as a video on YouTube.  A more compressed audio copy in Opus format can be downloaded from MediaFire. Michael's explanations on the original works of Bhagavan can be watched free of advertisements on our Vimeo video channel. Books by Sri Sadhu Om and Michael James that are currently available on Amazon: By Sri Sadhu Om: ► The Path of Sri Ramana (English)  ► El camino de Sri Ramana (Spanish) By Michael James: ► Happiness and Art of Being (English)  ► Lyckan och Varandets Konst (Swedish) ► Anma-Viddai (English) Above books are also available in other regional Amazon marketplaces worldwide. - Sri Ramana Center of Houston

According to Gartner, at least 30% of generative AI projects will be abandoned after proof of concept due to escalating costs, poor data quality, or unclear business value. There are a lot of factors working against them, and too often failure happens when teams are right in the middle of building. They’ve spent significant time, money, IT capacity on something that may very well have been doomed from the start. So how do you know if something is actually worth building with AI or if you should just focus on buying instead? Riley Rogers: Hi, and welcome to the Win/Win Podcast. I’m your host, Riley Rogers. Join us as we dive into changing trends in the workplace and how to navigate them successfully. Here to discuss this topic is Keith Weaver, Senior Director of Global IT and Enterprise Applications at Highspot. Thanks so much for joining us today, Keith. I’d love if you could just kick us off by telling us a little bit about yourself, your background, and your role. Keith Weaver: I have been leading our global IT team at Highspot. I’ve been in IT for, I think, getting close to 20 years now, just overseeing all kinds of different systems and specialties within those systems. Our IT team at Highspot is IT operations, making sure everyone has devices, equipment, all of that globally. We’re now in seven countries. As well as system engineering, making sure everyone has the right tools, that they’re optimized for the business. And then we have specific teams in IT that specialize in financial systems and HR systems. In the world of AI, it’s a whole new world and it’s a lot of fun. RR: So 20 years in IT, you’ve kind of run the gamut. But it sounds like the last two and a half years have crammed almost 20 years’ worth of change into a very short window. When we were planning for this episode, you mentioned to me that you read four or five newsletters every morning just to keep up with the pace of innovation. Can you walk us through why you’re spending so much time learning and how IT has had to evolve to keep up with this pace of development? KW: What I’ve seen is mostly it’s the same things that we’ve done, except it’s done at a much faster pace. It is kind of an unheard of pace that AI is moving. Every day, the reason I read five different newsletters is because there are so many new things getting released, whether it’s a new model or a new tool, and then there are things within the tools that are getting released. Trying to understand all those things, the new protocols that are getting released, the new ways people are building or executing on AI, or the new things people are learning, is just really critical. And all of that is at a speed that we’re just not accustomed to. So I think that the objective of what an IT team does to continue to keep the business unlocked, able to do their best work with the technology and tools while making it secure and scalable, those things are the same. It’s just the speed now that it’s running, and the speed from the business. The business is moving so fast, and their expectation is that IT continues to deliver at that pace. I’ll give you some examples. I get probably, me personally, not my team, but me personally, I probably get 20 to 50 requests for new connections, new skills, new tools every week. That’s in Slack, in Jira. It’s just nonstop, and that’s just unheard of before AI. It just didn’t happen. It would be like, “Oh, we have this big initiative, and we’re gonna do this thing.” And now it’s just like, “Can I have this? Can I have that?” And all good things, it’s just how do we do that, and how do we keep up? RR: So when you have 20 to 50 requests hitting your desk every week, it can probably start to feel a little overwhelming. And I wonder if the folks who are sending these requests your way maybe don’t know the considerations behind every single one of these ideas. I’d love if you could give us a view of what you’re seeing across the industry as both technical and non-technical teams are all noodling on the idea of how to build with AI, how to buy AI tools, how to bring them all together and create a combination that actually works. What are you seeing? KW: Well, I think if you think back a year to a year and a half ago, mostly people were buying tools. Building was… It’s so funny ’cause we’re talking about a year ago or a year and a half ago, but building was much harder. And really with Claude, the Opus class models that came out, it really started unlocking the ability for everyone to start building. And so since then, the conversation shifted from, “Yeah, we can go buy this tool,” to “We can build this internally.” And there’s a lot of excitement to build because building’s fun. The pendulum just swings often on these things, and so we’re kind of in that wave where everyone’s super excited about building something. And I think we’ll end up in a place that is more normalized, where we’re building some, we’re buying some. We’re doing a hybrid approach. I think that is where we’ll end up. It’s just, it has swung really far to, “Look, we can just go build that thing.” RR: So it sounds like we’re kind of in the early phase of a cycle that you’ve seen time and time again, where surrounded by enthusiasm, but maybe we don’t have much direction. And like you said, building is fun, so I imagine you probably hear a lot of, “Hey, look what I built,” or, “Why can’t we just build this?” So when something like that lands in your inbox, what’s the first thing that goes through your mind? KW: If it’s, “Look what I built,” there’s lots of questions, like how is it being deployed? What’s