Podcasts about developers

Hour 2 (10.01) A developer wants Tim's house, and under SB 79 they might be allowed to build big. Dean Sharp explains, plus why ADUs were 37% of all new homes in LA County last year. 7:05 Dean Sharp, The House Whisperer, is wearing a Kirkland fleece he got at Walmart, of all places. Then the real story: a developer is interested in buying Tim's house. SB 79, the Abundant and Affordable Homes Near Transit Act, took effect July 1, 2026. It lets developers build apartment buildings near qualifying rail and rapid-bus stops, even on single-family streets. Plus, the quiet ADU boom: LA County finished 10,230 ADUs in 2025, more than six times the number in 2018. 7:20 More with Dean on how ADU approval works. If your plans meet state standards, your city has to approve them within 60 days. There's no design review, no hearing, and no neighbor appeal. In the coastal zone, a new 2026 law puts coastal permits for ADUs on the same 60-day clock. 7:35 Walmart's new "Shop to Light" feature: tap an item in the app and its digital shelf label flashes so you can find it. Plus, SNAP changes started on Oct. 1. The maximum benefit rises to $306 a month for one person and $1,023 for a family of four, and states now pay 75% of the program's administrative costs. 7:50 HOAs: What do you actually get for your money? Tim also takes on being head of the household. Plus, a new Nature study co-authored by LA's City of Hope: transplant patients who ate more sweets while on strong antibiotics lost more of their healthy gut bacteria. Thanks for listening to Tim Conway Jr. on KFI!

Benjamin and Chance discuss the final Apple smart display rumors with a release for the ‘HomePad' rumored for October 13, although the small square screen form factor remains puzzling. Also, leaked photos of the iPad mini and HomePod mini suggest those long-awaited updates are also imminent, John Ternus apparently wants to make Apple more nimble, and Chance has thoughts on the new Apple Watch Readiness feature. And in Happy Hour Plus, Benjamin argues the case for adding Touch ID to the Apple TV remote. Subscribe at 9to5mac.com/join. Sponsored by Square: Get up to $200 off Square hardware when you sign up at square.com/go/happyhour. Sponsored by Notion: Learn more about how Notion can support your business, at notion.com/happyhour. Sponsored by Framer: The only free design tool that brings your ideas to the web. Visit framer.com/happyhour for 30% off a Framer Pro annual plan. Sponsored by Perplexity Computer: Start your free trial of Perplexity Computer today at pplx.ai/happyhour and experience the next phase of AI. Hosts Chance Miller @ChanceHMiller on Twitter @ChanceHMiller on Instagram @ChanceHMiller on Threads Benjamin Mayo @bzamayo on Twitter @bzamayo@mastodon.social @bzamayo on Threads Subscribe, Rate, and Review Apple Podcasts Overcast Spotify 9to5Mac Happy Hour Plus Subscribe to 9to5Mac Happy Hour Plus! Support Benjamin and Chance directly with Happy Hour Plus! 9to5Mac Happy Hour Plus includes:  Ad-free versions of every episode  Pre- and post-show content Bonus episodes Join for $5 per month or $50 a year at 9to5mac.com/join.  Feedback Submit #Ask9to5Mac questions on Twitter, Mastodon, or Threads Email us feedback and questions to happyhour@9to5mac.com Links Apple's HomePad smart home hub launching on Oct 13 with iMac G4 design – Bloomberg Leak reveals new design details about Apple's upcoming smart display Leaked images reveal new Apple TV 4K, HomePod mini New iPad mini details revealed in latest leak Leak reveals new iPhone Duo features not yet announced Apple releases iOS 27.0.1 for iPhone, here's what's new John Ternus wants to reshape Apple, here's how

Could the land beneath your solar project help finance the next one, without giving up equity in your company?Laura Pagliarulo, CEO and co-founder of SolaREIT™, returns to SunCast to share what six years of financing solar and battery real estate have taught her about how developers grow without overextending themselves. Her company has financed real estate beneath projects representing nearly $8 billion in total value.Laura explains how land purchases, lease purchases and land loans can provide flexible capital without selling equity in the developer's company. She describes repeat partners planning transactions six to eighteen months before a portfolio closes, with proceeds supporting interconnection deposits and other pipeline needs.Expect to learn:

0:00 - Intro2:39 - PC VR Mods & PS6 VR Support Debate18:28 - Tips: Hard Bullet Price Fix, Cave Crave & Bootstrap Chat26:14 - Viewer Takeover Grab Bag: Is VR Dying?, Ace Combat VR & More41:09 - Reassigning Midnight Walk45:23 - Reassigning : Behemoth48:20 - Reassigning : Happy Funland51:37 - Reassigning Walkabout Mini Golf55:52 - Reassigning : Saints and Sinners Chapter 259:22 - Reassigning : Synapse1:06:25 - Reassigning : Starship Troopers1:10:02 - Tips: Burnout Paradise, Journey to Foundation & Slender Man News1:17:19 - 4 Minute Challenge1:25:18 - Wrap Up - Member Show

On the podcast: growing for four years on press and organic alone, affiliate deals as an underexplored revenue stream, and why deciding to pivot is the hardest part.Top Takeaways:

Altium's acquisition of Duro brings cloud-based PLM software built for hardware startups and small engineering teams into the Altium platform, and in this OnTrack Podcast episode Zach Peterson asks Duro founder and CEO Michael Corr why the deal happened. Michael walks through how the Altium Designer plugin publishes library parts and full projects into Duro with part numbers, revision status, and draft change orders, and how that integration deepens inside Altium 365 while Duro stays available as a standalone product.  He also explains the AI agents Duro is starting to roll out, which act as RF, mechanical DFM, procurement, and supply chain specialists that review change orders for teams that can't hire every one of those roles. You'll hear why Duro builds every feature API-first, with documentation written so AI coding agents can build on it, and what customers are building with that access. Watch if you manage hardware product data and want product lifecycle management that doesn't take an IT team to configure.

Marina Wyss joins The Ai Dev Craft Show to talk about what it really means to become an AI engineer—and how developers can keep learning without trying to chase every new model, tool, and trend.The conversation covers the difference between AI engineering and machine learning, why evaluation is becoming such an important skill, how software engineers can transition into AI-focused roles, and why strong fundamentals still matter more than knowing every new framework.Marina also shares practical advice for choosing what to learn, building useful side projects, navigating AI careers, and staying current without burning yourself out.You can also hear Marina at Ai Dev Craft in Las Vegas, where she'll speak on Staying Current with AI Without Losing Your Mind and lead a workshop on Evaluating AI Systems.https://www.youtube.com/@MarinaWyssAIhttps://www.instagram.com/marina.wyss/https://www.linkedin.com/in/marina-wyss/www.marinawyss.comThe Ai Dev Craft Show is a part of the Ai Dev Craft Conference happening Master October 27-28, 2026 Las Vegas. Join us weekly as we discuss the rapidly changing AI-scape and how developers can adapt and excel.Master developing with AI, become your team's AI expertJoin us for Ai Dev CraftGet tickets now! https://ai-devcraft.com/Special thanks to our hosts:Lara Newsom Jay BellMike HartingtonJames SpiveyBrian Love

Gratis Erstgespräch buchen: https://shorturl.at/YQTVm 

You should always be aware of this Clause in your Bridging Loans! ▶︎ Website - www.thepropertyfinancecollective.co.uk▶︎ The Host - With a passion for creative finance and the ability to structure deals for Finance, I love helping first time Developers and Investors to get deals packaged for the finance needed to push Property Careers forward, and to date I have raised over £500 million for Developers and Investors. I first got into property at the age of 18 when I got into Conveyancing straight out of school. I then went into Estate Agency, back into Conveyancing and I then got into brokering at the age of 22. I decided a year and a half later that I wanted to work for myself and try and shake up the market place! At the age of 24 I set up The Property Finance Guy and became the youngest owner of a Commercial Finance Brokerage in the Country, and alongside this I now also have a successful Training Company, educating Investor and Developers on how to raise finance, and a successful Podcast.I am a keen public speaker and have delivered training and speeches to over 1000 investors and developers over the past 2 years.Follow Michael:▶︎ Facebook - https://www.facebook.com/thepropfinguy/▶︎ Instagram - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/thepropertyfinanceguy/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▶︎ LinkedIn - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/michael-primrose-886a365b/?originalSubdomain=uk⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Listen to the Podcast on:▶︎ Apple Podcasts - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://podcasts.apple.com/gb/podcast/the-property-finance-podcast/id1448207494⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▶︎ Spotify - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://open.spotify.com/show/7JiDtm7hc0EfSW9LjCXDaO⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▶︎ YouTube - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/@thepropertyfinanceguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▶︎ Disclaimer - With the market changing so quickly, the content could be out of date at the time of listening.This Content is for informational purposes only, you should not construe any such information or other material as legal, tax, investment, financial, or other advice.