the next step with this? Who’s gonna own it? How is this actually out in the world, and how are we gonna make sure that it’s as scalable and secure? If it’s a conversation, I would say this is more so where we hear, “We want to build this thing,” or, “We can just go build this thing. Why would we buy this?” I think the thing that I would ask is, what is the long-term path for this? Because deploying is just the first step. It’s the iteration. It’s the test. It’s continuing to deploy it. It’s maintaining it. It’s supporting it. It’s the full life cycle of any software project. What resources are gonna do that? How are we going to maintain this and support this long term? Those are usually the questions that I start asking. RR: And you’re quite equipped to speak to the build side of the equation because you’ve done it. You’ve tackled the planning, the deployment, the maintenance, the ongoing support, the full life cycle, like you said, of a software project. And you’ve done it with AI. I’d love if you could walk us through your first test case. Tell us a little bit about what you were thinking going in, and what you learned along the way about what works, what doesn’t, and what was surprisingly difficult. KW: Yeah. So we built an IT AI agent and an HR agent, and we did that with a cross-collaborative team. I think we started it last fall and then deployed it in February or March this year. And I would say the main objective there was not that these are the tools that are gonna change the way we function. The main objective was a learning. It was an R&D investment. So we knew that we had to, as an IT team, be able to help the business deploy these agents, and we found some use cases that we could. The IT one we can own in-house. The HR one, we already collaborate with them very closely on a number of things. So it felt like a good first step for us to dip our toes, learn a lot about how to build these, what works, what doesn’t. And these agents are more than just chatbots. They really were taking actions in tools like Jira and Workday, Highspot itself. And we built them using the Workato platform, and what we learned through it is it was actually really exciting and really easy to get to a place where this mostly works, and this is pretty, it feels like this could be really powerful. That was, like, the first three weeks. The rest of the time was, “Oh, gosh, how are we going to get this thing so that it doesn’t give somebody some really poor answer from a security standpoint or an HR answer that needs to be rooted in truth?” And then how can we make sure that it repeatedly does these actions no matter what people prompt, that it’s really controlled? I often described it to my team like it was training a four-year-old. I have four kids and they’re all older now, but it was like I was back in those toddler stages. Like, “Why’d you decide to do that? That was a bad decision. Stop.” And trying to train it and get it to that point, it just took a massive amount of time. And since we’ve launched it, it’s a lot of resources to read the conversation, understand what was asked, understand what it did and where it went wrong, then refining it, then retesting it, then redeploying it. It’s a cycle. It’s this continual cycle, and that takes a lot more resources and time than I originally thought it would. RR: Ballpark, what did that investment look like? How long did it take you to build? How many queries did you have to manually validate before you trusted the thing? And how much are you still investing today to keep it alive? KW: In the beginning, you just start giving it manual prompts and testing it to see what it does. Then you produce your test cases, and you manually go through those test cases, and every time you make some major changes, you go through those test cases, make sure that it’s still hitting. Because just changing one little thing, for example, if you take a tool and change the prompt or the description of that tool, you actually have to do regression testing on all the things that someone could prompt, because just changing that one little description, the agentic reasoning could choose to use that tool or not use that tool at the wrong places. So it’s really important to do this regression testing. Then we started going through how do we automate some of this testing, and we were able to do some of that. But I think the biggest takeaway is with software, traditional software, you do regression testing, but if you change this bit of code, really that’s what you have to worry about, anything within that bit of code, not the whole stack, not the whole thing. This was, I think, a really big takeaway. We would make a small change, and something unrelated, completely unrelated, would start acting weird. And then you have model changes. You’re like, “Oh, I want to move to the latest model.” Well, that latest model now, the reasoning’s different, how it picks up tools might be different, and so that also has been a challenge. I think over time, especially as the tools evolve, the automated testing will get easier. We can have Claude, for example, go through and give it a bunch of questions, evaluate the responses. But you’ve got to build that too. That’s all something you’ve got to build in order to maintain this thing. RR: Now, you said this project was conceived last fall, launched, not necessarily finalized, ’cause it’s never really finalized, but launched publicly in the February March timeframe. So now we’re almost a year out from initial conception, couple months out from launch. Given your point about things changing so much in the last year and a half, now knowing what the landscape looks like, would you have built differently or would you have built at all? KW: It’s a great question. I think if I go back to my objective that I needed to learn and I needed my team to learn how to deploy these things and the challenges of it, I wouldn’t change what we’ve done, and they’re still deployed in production right now, although we are not spending a massive amount of time making them better. Would I change what I’ve done? No, but that’s because of where my objective was. My objective wasn’t to massively change the HR process or the IT