Witam w trzysta dwudziestym czwartym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest zero-knowledge cloud, czyli polski wkład w cyfrową suwerenność Europy.Dziś moim gościem jest Paweł Masłowski – Chief Innovation Officer w Oktawave, odpowiedzialny za inicjatywy rozwojowe, strategię innowacji i wdrażanie nowych technologii. Jako inicjator zmian technologicznych wykorzystuje silne zaplecze inżynierskie oraz doświadczenie w budowie systemów wysokiej dostępności i High Performance Computing. Specjalizuje się również w zarządzaniu partnerstwami i współpracy międzynarodowej. Sponsor odcinkaSponsorem odcinka jest Oktawave.W ramach inicjatywy IPCEI-CIS Oktawave realizuje projekt Next Gen Cloud, finansowany ze środków Unii Europejskiej - NextGenerationEU w ramach Krajowego Planu Odbudowy i Zwiększania Odporności, przy udziale Narodowego Centrum Badań i Rozwoju. W tym odcinku rozmawiamy w następujących kontekstach:znaczenie cyfrowej suwerenności dla Europyzałożenia i skala inicjatywy IPCEI-CISdroga Oktawave do udziału w europejskim projekciecechy chmury nowej generacjiidea Zero-Knowledge Cloud w praktycepełna kontrola klienta nad danymi i kluczamifundamenty bezpieczeństwa chroniące dane przed dostawcądroga od koncepcji do gotowej technologiiwspółpraca z globalnymi dostawcami chmurowymibezpieczeństwo kluczy a ryzyko błędów użytkownikazastosowania w sektorach regulowanych i rozwoju AIfinansowanie, kamienie milowe i komercjalizacja projektuSubskrypcja podcastu:zasubskrybuj w Apple Podcasts, Spreaker, Sticher, Spotify, przez RSS, lub Twoją ulubioną aplikację do podcastów na smartphonie (wyszukaj frazę „Porozmawiajmy o IT”)poproszę Cię też o polubienie fanpage na FacebookuLinki:Oktawave –  https://oktawave.com/pl Projekt Next Gen Cloud – https://oktawave.com/pl/ipcei Profil Pawła na LinkedIn – https://www.linkedin.com/in/pawelmaslowski/ Jeśli masz jakieś pytania lub komentarze, pisz do mnie śmiało na krzysztof@porozmawiajmyoit.plhttps://porozmawiajmyoit.pl/324

Carnival CEO Josh Weinstein joins exclusively on the company's latest earnings, which have the stock jumping today. Then, we speak to T. Rowe Price Portfolio Manager Tony Wang about where to find opportunity in the tech sector. Plus, we preview what to expect at OpenAI's Developer Day today. Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Career reinvention for developers is usually discussed in terms of learning a new language, moving into leadership, adapting to AI, or finding a new job. Our conversation with Gaylen A. Wilson takes that idea much further. His story shows what happens when careers, businesses, health, and even our assumptions about the future stop following the plan. Season 29 of Building Better Developers is about building a career beyond the code. Usually, that leads us into conversations about leadership, communication, business value, quality, or the skills developers need as they move beyond completing technical tasks. This episode is different. We did not spend much of the first half talking about software development or QA. Instead, Gaylen told us his story, and the longer he talked, the clearer the connection to developers became. Gaylen's career repeatedly forced him to confront something most developers eventually discover for themselves: you can master the tools, solve complicated problems, and work incredibly hard, but none of that guarantees life will follow the architecture you designed. His story is ultimately about rebuilding when the plan fails, which makes it an unexpected but valuable example of career reinvention for developers. About Gaylen A. Wilson Gaylen A. Wilson is an author, relationship coach, technology veteran, entrepreneur, farmer, former stockbroker, and heart-transplant recipient whose career has required him to reinvent himself repeatedly. Together with his wife, Heather, Gaylen developed the Monument Method, an approach they use to help couples interrupt destructive conflict patterns and strengthen their connection. Learn more about Gaylen A. Wilson through his website http://www.monumentmethodinstitute.com/. Your Career Is Not a Straight Line Gaylen started his professional life far away from software. He became a farmer in his twenties and built a life around agriculture. Then drought and crop failures destroyed the business, eventually forcing him into farm bankruptcy. He had to reinvent himself. His next chapter took him into finance as a stockbroker. He succeeded there until a company whose investment he had recommended collapsed after, according to Gaylen, misrepresenting its financial condition. He described that experience as another devastating setback. Without healthy ways to process what had happened, his personal life also began to unravel. Eventually, Gaylen rebuilt again. In 2001, he found work as a traveling PeopleSoft computer consultant. He was earning more than he ever had before and thought he had finally reached a stable point in his career. Then September 11 changed the economy and consulting industry around him. By December, he had lost that job. After months of searching and hundreds of mailed résumés, he eventually took a job as a Walmart cashier because he needed to work. For developers, there is an important lesson in that progression. We often build our identity around what we do. We become the Java developer, QA engineer, architect, DevOps specialist, technical lead, or whatever role currently defines our career. Then the technology changes, the company restructures, a project ends, AI changes part of the workflow, or the market simply decides that yesterday's valuable skill is commonplace today. The ability to rebuild can matter more than the title you are trying to protect. Career Reinvention for Developers Starts with Transferable Skills One interesting part of Gaylen's story is how often skills from one chapter became useful in the next. Farming did not look anything like stockbroking, and stockbroking did not look much like technology consulting. Yet farming had already taught him far more about running a business than people might assume. When the consulting market disappeared, Gaylen eventually returned to his hometown and put a small advertisement in the newspaper offering computer repair. He had never worked professionally as a computer repair technician. He had simply been interested in computers for years. Within six months, that small side business was outperforming his Walmart job. Then the market changed again. As Windows became more reliable and malware-related repair work declined, the computer repair business that had supported Gaylen and his wife, Heather, began drying up. Instead of assuming the old business would somehow return, he adapted. He found platforms connecting technicians with companies needing field work and began traveling throughout rural America installing and servicing technology. Eventually, that work took Gaylen and Heather through all 48 contiguous states. That is where this story starts to sound much more familiar to a developer. Technologies disappear. Frameworks fall out of favor. Companies reorganize. Entire categories of work become automated. A skill that was valuable five years ago can become commonplace today. Career reinvention for developers becomes easier when we stop defining ourselves by a particular technology and start recognizing the skills that survive those changes. Those transferable skills include: Problem-solving and troubleshooting Learning unfamiliar systems quickly Breaking complicated problems into manageable pieces Communicating with customers and stakeholders Testing assumptions instead of blindly following them Adapting when the original solution no longer works Understanding the business problem behind the technology Those are skills that remain valuable even when the code changes. Developers Are Professional Problem Solvers There is another reason Gaylen's story belongs in a developer-focused season. Developers tend to be fixers. Give us a broken system, and we immediately start looking for the defect. We gather information, isolate variables, test assumptions, and keep working until we understand the problem. That mindset is incredibly valuable. It can also become dangerous when we start treating every problem as something we can overcome simply by working harder. Michael touched on this at the beginning of the episode while discussing the difficulty of slowing down after a period of long releases and extreme work hours. Even after the immediate pressure disappeared, there was still that feeling that he should be doing something. Rob connected that experience to the larger conversation about how quickly technology is moving and how easily careers can consume the rest of our lives. Many developers know that feeling. There is always another ticket, certification, framework, side project, production issue, release, or AI tool to learn. We tell ourselves things will calm down after the current deadline. Then another deadline appears. Gaylen eventually encountered a problem he could not outwork. When Working Harder Stops Being the Solution In 2014, after years of traveling for technical work, Gaylen became seriously ill. He initially believed he had pneumonia and continued working. During another extended trip, his condition worsened until a clinic in Corpus Christi sent him for a chest X-ray. He was told he had congestive heart failure and needed to return to Colorado. His first reaction is revealing. The jobs were paying well. They already had weeks of work scheduled. Gaylen initially thought they should finish the trip before dealing with his heart. It took two more jobs before the seriousness of the situation finally broke through his drive to keep working. That moment is an extreme example of a pattern many developers experience in smaller ways. We know we need sleep, but the release needs to go out. We know we need a weekend away from the computer, but production has a problem. We know we have not spent enough time with the people around us, but there is one more thing we need to finish. The problem-solving mindset becomes a trap when the answer to every problem is simply more effort. There are times when the correct solution is to stop. What Are You Actually Building? Gaylen eventually received a heart transplant in 2018. He described being near the point where he and Heather were preparing for the possibility that he would die when they received the call that a donor heart was available. By the next morning, Gaylen had received a new heart. He viewed the transplant as an opportunity to have more years with the person who had stayed beside him throughout his illness. That experience changed what success meant to him. It also gives developers a useful question to ask about our own careers: What are we actually building? We spend our days building systems for other people. We think about architecture, scalability, reliability, technical debt, requirements, and defects. Yet we do not always apply the same intentional thinking to the systems surrounding our careers. A successful career should support a life rather than consume it. That does not mean ambition is wrong. It does not mean developers should stop working hard or stop pursuing difficult goals. It means the career itself should serve something larger. Otherwise, we can become incredibly efficient at building a future we eventually discover we did not want. Quality Applies Beyond Software At EnvisionQA, we spend a lot of time thinking about quality and finding problems before customers encounter them. One lesson from this conversation is that the same mindset can extend beyond software. In software, we do not wait for catastrophic failure if we can avoid it. We monitor systems. We test assumptions. We look for warning signs. We examine recurring defects because they often point toward deeper problems. Our careers deserve similar attention. If every release requires heroics, something may be wrong with the process. If every week requires sixty or eighty hours, the workload may not be sustainable. If you cannot stop thinking about work when you leave the computer, that is information worth examining. If professional success consistently comes at the expense of health or important relationships, simply becoming more productive may not solve the underlying problem. Sometimes the system itself needs redesigning. Career Reinvention for Developers Is About More Than Technology Gaylen's journey moved from farming to finance, technology consulting, computer repair, nationwide field service, serious illness, a heart transplant, and eventually relationship coaching. That is hardly a traditional developer career path, but that is precisely why this conversation fits our season. Careers rarely follow the architecture diagram we created when we started them. Technologies change. Businesses disappear. Markets collapse. Health changes. Priorities change. Sometimes we make mistakes, and sometimes circumstances outside our control rewrite the requirements completely. The developers who build lasting careers are not necessarily the ones who perfectly predict what comes next. They are the ones who learn, adapt, rebuild, and carry lessons from one chapter into the next. That is ultimately what career reinvention for developers is about. Most importantly, the career is not the final product. The life you are building around it is. In Part Two of our conversation with Gaylen A. Wilson, we bring his experiences more directly back to developers, burnout, fight-or-flight thinking, relationships, and the challenge of leaving work at work. We also explore what happens when the same problem-solving mindset that makes us effective developers follows us home. 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The acquisition will see World Labs founder Fei-Fei Li join AMD as executive vice president and chief scientist. Also, SiMa.AI, the edge computing startup, raised a $150 million Series C led by Fidelity and Amplify. Learn more about your ad choices. Visit podcastchoices.com/adchoices

a16z's Ben Horowitz and Martin Casado sit down with TypeSafe AI founder Diogo Almeida to ask a simple question: AI has become remarkably capable, so where is all the automation?Diogo argues that coding agents may help us write software faster, but the software they produce still largely works the way software always has. TypeSafe is taking a different approach with Jev: putting intelligence inside software itself, so developers can build programs that reason about intent and make probabilistic decisions rather than simply generate text for a human to interpret.They discuss why reliability is the key to making AI genuinely programmable, how this could open a new era of probabilistic software, and why established SaaS companies may be particularly well positioned to benefit. Ultimately, Diogo's goal is straightforward: technology that can reliably “do what I mean.”Resources:Follow Diogo Almeida: https://x.com/CompleteSkepticLearn more about TypeSafe AI: https://typesafe.ai/Follow TypeSafe AI: https://x.com/typesafeaiFollow Ben Horowitz on X: https://x.com/bhorowitzFollow Martin Casado on X: https://x.com/martin_casado Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Using AI is one thing. Building an entire system around it is another.Matthew Bertram sits down with returning guest Richard Valentine and Hector Herrera for a deep technical conversation about how AI power users are moving beyond individual prompts and building their own AI architecture, specialized agent teams, memory systems, workflows, and internal infrastructure.They explore model drift, token management, specialized AI teams, scheduled learning, memory decay, human approval systems, and why AI shouldn't necessarily remember everything. The conversation also goes inside the challenge of transforming an organization from having a handful of AI power users to becoming truly AI-first.The discussion then turns to privacy, on-premise AI, security, credential management, deepfakes, impersonation, and the growing importance of controlling the infrastructure businesses increasingly depend on. Finally, they bring it back to marketing and SEO, exploring how AI systems can connect Search Console, analytics, trends, and other data sources to create feedback loops that continuously adapt marketing decisions to what audiences are actually doing.• rebrand updates and why we're building a broader SEO and AI community resource • why Claude can get “nitpicky” and how model behavior changes break workflows • token management, subagent sprawl, and rules for routing tasks to the right model • Hector's “teams” approach with doctrines, routing, scheduled learning, and change logs • memory decay, relevance scoring, and crystallization for keeping knowledge accurate over time • AI-first adoption inside organizations, consistency across tools, and reducing “islands” of usage • personas in Slack and email assistants, including permissioned execution and critical-system guardrails • on-prem and private setups for regulated industries, resilience, and avoiding vendor lock-in • security protocols like redaction, vaulting secrets, daily scrubs, and minimizing human error • deepfakes, propaganda, impersonation risk, and why EEAT signals matter more than ever please leave an honest review, uh, how we're doing.Guest Contact Information:Richard ValentineWebsite: richardvalentine.devLinkedIn: linkedin.com/richard-l-valentineHector HerreraWebsite: hexaisystems.comLinkedIn: linkedin.com/hector-herreraMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon Podcast.Free SEO Consultation: https://www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online.Now, host Matthew Bertram — creator of the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability.Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve.Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

Discover the emerging classifier revolution with Jev—a radical new take on LLMs that ditches generation for lightning-fast categorization. Plus, deep dives into the latest model releases (Luna, GPT-6 Sol, Claude Opus 5.5), practical strategies for iterative AI development, and why specialized models are reshaping how we work with AI. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us ⭐⭐ Machine transcription available on http://mergeconflict.fm

In this podcast, Michael Stiefel spoke to Erin Doyle about how artificial intelligence tools are transforming the software development process, and how they are affecting software engineers. Architecture skills are now critical because engineers need to understand how to build systems and handle the constraints and associated ambiguity in the requirements. At the same time, given the rapid change both in the nature of the AI tools, and the amount of code they can produce which can overwhelm developers, psychological safety becomes essential for successful AI adoption. Teams need a secure, non-judgmental environment to share their successes, admit failures, ask for help, and express skepticism. Industry lacks a plan to train junior engineers because AI is taking over the tasks they were traditionally trained on, and university education is not adequate preparation for this new reality. The conversation concluded by discussing how software developers and organizations must retain complete ownership and assume full liability for the output generated by AI tools. To manage this, there is an urgent need to develop advanced verification and telemetry tools that can support the review process. Read a transcript of this interview: https://bit.ly/4yNWi05 Newsletter: Subscribe to the Software Architects' Newsletter, a monthly roundup of the patterns and technologies senior practitioners are working through, with the news and lessons from people doing the work: https://www.infoq.com/software-architects-newsletter InfoQ Online Certification Programs: 5-week online cohorts for senior engineers and architects, built around QCon talks. Programs now cover software architecture, AI engineering, and organizational architecture. Each week you join a four-hour live session with a confidential peer group of practitioners from other companies, apply frameworks from QCon talks to the decisions you're making at work, and earn an InfoQ certification. You leave with new approaches, or confirmation that the calls you're already making are the right ones. Learn more: https://certification.qconferences.com/ Upcoming Events: QCon San Francisco 2026 (November 16-20, 2026) https://qconsf.com/ QCon London 2027 (April 13-16, 2027) https://qconlondon.com/ The InfoQ Podcasts: Weekly conversations with senior software leaders about how they build systems and teams, including what they'd do differently. Listen to all our podcasts and read interview transcripts: The InfoQ Podcast: https://www.infoq.com/podcasts/ Engineering Culture Podcast by InfoQ: https://www.infoq.com/podcasts/#engineering_culture Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: Mastodon: https://techhub.social/@infoq X: https://x.com/InfoQ LinkedIn: https://www.linkedin.com/company/infoq/ Facebook: https://www.facebook.com/InfoQdotcom Instagram: https://www.instagram.com/infoqdotcom/ YouTube: https://www.youtube.com/infoq Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Share what you've learned building software with a community of senior practitioners, and get your work in front of the people who read InfoQ. https://www.infoq.com/write-for-infoq

The developers behind a housing project at the base of Mt Iron say it could help ease Wanaka's housing crisis. The Mt Iron Junction scheme will deliver 250 homes and community facilities, but opponents have questioned its scale, traffic impacts and effects on the landscape. And after years of wrangling with the RMA, the project has now been given fast-track approval. One of the developers, Steve Schikker, spoke to John Campbell.