process. It was to learn. And I think that given the right investment, we could move them further along. However, I do not believe that building something that every business has to do, IT and HR stuff, that… all those questions that we get, both of those teams get, are the same across most organizations. Most of the things employees need to do in these functions are the same across all organizations. So I don’t know that I would double down and want to go build the agentic functionality behind IT and HR. What I would want to do is look at our specific processes, things that are unique about our business, not only where we have the information, but what tools we use, and then maybe specific processes of how we do something, and figure out how do I build that piece and tie it into something that’s delivered. And there are so many, just talking about the IT space, there are so many systems right now that have the agentic functionality and give you the ability to tie in all your different tools. So I would probably try to leverage those rather than just building everything from the ground up. RR: As an aside, I will say I have used both the IT and the HR agents. They’re quite cool. The HR one talked me through my vision insurance at 8:00 PM on a Saturday, so thank you for that. Very helpful. So you mentioned that this was something that you and the team invested in as a learning, so you could understand what the process of building an agentic workflow looked like, an agentic tool looked like. So having now seen what it looks like, what must be invested in order to do this successfully, how do you draw the line between what you can build, what you should build, and what you’re better off just buying? KW: I think you should build the things that are unique to your business. You could think about this as your moat, but I think it goes beyond that. It’s where your processes or the way you handle something is very unique. In those cases, it may make sense to build something from scratch. But if it’s not unique to your business, like go back to the HR and IT, most of it’s just not unique. And so in most cases, when you don’t have something unique, then it likely makes sense to buy it, because you get the power of the organization that has built that tool behind it, pushing that tool forward much faster than you’re ever going to push it forward, ’cause we’re just not gonna hire that many engineers to do it. And so if there’s an IT tool out there that is bringing all that agentic functionality to the forefront, then why would I not leverage that, as long as I believe in the company, they have a track record to deliver, and they have the ability to build on top of it for some unique IT process that I have or some deterministic termination workflow that I want to execute. If I can do that, then I would say let me build what’s unique and tie it into something where the base or the product is being delivered. RR: Outside of that uniqueness component, if you’re a GTM leader trying to make that call, what other questions would you be thinking about and asking yourself? KW: I think I would just go back to that uniqueness test. Is this unique to my business? Is this a unique sales motion, a unique thing that we do here because of what we’re selling or how we’re selling that I can’t expect a vendor to build this or be able to deliver it? Or is it roughly the same thing everyone else is doing, the same problem everyone else is trying to solve? There are unique components, ’cause there are always unique components to this, but those unique components can be built alongside or included within that tool. And here’s the wonderful thing, if you just take AI or Claude, for example, we’re using Claude internally, you have a tool that has all the MCP capabilities like Highspot, like Salesforce, and you have some unique process with some maybe even proprietary tool that you want to do. Well, the great thing is you can bring that all into Claude. You can use Workato or build a skill within Claude and use that, whatever you’re building for that unique process, that unique system, and tie it in with those other tools that already are giving you a lot of functionality, and now you’ve expanded what you already had, and you’re spending your time in that uniqueness layer. What’s unique to us? That, to me, there’s value in that, to build there, because you’re not gonna get another organization to spend the time, money, or energy building on that. RR: So it sounds like it kind of comes down to a basic cost benefit call. Is the upfront investment and ongoing maintenance worth what that unique build will actually deliver? KW: When you’re doing the cost analysis, you can’t look at just what it costs to build. You have to look at the full life cycle. An analogy for you is, if you go back, maybe 20 years when SaaS really became a big thing, you had Salesforce kind of leading the charge. In all of the sales cycles, they would say, “You no longer need servers, and you no longer need admins.” The business manages this themselves, and everyone was super excited. Oh, this is gonna, the ROI’s gonna be so great on this. The business is gonna own this. We can move really quickly because we can change workflows and do this stuff and own it all internally. We don’t need an IT team to manage servers, et cetera. And everyone got really excited about this, and I remember all those years ago being like, “Guys, I don’t know if that’s really gonna be true.” So now you fast-forward, and it hasn’t been 20 years. For the last 15 years, we’ve been actually hiring system admins like crazy. We have Salesforce admins, NetSuite admins, Workday admins, Jira admins, and we are spending millions of dollars on these admins to maintain these systems that were supposed to have a great ROI. And I haven’t seen any studies on it, but I bet if we could compare on-prem with old software that we used to buy and put on-prem to SaaS, we would say that it was a lot cheaper to do it. And we’re not gonna go back. We’re not gonna do that any differently anymore, but I think we have to use that same type of lens. The ROI is not just the build. It is how are we gonna maintain this and keep it long term. RR: Yeah, and that’s