Thanks Pressable for supporting the show! Get your special hosting deal at https://pressable.com/wpminuteBecome a WP Minute Supporter & Slack member at https://thewpminute.com/supportThis edition of The WP Minute's member meetup focuses on best practices for your vibe coding projects. GridPane's Patrick Gallagher joined Eric and Matt to discuss the good, bad, and ugly of vibe coding plugins and apps with AI.Patrick shows off a slide deck he generated from a single prompt in Claude Design, explains recent leaps in AI capability since OpenAI's o1 Pro reasoning model, and the rising power of local open models. He also points out that persistent hallucinations continue to be an issue, underscoring the need for human accountability and multi-model “red teaming” to verify code and security.You'll also find takes on why AI tools rarely default to WordPress for site building, how negativity and training data may influence model choices, and why real product value still depends on execution, responsibility, and serving specific customer needs.It's everything you need to turn vibe-coded projects into usable products!Editor's Note: GridPane is a Pillar Sponsor of The WP Minute.Takeaways:AI can create substantial code and content incredibly quickly.Human expertise is still essential for verifying AI-generated work.AI models can hallucinate confidently, even when told not to guess.Developers should use multiple AI models to inspect and refine code.AI makes execution easier, allowing us to focus on real customer issues.Narrow, specialized WordPress products can still succeed by serving a specific audience.AI may replace simple utility plugins, but established products with support remain valuable.In-person communities may become more important as online discourse gets noisier and more negative.Important Links:GridPaneArtificial AnalysisConnect with Patrick: LinkedIn | Twitter/X The WP Minute+ Podcast: thewpminute.com/subscribe  ★ Support this podcast ★

There are so many ways to bring down the cost of new build in the UK, chief among them reduced regulation, planning and taxation. So I was most disappointed, putting it mildly, to see Prime Minister Andy Burnham's new initiative, Your First Home, which will give government-backed equity loans of 20% to first time buyers, who will now be able to buy new build property with just a 2.5% deposit. Initially, that 20% will be interest-free.This is just another means to saddle young people with debt. As if student loans weren't bad enough. Unlike period property, new build struggles to keep its value. It's often because people overpay for new build - the so-called new-build premium. You're buying a brand new product and somebody, you, has to cover the developer's margin, marketing costs and all the other costs wrapped up in that shiny new flat. Meanwhile, there is no longer the buy-to-let investor to prop up the buy side. The government has already seen to that. The risk of in the inexperienced first-time-buyer overpaying is high and the likelihood of them falling into negative equity is immense. Look at the problems those who went down the Help To Buy route are now having with London flats, where prices are down 20-30%, with owners in negative equity, unable to sell without taking huge losses, and unable to move up the property ladder. Trapped.Help to Buy artificially inflated the prices of new-build flats. Developers knew buyers had government backing, so they charged a “new-build premium,” which effectively captured most of the subsidy. It handed money to people who already had it. Of course building companies will welcome Burnham's scheme this time around. Now that the Help-To-Buy subsidy has ended, new buyers must purchase using normal mortgages, which has caused prices to “normalise”, ie fall 30%.Meanwhile, there are the problems of skyrocketing service charges and the fallout from the cladding scandal, both of which have also made flats hard to sell.The main people Help To Buy helped were the large building companies, and Andy Burnham's new scheme will do just the same. It is yet another demand-side intervention in a market where the fundamental problem is that housing is too expensive to build. It is a terrible and misguided thing to do. Builders can (and will) overprice their deals, and trap buyers, who, as first-timers will be naive, in punitive leasehold deals. It is no more than a subsidy for building companies. It does not address the many causes of Britain's unaffordable housing. It exacerbates them. You are creating more of what caused Britain's affordability problem in the first place.This is new builds only. So happy days for the likes of Barratt Redrow, Vistry and Taylor Wimpey, never mind the cowboys, who will take the money and run, and leave you holding the bag of poor construction, leasehold and unsellability. Builders' shareprices will rise on the back of this. Loads of people will be suckered into buying because of the easy affordability now, and thier desperation to own a property. “Oh, it's better than renting” “Oh, we only have to pay this much.” But if you or anyone you know is tempted by this, I urge you or them to please avoid it at all costs. As a rule flats, particularly new build, are to be avoided because, there is so much beyond your control that you end up being financially responsible for, from basic repairs and maintenance, to problems in the actual build, such as cladding, only found years later, which have now become your unsellable asset.A 2.5% deposit is just too much leverage. It's fine if you know what you are doing, but most don't.You could overpay for your property by 5%, which is easily done when you have the carrot of easy affordability now being dangled in front of you. Prices could fall 10%. Or you lose your job. Heaven forbid prices should fall 20-30% as they have with Help to Buy. There are so many routes to negative equity. It is going to ruin people.Do our policy makers never learn? Never mind Help to Buy, what about the US subprime crisis? And then there is 1989-94 and the loose lending that preceded that crash. All the evidence of where this goes is right there in living memory, staring them in the face.There is also the issue that interest rates today are much higher than they were when Help To Buy was introduced.Yet again the government is addressing the problem of unaffordable housing by making it easier to borrow more money to buy unaffordable housing. In other words, it's finding more ways to bring money into the system when the problem is too much money.This will absolutely screw people. And it's all dressed in this great guy, true Northerner, trustworthy kids TV presenter, helping you out language with no mention of the risks. It is proper gaslighting. It's like the friendly chap outside the school playground with the gateway drug. There are times when I think this country's leadership and administration is just superlatively incompetent. There are times when I actually think Satan might be at work and this is one of them. And you wonder why I can't stand governments!Share this article with a friend.If you're interested in the subject of unaffordable housing, you might enjoy this classic from the archives Finally, but perhaps most importantly, here is this week's commentary. I urge you to read it, if you haven't already. Thanks for subscribing to the Flying Frisby.Until next time,DominicIf you live in a third world country such as the UK, I urge you to own gold or silver. The pound will be further devalued, as will the euro and dollar. The bullion dealer I use and recommend is The Pure Gold Company. They deliver to the UK, the US, Canada and Europe. More here.For my readers on the other side of the pond, let me also plug next month's New Orleans Investment Conference, which runs from October 28-31. I'll be there and there is an array of great speakers. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.theflyingfrisby.com/subscribe

Kým dnes drvivá väčšina Slovákov býva vo vlastnej nehnuteľnosti, rastúce ceny bytov, drahšie financovanie a meniace sa preferencie mladšej generácie otvárajú priestor pre nový realitný biznis Developer Lucron stavia v bratislavskom Neste viac ako 300 zariadených nájomných štúdií. Ak sa model osvedčí, môže byť jedným z prvých signálov, že slovenský realitný trh sa začína približovať západnej Európe. Pre developera však nájomné bývanie znamená úplne inú ekonomiku ako klasický predaj bytov. Pri tradičnom modeli developer projekt postaví, byty predá a v priebehu niekoľkých rokov inkasuje späť vložený kapitál. Pri nájomnom modeli musí nehnuteľnosť dlhšie vlastniť alebo prevádzkovať, budovať obsadenosť a až následne môže aktívum predať investorovi. Slovensko navyše zatiaľ nemá dostatočne rozvinutú sieť veľkých inštitucionálnych investorov ani profesionálnych operátorov, ktorí sú v západnej Európe prirodzenou súčasťou tohto trhu. Projekt Nesto je najväčším projektom Lucronu v Bratislave. Na 47 hektároch v Petržalke má počas najbližších 15 až 20 rokov vyrásť nová mestská štvrť. Už dnes v nej žije približne 400 ľudí. Nájomný sektor sa začal stavať v marci 2026. Developer ho chce stavebne dokončiť v roku 2028 a prvých nájomníkov privítať ideálne už v septembri toho istého roka. Projekt má byť zároveň testom, či je profesionálne nájomné bývanie životaschopné aj na slovenskom trhu. „Je to pre nás laboratórium, ako sa táto biznisová línia v rámci developmentu osvedčí. Keď to funguje v zahraničí a vykazuje to dobré čísla, prečo by to nemohlo fungovať na Slovensku?“ hovorí Slavomír Habánik, development director spoločnosti Lucron. Viac si vypočujete v podcaste.

Welcome to The Jas Johal Show Political Happy Hour — where the week's best political conversations keep going. This week: Keith Baldrey: Caroline Elliott bumps an MLA, OneBC threatens to split the right, and poll fallout (1:11) Beau Jarvis: Wrong fix? Developers takes on Eby's unsold condo tax (17:31) Shachi Kurl: Angus Reid poll puts Conservatives up eight on the NDP (31:26) Pull up a chair. Fire up the expense account. Learn more about your ad choices. Visit megaphone.fm/adchoices

Podcasting 2.0 September 25th 2026 Episode 272 - "Is this Y'all?" 00 -

Marc Cox and Kim St. Onge open the St. Louis Morning Brief analyzing citizen petition efforts following a city council vote granting developer tax incentives. The hosts review municipal petition signatures required to trigger council reconsideration or a referendum vote in Ballwin.The segment honors Naismith Basketball Hall of Fame inductee and two-time NBA Most Valuable Player Bob Pettit, who passed away at age 93. The hosts review Pettit's 11-season career with the Milwaukee and St. Louis Hawks, his 1958 NBA championship, and his career statistics. The brief covers employment termination proceedings involving a local substitute teacher, assault and robbery charges filed against four individuals following an accident in North St. Louis County, and hearing postponements in St. Louis Board of Aldermen ethics proceedings involving Alderwoman Sharon Tyus and Alderman Rasheen Aldridge.For official voter guidelines, sample ballots, and election information, consult the Missouri Secretary of State Elections Division. LISTEN TO 97.1 FM TALK LIVE IN ST LOUIS OR STREAM WORLDWIDE AT 971TALK.COM Hashtags:#971FMTalk #StLouis #STLNews #STLMorningBrief #BobPettit #Ballwin

Nexterity's robot can tighten or loosen four bolts at a time, and it fits in a Pelican case. Feather is betting on a customizable, $30,000 platform built for software developers. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Some advocates say diversifying how farmland is used can help preserve it.

Benjamin and Chance cover the week in Apple news, including hands-on with the new M6 Mac mini and AirPods 5, the first round of bug fixes for the new operating systems, Apple Music Hall, and more.  And in Happy Hour Plus, we reflect on how Siri AI has fared in the real world so far. Subscribe at 9to5mac.com/join. Sponsored by Quince: Find your next fall favorites at Quince. Download the Quince app for app-exclusive offers, or visit quince.com/happyhour. Get free shipping on your order and 365-day returns. Now available in Canada and the UK, too. Sponsored by iMazing: iMazing's platform for data transfer and device management keeps getting better. Get 20% off iMazing with code 9TO5-SEP26-20OFF.  Sponsored by Copilot Money: Get two months free with code 9TO5MAC at copilot.money/9to5mac. Hosts Chance Miller @ChanceHMiller on Twitter @ChanceHMiller on Instagram @ChanceHMiller on Threads Benjamin Mayo @bzamayo on Twitter @bzamayo@mastodon.social @bzamayo on Threads Subscribe, Rate, and Review Apple Podcasts Overcast Spotify 9to5Mac Happy Hour Plus Subscribe to 9to5Mac Happy Hour Plus! Support Benjamin and Chance directly with Happy Hour Plus! 9to5Mac Happy Hour Plus includes:  Ad-free versions of every episode  Pre- and post-show content Bonus episodes Join for $5 per month or $50 a year at 9to5mac.com/join.  Feedback Submit #Ask9to5Mac questions on Twitter, Mastodon, or Threads Email us feedback and questions to happyhour@9to5mac.com Links Steve Jobs Antennagate Q&A M6 Mac mini review: Apple's most versatile Mac continues to shine Apple unveils AirPods 5 with upgraded noise cancellation, more Apple releases watchOS 27.0.1 to fix Apple Watch Series 12 and Ultra 4 bug iPhone 18 Pro Face ID bug causing system to crash and reboot for some users Apple says software update to fix iPhone 18 Pro rebooting bug is coming next week watchOS 27.2 beta 2 brings the App Switcher back with a new gesture Apple working on Whoop-style screenless fitness tracker, per report Apple planning to sell AI servers powered by M8 Ultra chips, says report Apple Music opens new live music venue in London In select countries, iCloud+ now includes Apple TV and Apple Arcade at no extra charge Five ways that the new Siri AI is frustrating iPhone and Apple Watch users

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

What actually goes into developing a piece of land, and where do projects usually start going wrong?In this episode, Jessey sits down with developer Eugene Gershman to talk about what he's learned from more than 20 years working across both construction and real estate development.Eugene breaks down what he looks for when choosing contractors, why experience with the same product type matters, and why simply choosing the lowest bid can end up costing you significantly more.They also get into some of the details that owners often overlook, including incomplete construction drawings, missing finishes, change orders, and the difference between getting plans approved and actually having enough information to build from.They also talk about today's development market, why many projects are struggling to pencil, and how Eugene evaluates whether a property is worth moving forward with.What you'll learn:- What to look for when choosing a contractor or development partner- Why experience with the same product type matters- How incomplete plans and missing scope can lead to expensive change orders- Why a project that works on paper can still carry significant riskConnect with Eugene Gershman:Podcast: Real Estate Development: Land to LegacySocial: @eg_developerEugene Gershman Personal: https://egershman.comGIS Companies: https://giscompanies.coLinkedIn: https://www.linkedin.com/in/eugenegershman

In this episode, Jackson Sells, a builder and founder of Black Timber, shares insights on ground-up construction, townhome development, and strategies for raising capital in real estate. Discover how innovative approaches are shaping the future of affordable housing and development in Metro Atlanta.   Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind: Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership: Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true 'white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright: Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a "mini-mastermind" with Mike and his private clients on an upcoming "Retreat", either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas "Big H Ranch"? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform! Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