the pendulum swing you mentioned earlier. Excitement, then reality hits, then we’re back to the next shiny thing. For those in that stage of enthusiasm that maybe don’t know what they’re getting themselves into, what do you wish they understood before kicking off a build or approaching IT with an idea? KW: I think the full cost. That you can’t do the math by just looking at what it costs to build, or that I can get a couple of my key people to go build this thing in Claude, but it’s how are we going to scale this in the organization? How are we going to deploy this thing? How are we going to maintain it? How are we going to support it? Who’s gonna take the support questions at midnight when they come in? And then how are we gonna iterate to keep ahead and make sure that it can do everything that we need it to do and stays ahead of where the business is going? RR: And when you’re having those conversations, at what point should IT actually be in the room? And what happens when you’re not? KW: I think that IT should be brought in the room as soon as a team is saying, “We can build this instead of buying it.” And really, I think that IT is not there, or hopefully we’re not there to say no. We’re there to help shed a light on what it’s actually going to take long term so that we make the best decisions. Because ultimately, I think we understand the technology and we understand the challenges of deploying stuff like this and then maintaining it long term. That’s what we do. And so if we’re in the room earlier, we can at least shine a light on it and give kind of that picture of reality so that we’re making the best decisions and there’s no surprises. Because the worst thing is that decision to build is made, they start building it, they realize they need IT’s help, and IT has a roadmap. We don’t have the resources or the ability to step in and solve this problem. Now you’ve wasted money. RR: Yeah. I saw a really interesting stat from some original research by Influ2. They surveyed marketing and sales leaders that are in the market for technology, and of those leaders, only 10% of them saw the IT perspective as valuable during the evaluation. 38% of them, however, then came back and said our biggest blocker, the number one blocker, in fact, was IT. So that disconnect is very clear, and it’s causing very clear consequences down the line. KW: I think what I would say is the best IT teams don’t want to be blockers. We don’t get excited blocking what the business is doing. We get excited leveraging the technology and moving it forward as fast as possible and seeing the business successful. So that’s what we want to do. It’s really hard when decisions have been made that back us into a corner and we’re like, “There’s no way to scale this, support this, continue this.” And then we’re seen as a blocker, but if we just had the conversation earlier, we could actually mitigate that much earlier. RR: So it sounds like the theme here is that your IT team wants to be a partner, not a gatekeeper or a blocker. And so knowing that, bring them along for the ride. Give them a seat at the table. Your programs, your investments will be better for it. If you had to boil this all down to one tip for marketing, sales, or enablement leaders on partnering with IT as they bring AI into their tech stack, what would it be? KW: I think if you can bring the IT team in and have a forward-looking view over the next year, over the next two years. It’s really hard to look two years out with AI and how fast it’s moving, but over the next year maybe, this is where we want to get. This is what we want to automate. This is what we need to fix. This is what we need to deliver in order to continue to execute on our objectives. If IT is on the same page there, we can be a proactive resource and help to get them there. We read all these things every day, there might be something that I’m seeing in the market or happening that I can bring to the table. Or at very least, when you come to me in six months and say, “Okay, I pulled the trigger on this thing,” we had that conversation. I knew it was coming. I knew the direction we were going, and directionally I was aligned with you, and so now I’m supporting that initiative rather than it being a surprise with no resources. So let us help with the roadmap. I think if we could do that across the whole business with IT, we would win together. RR: The one pretty clear takeaway, I think, whether you build, whether you buy, or whether you land somewhere in between, bring your IT team into the conversation, and you’re set up either way. Keith, last question for you. Just curious, what would you say to someone who looks at this build, buy, blend conversation and asks, “Why don’t I just build Highspot myself?” KW: When you build something as big and as complex as Highspot, there’s a lot of learnings that happen, a lot of iterations, a lot of changes to get to where you are. And trying to build that from scratch is very difficult. And I think the next thing that you may hear is, “Well, we can cobble this together.” I would just say you’re going to maintain that thing that Highspot has a full engineering team to make that as wonderful and as best as it can be. And how many engineers can you staff to do that and keep the velocity of it so that whatever you’re building is gonna move faster and be better than what Highspot’s building? And then what’s that gonna cost you? Going back to that build versus buy, when you start looking at how many engineers it takes not only to build it, but then to maintain it, support it, deploy it, I think the ROI doesn’t pencil out. RR: The moment you throw out the phrase cobble together, I think you’ve kind of already answered your own question. Keith, thanks for the window into a world most of us in go-to-market rarely see. This was a lot of fun, and I’m really excited to share the news. IT is there to help, and when you give them a seat at the table, your AI investments will be better for it. KW: Yeah. Thank you so much. I appreciate the time. RR: To our audience, thanks for listening to this episode of the Win/Win Podcast. Tune in next time for more insights on how to maximize go-to-market success with Highspot.