AI communication skills are becoming increasingly important as developers and leaders rely on artificial intelligence to summarize meetings, draft emails, organize ideas, and prepare for conversations. These tools can save time, but Salvatore Manzi warns that using AI to improve your communication is different from letting AI do your communicating for you. In Part 2 of our Develpreneur conversation with leadership communication coach Salvatore Manzi, Rob Broadhead and Michael Meloche explore how communication changes as developers move into leadership roles and AI becomes part of everyday work. The discussion covers better meetings, keeping remote teams engaged, using AI without weakening your skills, and communicating technical ideas to people outside your technical world. About Salvatore Manzi Salvatore Manzi is a leadership communication coach whose work sits at the intersection of leadership, communication, and collaboration. He works with teams and analytical professionals to improve how they communicate so they can collaborate more effectively and move their ideas forward. Salvatore is also the author of Clear and Compelling: Communication Strategies for Big Thinkers. During the Develpreneur interview, he explained that the book draws on twenty years of communication strategies and is aimed particularly at analytical, technology, and data-driven professionals with bold ideas. His work fits closely with the theme of this season of Develpreneur: building a career beyond the code. Technical knowledge can help you develop the idea, but leadership communication helps you explain it, build support for it, and bring other people along with you. Social: Facebook / YouTube / Instagram / LinkedIn Website: Salvatore Manzi's Website AI Communication Skills Need Structure Without Becoming Rigid Developers tend to appreciate systems, but nobody wants every conversation governed by a complicated set of rules. That creates an interesting challenge for leaders: How much structure does a team actually need? Salvatore describes communication as an art rather than something with a perfect formula. However, he also points out that people need parameters. We need to understand the limits before we know how much freedom we have within them. In a meeting, those limits might involve time, the topic being discussed, or how long each person should speak. The key is keeping those parameters flexible. Telling someone they can speak exactly seven words creates a new problem because everyone becomes focused on satisfying the rule. Asking people to keep their responses to one or two sentences establishes a useful boundary without turning the meeting into an exercise in compliance. This same principle applies throughout leadership. Structure should help people communicate rather than becoming another obstacle they have to navigate. Better Communication Starts With the Purpose of the Meeting Many developers have experienced days where one meeting runs into another until there is almost no time left to do the work discussed in those meetings. The problem is not necessarily whether a meeting lasts fifteen minutes, thirty minutes, or an hour. Salvatore recommends starting with a more fundamental question: What is this meeting supposed to accomplish? Without a clear objective, a meeting can continue indefinitely without producing a useful result. When people understand the goal and receive the information they need beforehand, however, some discussions can be resolved in five or fifteen minutes. That changes the way we think about meeting efficiency. Instead of automatically scheduling an hour and trying to fill it, define the outcome first. Then determine how much time the team actually needs to achieve it. AI Communication Skills Require Human Engagement AI has added another dimension to the meeting problem. We can now record conversations, generate transcripts, create summaries, identify action items, and return to the information later. Those capabilities are useful, but they can also create an excuse to disengage. Michael raised a scenario that is becoming increasingly familiar: people attend a meeting with their cameras off, barely participate, and depend on an AI-generated transcript or summary to tell them what happened afterward. Salvatore argues that leaders have a responsibility to create engagement. His recommendation is the 3-5 rule: every three to five minutes, introduce some type of pattern disruption that brings people's attention back into the conversation. That disruption does not need to be dramatic. A leader can: Ask a question. Poll the group. Ask someone for their perspective. Introduce an interactive visual. Connect the discussion directly to someone's current work. Change the way information is being presented. One of the most effective approaches is relevance. If you connect a discussion directly to a project someone is working on, that person's attention naturally increases. Instead of simply delivering information to a group, you are showing people why that information matters to them. That may become even more important as AI makes passive participation easier. Communication Skills Matter Even Without a Leadership Title What happens when you recognize that a meeting is failing but you are not the person running it? That is a common situation for developers. You may be sitting in a retrospective, refinement, stand-up, or project meeting where two or three people dominate the conversation while everyone else remains silent. Salvatore suggests that participants can help create engagement without taking over the meeting. One approach is to respond directly to something another person shared. You might briefly explain what you appreciated about their contribution and how it connects to the work. If the meeting consistently prevents important voices from being heard, that can also become a conversation with the facilitator before the next meeting. Explain what you need from the discussion and why hearing from more of the team matters to your ability to move forward. This approach changes the interaction from criticism to a request. You are not simply saying that the meeting is bad. You are explaining what would make it more useful and why that change matters. Better Team Communication Permits People to Challenge Ideas Another problem appears when people have concerns but do not want to become known as the person who is always negative. Salvatore described working with a startup that deliberately assigned roles such as the critic, negator, or contrarian during meetings. The roles rotated between people, which gave someone explicit permission to challenge an idea without being personally labeled as difficult. Over time, something interesting happened. Team members reported feeling safer raising uncomfortable issues even when they were not officially assigned one of those roles. For software teams, this concept has obvious applications. Projects need people willing to ask what happens when something fails. Testers need to challenge assumptions. Developers need to question architecture. Business analysts need to identify missing requirements. Security teams need to think about how a system could be abused. The goal is not negativity. The goal is making constructive disagreement part of the process instead of treating disagreement as a personality problem. Communication Skills Help Make Complex Ideas Easier to Process Technical experts often struggle with another communication problem: we know too much. When someone asks about a system we have spent months or years building, it is tempting to provide all the history, context, data, dependencies, and edge cases necessary to prove that we understand the problem. The listener probably does not need all of it. Salvatore recommends narrowing information into a small number of meaningful chunks. The underlying data still matters, but effective communication requires deciding which pieces another person needs to understand before moving forward. That skill becomes increasingly important as developers move into leadership. Executives, customers, operations, marketing, legal, and other departments usually do not need the same technical depth that another developer needs. The challenge is not knowing the information. It is knowing which information matters to the person in front of you. Do Not Let AI Communication Replace Your Own Voice This is where AI communication skills become particularly important. AI can summarize a long email chain, draft a response, prepare meeting notes, and transform rough ideas into polished language. Salvatore sees value in those capabilities, but he also sees a risk when AI begins communicating back and forth while the people involved stop thinking for themselves. Eventually, an email conversation becomes a real conversation. At that point, you have to explain the ideas that supposedly came from you. You have to answer questions in real time, adapt to new information, defend decisions, and respond to a dynamic situation. If AI has been doing all of the thinking and communicating for you, you may discover that you are not prepared for that conversation. Salvatore's recommendation is straightforward: use AI, train it toward your voice, and take advantage of what it can do, but always read before you send. Edit the output. Make sure it sounds like you. More importantly, make sure you understand and can stand behind what is being communicated. AI should reduce unnecessary work. It should not remove you from your own communication. Build AI Communication Skills One Problem at a Time Avoiding AI entirely is not the answer either. The challenge is maintaining your own cognitive and communication abilities while taking advantage of increasingly capable tools. Salvatore offers a simple exercise: one a day. Once each day, take one problem and work through it yourself before asking AI for help. Think through the problem, develop your answer, and write out your reasoning. Then give it to AI and compare what it produces with your approach. That creates a very different relationship with the technology. Instead of asking AI to think so you do not have to, you are using it as another perspective against which you can test your thinking. You continue exercising the skill while also learning where AI can improve your work. For developers, this should feel familiar. We do not become better programmers by copying code we do not understand. We improve by solving problems, reviewing alternatives, testing assumptions, and learning from the differences. AI communication skills should develop the same way. Communication Skills Help You Speak Outside the Technical Room Technical professionals face another challenge as their careers progress. Eventually, the audience changes. You may spend years discussing systems with developers who understand your terminology, assumptions, and data. Then you walk into a room with operations, HR, legal, sales, marketing, executives, or customers. The same communication approach no longer works. Salvatore recommends practicing metaphors because they force technical professionals to translate an idea into something another audience can visualize. He compares this to giving someone the blueprint for a house versus showing them a rendering of the finished house. The blueprint may contain more precise technical information, but the rendering makes the result easier to understand. Developers can practice this before they ever enter the boardroom. Pick something familiar—a hobby, sport, cup of coffee, or everyday activity—and explain how your current project is similar to it. The metaphor does not need to be perfect. The exercise teaches you to look at the same technical idea through a different lens. That ability to switch communication styles is part of moving beyond the code. The more responsibility you gain, the more likely you are to communicate with people who do not share your technical background. AI Communication Skills Are Career Skills AI will continue getting better at writing, summarizing, organizing, and preparing information. That makes learning how to use these tools important, but it also increases the value of the skills that remain human. Can you read the room? Can you recognize when someone has disengaged? Can you explain a technical problem to a nontechnical stakeholder? Can you challenge an idea without attacking the person who proposed it? Can you answer an unexpected question without waiting for an AI-generated response? Those are communication skills, but they are also career skills. Salvatore's advice is not to reject AI. Use it for interview preparation. Use it to evaluate your communication. Use it to help generate new ways to explain an idea. Train it to better understand your voice. Just do not stop developing your own. Stay Connected: Join the Developreneur Community

Apple's new Siri AI is finally turning digital assistant hype into real, practical power, letting users speak naturally and control their apps in ways that were impossible a year ago. Matthew Cassinelli, a Siri automation expert, is here to break down what's genuinely working, what's missing, and why this matters for your iPhone right now. Early experiences: Siri's improved world knowledge and real-time actionability Developer shift: New Siri relies on app actions and App Intents for integration Beta rollout details: Supported devices, region restrictions, language support Apple's foundation models, on-device AI, and privacy-focused execution App actions at launch, incoming third-party app support, and developer adoption hurdles Siri AI's limitations: Domains not supported and why Technical evolution: Transition from SiriKit to App Intents framework and its challenges for devs NSSpain XIV recap and developer readiness strategies App Intents Optimization (AIO): Why it matters as the new SEO for apps Shortcuts Corner: Testing Siri AI's ability to build complex automation workflows Host: Mikah Sargent Guest: Matthew Cassinelli Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsors: trustedtech.team/twit scribe.how/ios

Noah and John sit down with Kyle Egan of Douglas Elliman — 13 years in the business, $200M+ in career sales, and the son of a luxury custom builder who spent a decade in construction before ever listing a property. That background shapes everything about how Kyle thinks. Kyle opens with what he's seeing right now: buyers are hyper-sensitive to condition, and the renovation penalty goes beyond the cost of the work. Even when sellers discount for a renovation, it's often not enough — buyers need a margin above the cost to account for time and financing. And a six-year-old renovation? Buyers still want to change it. From there: how Kyle won the listing at 235 West 75th (The Astor) by being honest on pricing when others weren't, why educated buyers are walking in with Excel spreadsheets, and why what a seller paid is completely irrelevant to what it's worth today. Topics in this episode: • Why NYC buyers reject unrenovated apartments — even at a discount • The renovation decay curve sellers don't want to hear about • Upper East Side co-ops: best unrenovated value in Manhattan right now • How Kyle won The Astor condo conversion listing at 235 W 75th • Developers vs. homeowners — who's more rational about pricing? • Why honest pricing wins listings and sets up better outcomes • Educated buyers coming in with data that rivals brokers • New development resale pressure — some condos below their original price • Why what you paid is irrelevant to today's market value • Breaking goals into lists: how an independent broker stays productive • Handwritten notes: a marketing edge that still works • Managing stress by controlling what you can ✅ Kyle Egan at Douglas Elliman: https://www.elliman.com/agent/kyle-egan/1028253 ✅ Kyle on LinkedIn: https://www.linkedin.com/in/kyle-egan-1bba2216 ✅ Kyle on Instagram: https://www.instagram.com/kyleegannyc =============== ✅ Stay Connected:

Canada Housing Starts Are Down — But What Does That Actually Mean? Housing starts are down. Sounds important. But does that mean Canada is building fewer homes? Does it mean housing prices are about to rise? Does it mean fewer rental properties are coming? Not necessarily. On today's Canadian Real Estate Investing Morning Show, Wayne and Gabby dig underneath the housing-start headlines and explain why the number most people quote does not tell investors nearly enough on its own. The problem is simple: When Canada reports "housing starts," that number combines very different types of housing. A detached family home is not the same thing as a townhouse. A townhouse is not the same thing as a 200-unit apartment building. And a condominium tower is definitely not the same thing as a purpose-built rental building. Yet much of that gets bundled together. What Is a Housing Start? A housing start is not a permit. It means construction has actually begun. In practical terms, that generally means work has reached the point where the building's foundation or equivalent construction stage has begun. That distinction matters. A building permit represents an intention to build. A housing start means construction has actually moved forward. But even knowing that still doesn't answer the most important question: What kind of housing is being built? The Headline Number Can Be Misleading Wayne uses recent CMHC data to demonstrate the problem. The national housing-start number includes: Single-detached houses Semi-detached homes Duplexes Townhouses Condominiums Apartment buildings Other multi-unit housing The broad "all other" category can therefore represent completely different markets. Some units may eventually be purchased by homeowners. Others may become rental properties. Some could be high-rise condominiums. Others could be row houses or large apartment buildings. Without knowing the mix, investors should be very careful about making conclusions from the headline number. A Rental Unit Is Not the Same as a Home for Sale This is where Wayne believes the housing conversation becomes especially important. Canada has spent several years encouraging density and rental construction. Programs such as the Housing Accelerator Fund and favourable financing programs have helped make larger multi-unit developments attractive to investors and developers. The result has been a major increase in purpose-built rental development in many cities. But building more rental units does not necessarily solve the same problem as building more homes people can actually purchase. Those are two different markets. Are We Building the Wrong Type of Housing? Wayne raises a question that he believes deserves much more attention. What happens when a perfectly usable single-family house is demolished and replaced with eight or twelve small rental units? You created more rental units. But you also removed one house from the ownership market. If this happens repeatedly across a city, it is possible to simultaneously create: Too much rental supply while creating: Too little traditional ownership housing. Wayne believes this may already be happening in some Canadian markets. He is clear that the available national data does not provide enough detail to prove that conclusion definitively. But based on the information available, it is something investors should be watching closely. Why Local Data Matters More This is why Wayne does not rely heavily on national housing-start headlines when making investment decisions. Canada is not one real estate market. Edmonton is different from Toronto. Calgary is different from Vancouver. A neighbourhood can behave differently from another neighbourhood in the same city. And a single-family rental can behave very differently from a one-bedroom apartment. Investors need to go deeper. Look at what is actually being permitted and built in the municipality where you invest. Are developers building: Apartments? Condos? Townhouses? Duplexes? Single-family houses? Basement suites? Garage suites? That information is far more useful than knowing the national housing-start number. Permits Aren't Starts Either Gabby also points out another distinction. Building permits can help investors understand what developers are planning. But a permit does not guarantee construction. Projects can be: Delayed. Redesigned. Refinanced. Cancelled. A housing start tells you that construction has progressed further. Even then, the investor still needs to understand exactly what is being built. Why Multi-Unit Starts May Be Slowing Wayne believes much of the slowdown is likely coming from multi-unit development rather than detached housing. That would make sense based on what he is hearing within the investor and development community. Developers are dealing with: Softer rents Higher vacancies Higher construction costs Financing challenges Large amounts of competing supply Projects that no longer produce the expected returns Wayne is also seeing and hearing about projects being delayed or cancelled. That may eventually help rental markets rebalance. But there is still a significant amount of previously approved and currently under-construction inventory that has yet to reach tenants. Follow the Money The episode also looks at why investors naturally gravitated toward multi-unit development. Imagine owning a large lot. Building one new house may not generate an attractive enough return. Build two homes and the economics improve. Build eight or twelve rental units with favourable development rules and financing incentives, and suddenly the numbers look much more attractive. Investors responded to the incentives that existed. Builders responded to demand from investors. Municipalities changed zoning to encourage density. The result was predictable. A tremendous amount of multi-unit housing was proposed and built. Does Canada Still Need More Houses? Wayne's answer is: Probably. But he is careful to call that his interpretation rather than a proven conclusion because the available information does not provide enough detail. There may be markets where rental units are becoming oversupplied while traditional family housing remains relatively scarce. That distinction matters enormously to investors. If you simply hear: "Housing starts are down" and make an investment decision from that headline, you are missing most of the story. Understand the Property You Actually Own For Wayne, the lesson comes back to the fundamentals. Don't invest based on a national headline. Understand: Your city Your neighbourhood Your property type Your tenant profile Your competition Your purchase price Your rent Your expenses Your cash flow A national statistic can be useful information. It should not replace local market analysis. REI Masters Mentorship Special Offer Anyone who joins the REI Masters Mentorship Program before October 3, 2026 receives: 24 months of mentorship for the price of 12. The offer includes an additional 12 months of coaching, education and mentorship at no additional cost, plus entry to the upcoming REI Masters annual retreat in Edmonton. Work directly with Wayne and Gabby on: Market analysis Acquisitions Financing Deal analysis Property management Joint ventures Building your personal real estate roadmap Learn more: www.reimasters.ca The 5% Rule™ Want to understand how much cash flow a rental property should produce? Search: The 5% Rule by Wayne Hillier on Amazon. Watch the Morning Show Join Wayne and Gabby every weekday morning at 7:00 AM Mountain Time on YouTube. Follow Wayne Hillier – Real Estate Investing Coach on YouTube. Questions: info@reimorningshow.com Sponsors Calvin Realty – Edmonton Investor-Focused Realtor Team www.calvinrealty.ca Finngo Bookkeeping & Tax Specialized bookkeeping and tax services for Canadian real estate investors. www.finngo.com/rei Kirkwood & Brennan Mortgage Group Investor-focused mortgage planning for Canadian real estate investors. www.kbmortgages.ca keaton@kbmortgages.ca

Matthew Hodgson, founder of Zen X Machina, joins Dave West to unpack the Raptors project, an experiment that started by accident during digital transformation work and grew into a working model for agentic teams. Hodgson explains how he built a cross-functional AI team, complete with a Scrum Master agent named Al, and what it took to get the agents to self-organize, adapt sprint by sprint, and catch their own mistakes. The conversation digs into why explicit governance files matter more with agents than with humans, where agents still need human oversight, and why traditional governance models move too slowly for agentic AI. Hodgson also previews ideas from his book, Evolve, on adaptive governance for modern product operating models.Access the whitepapers that cover the experiment and learnings.

Interview with Nick Smart, CEO, ValOre Metals Corp.Our previous interview: https://www.cruxinvestor.com/posts/valore-metals-tsxvvo-undervalued-investment-series-with-nick-smart-9774Recording date: 22nd September 2026ValOre Metals Corp. (TSXV: VO, OTCQB: KVLQF, FSE: KEQ0) is a Brazil-focused precious metals developer advancing the Pedra Branca project, a 100%-owned, near-surface platinum-palladium-gold deposit in Ceará State. The project's appeal begins with jurisdiction: roughly 90% of global PGE supply is concentrated in South Africa, Zimbabwe and Russia, each facing distinct operational or geopolitical constraints, while Pedra Branca sits outside that concentration entirely, benefiting from a four-hour paved highway link to Fortaleza's international port and airport.The current resource base - a 2022 NI 43-101 inferred estimate of 2,198 koz 2PGE+Au across seven near-surface zones - has already doubled since ValOre acquired the project at roughly 1.1 Moz, following an additional US$10 million and 23,534 metres of company-funded drilling layered onto a legacy dataset from prior owners Anglo American and Anglo Platinum. A further 5,000-6,000 metres drilled since the 2022 estimate, including five new exploration zones, has not yet been incorporated into a public resource figure, leaving a visible near-term catalyst in an updated estimate.Metallurgical testwork is the other major workstream ahead of the PEA. The company is scaling up leach testing from shake-flask to column and stirred-tank vessel trials to assess heap-leach amenability on weathered, oxidised material (roughly 40% of tonnage), while advancing conventional flotation on the fresh material that contributes the bulk of contained ounces. Recovery testwork is currently tracking in the high 70% range, with management indicating room for improvement as the flowsheet is optimised - a genuine trade-off exists between lower-capex heap leaching and higher-recovery vessel processing that the PEA will need to resolve.Management has signalled a preference for staged development over a single maximum-scale build: securing licensing for an initial phase, proving the process, and adding capacity in subsequent phases as cash flow supports it, rather than raising capital repeatedly to reach full scale before any production decision. That approach, combined with Brazil's expanding domestic PGE processing capacity - illustrated by neighbouring Bravo Mining's proposed smelter complex at the port of Barcarena, which ValOre has flagged as a potential logistically attractive buyer for future concentrate - points toward a capital-efficient path to first production rather than a single binary de-risking event.On valuation, ValOre's roughly $20M market capitalisation compares to a peer set - Bravo Mining, Platinum Group Metals, Generation Mining and Stillwater Critical Minerals - carrying market caps from ~$126M to ~$440M at broadly comparable or more advanced project stages. Insider and close-associate ownership stands at 30% combined, with resource and mining funds holding a further 25%. Cash on hand was under $0.8M as of September 1, 2026, against 255M shares outstanding (304.2M fully diluted), underscoring that near-term financing will likely be required to fund the PEA and subsequent development studies. The company's key near-term catalysts are the updated resource estimate, the Q4 2026 PEA, and subsequent licensing steps into Q1 2027.Learn more: https://www.cruxinvestor.com/companies/valore-metalsSign up for Crux Investor: https://cruxinvestor.com/subscribe

Anthropic has launched Claude Opus 5.5, a new artificial intelligence model designed to balance high performance with rigorous safety standards. This latest release claims to be 40% more cost-effective and over 30% faster than its predecessor while excelling in complex tasks like agentic coding and research. Despite recent industry debates regarding the speed of AI development, the company emphasizes that this version achieved the highest alignment scores to date during internal testing. Developers can now utilize the model through various platforms and a new TypeScript SDK, benefiting from a massive one-million-token context window. Additionally, users on professional plans will see increased usage limits, allowing for more extensive interaction with the model's improved natural communication and instruction-following capabilities. Successive releases for the Sonnet and Haiku tiers are expected to follow in the coming weeks.