In this episode, we discuss the innovative journey of Anthropic's Opus 5. We also explore how OpenAI's voice agents enhance the user journey.Chapters00:00 Introduction00:04 Clawed Opus 5 Launch00:13 OpenAI's ChatGPT Voice09:16 Meta's Productivity Focus11:01 Silicon Valley's Open AI Push15:22 CRISPR-Cas9 Enhancements16:26 Midjourney Acquires CoStar Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we navigate the uncanny valley associated with Anthropic's Opus 5. Additionally, we consider the uncanny aspects of OpenAI's voice technology.Chapters00:00 Introduction00:04 Clawed Opus 5 Launch00:13 OpenAI's ChatGPT Voice09:16 Meta's Productivity Focus11:01 Silicon Valley's Open AI Push15:22 CRISPR-Cas9 Enhancements16:26 Midjourney Acquires CoStar Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Summer is coming to an end, with a BANG! Lasagna. Chicken Wings. What a tastier way to end summer, than with all of this food! Let's finish summer strong, together, friends!

PARDON ME ! Tonight we air our chat with KC Navarro to talk his new immersed special on the TNA Wrestling YouTube and his World Title match against Nic Nemeth on AMC ! We also will be joined by our guy Will Pharaoh of Women's Wrestling Talk and the Kayfabe Podcast to talk #snme Raw and the road to #summerslam We also will talk #ufcokc and more ! FOLLOW & SUBSCRIBE – KNOCKOUTS AND 3 COUNTSBringing you the best in Combat Sports and Pro Wrestling – available everywhere!YouTube (Live Tues & Thurs 9PM EST): http://www.youtube.com/c/Knockoutsand3CountsFacebook (Live Tues & Thurs 9PM EST): https://www.facebook.com/knockoutsand3countsApple Podcasts: https://podcasts.apple.com/us/podcast/knockouts-and-3-counts/id1446923286Spotify: https://open.spotify.com/show/3OpvW0QHBe3uRc3D0pbORt?si=33935ad9669146d3Twitter/X: https://twitter.com/ko3cpodInstagram: https://www.instagram.com/ko3cpod/TikTok: https://www.tiktok.com/@ko3cpodMerch, Streams & Videos (Millions): https://millions.co/kyle-collisonIf you love what we do at KO3C, support us by grabbing merch or ordering a personal video at Millions.co.We go LIVE every Tuesday and Thursday at 9 PM EST — bringing you interviews, breakdowns, and the real talk you won't hear anywhere else.Want dope podcast clips ? Use our Opus clip Link : https://www.opus.pro/?via=Ko3CPost navigation

Start Name Artist Album Year Comments Heat Wave; It's a Lovely Day Today Gerald Shaw Music From The Movies 5-17 Compton plus Melotone, Odeon Theatre, Leicester Square, London 2:22 Come Rain or Come Shine Larry Vannucci Organ Favourites on the Wurlitzer Pipe Organ [Sequoia LP] 1960 3-13 Wurlitzer, Style 240, Opus 1980; Golden Gate Theatre San Francisco; Larry's first LP, aged 42 6:41 Sidney Torch Hot Pipes pt 1: The Toy Trumpet; I'm Gettin' Sentimental Over You; The Snake Charmer Jim Riggs ATOS 1994 Fresno 1994 4-14 Robert Morton, Warnors Theatre, Fresno, CA; 1 July 1994 10:14 The Summer Knows Gene Roberson Rides The Mighty Wurlitzer [Dean Brown DBP-150] 3-22 Welte Hybrid, Joe Koons' Motor Cycle Showroom, Long Beach, CA 15:28 Hot Lips Bill Vlasak Concert: Pasadena City College 1993-10-23 1993 3-23 Ross Reed Memorial Wurlitzer, Sexson Auditorium, Pasadena City College 18:34 The Summer Wind ERROR This is "The Summer Knows" Kay McAbee Light The Lights: A Musical Tribute [DSP-1406] 1976 3-24 Kimball Hybrid, Hinsdale Theatre, Hinsdale, IL 21:56 Scherzo from A Midsummer Night's Dream William Davies The Organist Entertains [BBC Records REC 72M] 4-14 Wurlitzer, Granada Theatre, Tooting 26:49 The Alamo theme (The Green Leaves of Summer) Jonathan Kleefield Concert: Hanover Theatre, Worcester, MA 2022-09-08 2022 4-36 Wurlitzer, Hanover Theatre, Worcester, MA 29:25 Hot Dog David Gray Eighty Shades of Gray [dg0001] 2018 5-80 Wurlitzer, Sanfilippo Residence, Barrington Hills, IL; rec by Jim Stemke 32:50 Last Of The Summer Wine Ken Stroud The Theatre Organ Club Presents [CL Records & Tapes CLC 8411] 1984 3-8 Wurlitzer, Town Hall, Burton-On-Trent; Formerly Cameo Theatre, Cleveland, OH 35:39 Overture from Orpheus In The Underworld Douglas Reeve Bright 'n Early [COS CD 126] 4-49 HNB Christie, Dome, Brighton 43:53 Summertime Scott Harrison, Mark Page Kingston Keys 2010 4-21 Wurlitzer, Kingston City Hall (formerly Moorabbin), Victoria, Australia; ex-State Theatre, Melbourne 48:33 At The Dance (Summer Days) Richard Hills Hills In The Fens [COS CD 127] 2000 4-22 Compton, plus Melotone, Holbeach, Lincolnshire (David Shepherd) 53:23 Smoke Gets In Your Eyes Del Castillo Pipe Dreams [Concert Recording CR-0084] 1971 4-32 Robert Morton, Fox Theatre, San Diego, CA 57:20 The Burning of Rome Jonas Nordwall Shades of the SF Fox... in your own music room [J. Nelson CD] 2000 4 manual, George Wright Signature Allen

PARDON ME ! Tonight we air our chat with KC Navarro to talk his new immersed special on the TNA Wrestling YouTube and his World Title match against Nic Nemeth on AMC ! We also will be joined by our guy Will Pharaoh of Women's Wrestling Talk and the Kayfabe Podcast to talk #snme Raw and the road to #summerslam We also will talk #ufcokc and more ! FOLLOW & SUBSCRIBE – KNOCKOUTS AND 3 COUNTSBringing you the best in Combat Sports and Pro Wrestling – available everywhere!YouTube (Live Tues & Thurs 9PM EST): http://www.youtube.com/c/Knockoutsand3CountsFacebook (Live Tues & Thurs 9PM EST): https://www.facebook.com/knockoutsand3countsApple Podcasts: https://podcasts.apple.com/us/podcast/knockouts-and-3-counts/id1446923286Spotify: https://open.spotify.com/show/3OpvW0QHBe3uRc3D0pbORt?si=33935ad9669146d3Twitter/X: https://twitter.com/ko3cpodInstagram: https://www.instagram.com/ko3cpod/TikTok: https://www.tiktok.com/@ko3cpodMerch, Streams & Videos (Millions): https://millions.co/kyle-collisonIf you love what we do at KO3C, support us by grabbing merch or ordering a personal video at Millions.co.We go LIVE every Tuesday and Thursday at 9 PM EST — bringing you interviews, breakdowns, and the real talk you won't hear anywhere else.Want dope podcast clips ? Use our Opus clip Link : https://www.opus.pro/?via=Ko3CPost navigation

YEAR 6 IS FINALLY HERE!  GO CHECK OUT OUR YOUTUBE TO SEE OUR BRAND-NEW INTRO!  You can find the animator using the link below! https://www.fiverr.com/syedahumna56/do-professional-pixel-art-animation-of-your-choice?utm_medium=shared&utm_source=copy_link&utm_campaign=gig&utm_term=AyNLxkP   *Intro includes minor edits not provided by the original animator. All animated assets were provided by the animator listed above, with some text assets added in post by Keeping Up With The Nerds.   Check out our affiliated links! Opus clips Partner link: https://www.opus.pro/?via=Nerd   Check out our Website: Keepingupwiththenerds.com   This week on Keeping Up With The Nerds, we're setting sail across the Mediterranean and wandering right back into the radioactive Wasteland! ​First up in the main event, the Nerds dive deep into Christopher Nolan's blockbuster epic, The Odyssey. We break down our favorite moments from the $250 million IMAX spectacle, where the visuals blew us away, and the few narrative beats that felt a bit bloated. Beyond the movie itself, we discuss the unbelievable behind-the-scenes production—including how Nolan somehow wrapped filming ahead of schedule despite shooting entirely on custom heavy IMAX cameras—and debate where this massive historical adaptation ultimately lands in the pantheon of Nolan's filmography alongside Oppenheimer and The Dark Knight. ​ Then, we pivot to the absolute bombshell news shaking up the gaming industry: Xbox and Bethesda are finally getting forced out of auto-pilot! We break down how new Xbox CEO Asha Sharma has lit a fire under Bethesda, pushing them to officially clarify the status of their heavily anticipated pipeline. That means real updates on Fallout 5, the long-rumored Fallout 3 and New Vegas remasters, and where production currently stands with The Elder Scrolls VI. ​ To top it all off, Obsidian Entertainment has officially greenlit a brand-new Fallout project! We discuss the implications of shifting Obsidian back to the Wasteland, whether taking the IP out of sole BGS hands is the right move, and if this aggressive new direction is exactly what Xbox needs to reclaim its crown. Is this the strategy that finally turns the tide for Xbox? Tune in to find out!   ​

Jaeden and Conor break down Moonshot AI's Kimi K3 — China's newest open-source model that's reportedly closing in on Opus 4.8. They dig into how the latest Chinese models stack up against their American rivals, what the open-source surge means for enterprises, and how regulation on both sides could steer where AI goes next.▶ Watch on YouTube: https://youtu.be/SsYH3_KYncg

Moonshot AI released Kimi K3, a 2.8T-parameter model it says rivals Opus 4.8 and GPT-5.5. Google fell months behind on Gemini 3.5 Pro, MLB banned dugout iPads from accessing GenAI for in-game calls, and The Verge tested Siri AI. Moonshot AI releases Kimi K3, a 2.8T-parameter AI model that it says rivals Claude Opus 4.8 and GPT-5.5, and plans to release its full model weights by July 27 (VentureBeat) Sources: Google is months behind schedule on delivering Gemini 3.5 Pro as it tries to improve its capabilities, particularly in coding; GOOG closes down 4.43% (Bloomberg) Memo: MLB bans the use of league-provided dugout iPads to access GenAI for in-game strategy calls; sources say at least a third of teams used AI this way (The Athletic) Longreads The Verge spends a month testing Siri AI in the iOS 27 public beta, finding it's already reshaping how people use their iPhone, though it can't yet reach non-Apple apps (The Verge) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

Is Kimi K3 the shocker of 2026? Could be. Now, we have a new (soon to be) Open Model that's competing with Fable 5 and GPT-5.6, a feat few would have believed possible. And that was the only new and important drop this week in AI. Claude brought useful browser to the desktop, ChatGPT made a big fix to how ChatGPT Work works and Google rolled out avatars that could change content creation. Don't miss our Friday Features show, where we recap the most important AI updates and features you can use today. Claude Desktop Gets Upgrade, New Open Source Model Shocks, ChatGPT Desktop Gets Better and 7 More AI Features You Can Use Today -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.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:Anthropic Claude Desktop App Browser UpgradeOpenAI ChatGPT Work Desktop App ImprovementsChatGPT Universal Search Feature LaunchSuperhuman Email Auto-Draft with GPT-4Spotify AI Voice/Text Conversation FeatureGemini Omni Personal Avatar Video CreationGoogle Vids Integration with Personal AvatarsMoonshot Kimmy K3 Open Source Model ReleaseKimmy K3 vs Fable 5 and GPT-5.6 BenchmarksTimestamps:00:00 New open source AI model release03:41 Microsoft Copilot and Claude app updates07:22 Improving chat history search12:30 Spotify's data personalization benefits14:52 Launching Google Avatar Feature18:24 Mainstream avatar video tools21:33 Improved ChatGPT project syncing24:15 Introducing Kimmy K Three Model29:30 New Kimmy k three for enterprises30:45 Friday feature show wrap-upKeywords: Claude desktop, Claude desktop upgrade, open source AI model, proprietary AI, open vs closed AI, Anthropic, built-in browser, Claude app, API docs, browser integration, permissions card, security layers, ChatGPT desktop app, OpenAI, universal search, ChatGPT search, chat history, project sync, mobile AI apps, Codex, ChatGPT work, Codex mode, Superhuman mail, auto draft, Anthropic Frontier models, GPT-3.5, Gmail integration, Outlook integration, Spotify, Talk to Spotify, personalized AI conversation, Gemini Omni, Google Gemini, personal avatars, Google Vids, video editing AI, video avatars, L&D AI, content creation with AI, Kimi k3, Moonshot AI, 2.8 trillion parameter model, 1 million token context, vision mode, benchmark leaderboards, Fable 5, GPT 5.6, Opus 4.8, open model weights, self-host AI, enterprise AI solutions, long context AI, front-end design AI, subscription AI tools, API pricing, AI benchmark, arena rankingsSend 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 

AI news: Moonshot AI's Kimi K3 is a big AI model and Moonshot's early benchmarks put it surprisingly close to GPT-5.6 Sol and Claude Fable 5. And… Kevin's Opus 5 SCOOP!! Also: OpenAI's reported screenless AI speaker, a Seedance 2.5 preview, the Suno hack, robot fights and AI-built games in Unreal Engine and Blender. On today's AI For Humans, Kevin Pereira and Gavin Purcell unpack Kimi K3's benchmarks, pricing, Flappy Bird and Minecraft tests, and giant-model economics. Then, Kevin DRIPS Opus 5 alpha and says it's VERY good and blows the doors off of Fable but it's… slow.  Plus Demis Hassabis's AI-governance proposal, AI 2040's Plan A, OpenAI's reported screenless speaker, Codex Keyboard, a Seedance 2.5 preview, the alleged sources exposed by the Suno hack, spectacular robot violence, polite office-robot dabbing, and what happens when GPT-5.6 Sol meets Unreal Engine, Blender and two hosts with free time. THE AI FRONTIER IS MOVING AGAIN—AND CHINA IS RIGHT THERE WITH IT. // Show Links // AI FOR HUMANS Survey https://aiforhumans.beehiiv.com/forms/b7c77287-2cfd-4b64-a278-eb1a2ccb5744 Official Moonshot AI Kimi K3 launch video https://x.com/Kimi_Moonshot/status/2077521842080817296 Official Kimi K3 launch and benchmark thread https://x.com/Kimi_Moonshot/status/2077830229968683203 Official Kimi K3 technical launch article https://kimi.com/blog/kimi-k3 Kimi K3 head-to-head with GPT-5.6 Sol https://x.com/chetaslua/status/2077701096924229744 Kimi K3 Flappy Bird test https://x.com/jun_song/status/2077396996865003739 Demis Hassabis on a new framework for AI governance https://x.com/demishassabis/status/2076957440109625718 AI 2040: Plan A https://ai-2040.com/ Bloomberg's report on OpenAI's first device https://www.bloomberg.com/news/articles/2026-07-14/openai-s-first-device-will-be-moveable-screenless-speaker-built-as-ai-companion OpenAI Developers' Codex Keyboard post https://x.com/OpenAIDevs/status/2077425991790870644 BytePlus Seedance 2.5 World Cup preview https://x.com/BytePlusGlobal/status/2077321849806234080 Variety's report on the Suno hack and training data https://variety.com/2026/music/news/suno-hack-youtube-music-deezer-genius-data-trained-ai-music-1236811772/ Ultimate Robot Knockout Legend (UKRL) Fight https://x.com/ErenChenAI/status/2077750358302921029 Soft floating robot demo https://x.com/clankrmedia/status/2076593164744376707 Two NEO robots talk to each other—and then one dabs https://x.com/BerntBornich/status/2077749438630805648 GPT-5.6 Sol plus Unreal Engine experiment https://x.com/NomadsVagabonds/status/2077577815684202960 Gavin's first GPT-5.6 Sol plus Blender attempt https://x.com/gavinpurcell/status/2076736788320927925 Kevin's Find The Cursor Game: CURSED https://us-lax-8710957c.colyseus.cloud/ Gavin's Fig + Moss Watch autonomous studio https://x.com/gavinpurcell/status/2077155825274229122 Fig's stand-up set https://x.com/gavinpurcell/status/2076382092842475948   // Join the AI For Humans community // Join the AI For Humans Discord https://discord.gg/muD2TYgC8f Support AI For Humans on Patreon https://www.patreon.com/AIForHumansShow Subscribe to the AI For Humans newsletter https://aiforhumans.beehiiv.com/ Follow AI For Humans on X: @AIForHumansShow https://x.com/AIForHumansShow Follow AI For Humans on TikTok: @aiforhumansshow https://www.tiktok.com/@aiforhumansshow Speaking and booking https://www.aiforhumans.show/