Leadership communication becomes increasingly important as developers move beyond writing code and begin leading people, projects, and technical decisions. Being the smartest person in the room does not automatically make you the most effective leader. In fact, technical expertise can sometimes work against a team when the people with the strongest opinions dominate the conversation while everyone else quietly checks out. In this episode of Develpreneur, Rob Broadhead and Michael Meloche talk with leadership communication coach Salvatore Manzi about what happens when developers and technical experts move beyond writing code and begin leading people. The conversation focuses on learning how to make sure people understand one another, contribute their ideas, and work together instead of simply talking past each other. About Salvatore Manzi Salvatore Manzi is a leadership communication coach whose work sits at the intersection of leadership, communication, and collaboration. He works with teams and analytical professionals to improve how they communicate so they can collaborate more effectively and move their ideas forward. Salvatore is also the author of Clear and Compelling: Communication Strategies for Big Thinkers. During the Develpreneur interview, he explained that the book draws on twenty years of communication strategies and is aimed particularly at analytical, technology, and data-driven professionals with bold ideas. His work fits closely with the theme of this season of Develpreneur: building a career beyond the code. Technical knowledge can help you develop the idea, but leadership communication helps you explain it, build support for it, and bring other people along with you. Social: Facebook / YouTube / Instagram / LinkedIn Website: Salvatore Manzi's Website Leadership Communication Starts With Understanding Technical professionals are trained to process information quickly. Someone explains a problem; our brains immediately start analyzing it. This happens even before the other person has finished speaking; we may already be constructing a solution. That speed can be useful when solving technical problems. It can also create problems when working with people. Salvatore recommends starting disagreements with shared understanding. Before offering your own response, rephrase what you believe the other person said and confirm that you understood it correctly. The purpose is not to repeat their words back to them. It is to demonstrate that you understood the idea behind those words before adding your own perspective. For developers, this can initially feel inefficient. If everyone in the room understands the technology, why repeat something that was just said? Salvatore argues that this small investment in leadership communication can prevent much larger problems later. Rephrasing establishes a common starting point, particularly when people are working together for the first time or discussing an important decision. A simple way to develop the habit is to practice it once each day. Find one conversation where, instead of immediately responding, you rephrase what you heard and ask whether you understood correctly. Over time, that intentional pause becomes part of how you communicate. Get Your Voice Into the Meeting Early The opposite communication problem happens when someone has something useful to contribute but waits too long to speak. This is common on technical teams. When one or two people are viewed as the experts, everyone else may wait for them to speak first. Once those people begin driving the conversation, it becomes increasingly difficult for quieter team members to enter it. Salvatore recommends getting your voice into the meeting within the first five minutes. You do not need to make a profound statement or immediately solve the problem. Ask a question, acknowledge someone else's contribution, or invite another person into the discussion. The goal is simply to become an active participant instead of a passive observer. That advice applies especially well to developers who prefer to process information before speaking. Waiting until you have the perfect answer can mean never entering the conversation at all. Leadership can make that problem easier or harder. Leadership Communication Means Creating Space for Everyone A leader's responsibility is not simply to provide the best answer. Effective leadership communication also means creating an environment where the team can produce better answers together. Salvatore suggests several practical techniques for getting more people involved. One is a quick round-the-room check-in where everyone provides something that is going well and something that could be going better. The important part is establishing limits, such as one sentence for each answer, so the exercise does not turn into a series of monologues. Another technique is the 10-second rule. Ask the team a question, but tell everyone that nobody should answer for ten seconds. That short silence gives analytical team members time to process the question. Instead of rewarding whoever can speak fastest, the meeting gives everyone a chance to formulate a useful response. These techniques are simple, but that is part of their value. Improving team communication does not necessarily require a new platform, complicated process, or another meeting. Sometimes it requires changing the way an existing conversation is structured. Stop Putting People on the Spot There is also a significant difference between inviting someone into a conversation and suddenly calling on them. Anyone who remembers being unexpectedly called on in school knows the feeling. Instead of thinking about the question, your brain suddenly starts thinking about the fact that everyone is looking at you. Salvatore demonstrated a better approach during the conversation: give the person advance notice that you are coming to them, tell them the subject you want them to address, briefly move the group's attention elsewhere, and then return to them. That small handoff gives the person time to prepare mentally. Instead of creating a performance test, the leader creates an opportunity for the person to contribute. This is particularly useful for technical teams where some members may need a few moments to organize a complex answer. The goal is not to eliminate spontaneity. It is to stop confusing fast responses with valuable responses. Breaking Down Technical Silos Through Better Communication Technical organizations naturally create specialists. One person understands the database. Another understands infrastructure. Someone else knows the business rules, testing process, user interface, or deployment pipeline. Specialization helps teams solve difficult problems, but it can also create silos. Salvatore described working with a team whose individual groups functioned effectively but struggled when they came together. They were essentially speaking different languages. During a half-day session, the team worked through what they needed from one another and what they believed they were hearing from each other. They also formed smaller cross-functional groups. One surprisingly effective part of the exercise was asking people to begin by identifying something they appreciated about another person's work. That forced team members to think about what their colleagues actually contributed rather than seeing only their own piece of the system. That lesson matters in software development because it is easy to judge another role by how it affects your own work. Developers can become frustrated with QA. QA can become frustrated with developers. Technical teams can become frustrated with business stakeholders, while business stakeholders wonder why seemingly simple requests take so long. Good leadership communication helps people understand those different perspectives. Understanding what another person contributes does not eliminate disagreement, but it gives that disagreement context. What About the Person Who Never Stops Talking? Creating space for quieter voices introduces another challenge: the person who takes too much of that space. Most teams have experienced the meeting where someone gets the microphone and never seems to give it back. Salvatore recommends addressing this before it becomes a problem by establishing communication agreements for the team. Those agreements might include: Make sure every voice has an opportunity to contribute. Keep individual contributions short. Lead with the bottom line. Provide additional detail when the group needs it. Once those expectations are established, a phrase such as "bottom line" can become a shared reminder rather than a personal criticism. Everyone already understands what it means and why the team uses it. That distinction is important. Good meeting facilitation is not about silencing people. It is about managing the limited amount of attention and time available so the entire team can participate. Leadership Communication and the Move From Expert to Leader One of the biggest career transitions for developers is moving from being responsible for your own technical output to helping other people produce results. The skills that made you a strong developer do not disappear when you become a technical lead, architect, manager, or executive. However, they are no longer enough by themselves. You have to listen differently. You have to recognize when someone has stopped participating. You have to create room for people who need time to think while keeping stronger personalities from consuming the entire conversation. Most importantly, you have to stop measuring leadership communication by whether you successfully said something and start asking whether the other person actually understood it. Salvatore's advice throughout this conversation comes back to small, repeatable behaviors. Rephrase someone's idea once a day. Speak within the first five minutes of a meeting. Give people ten seconds to think. Prepare someone before handing them the conversation. Establish expectations before someone starts monopolizing the room. None of those techniques requires a major organizational transformation. They require practice. That is also what makes them valuable for developers working to build a career beyond the code. Leadership does not suddenly begin when someone gives you a management title. It develops through the way you communicate, listen, facilitate, and help the people around you contribute their best ideas. Stay Connected: Join the Developreneur Community

visionOS 27 arrives with Siri AI, curved windows, and personal environments, and the panel works through what it means alongside Apple's widening layoffs, a peer-reviewed neurosurgery study, and a rhythm game that builds levels from your own music.Host: Marty Jencius | Panelists: Eric Bolden, Dave Ginsburg, Daniel BurkholderVISIONOS 27 — THE BIG UPDATEvisionOS 27 Is Now Available — Here's What's Newhttps://www.macobserver.com/news/visionos-27-is-now-available-for-apple-vision-pro-heres-whats-new/visionOS 27 Adds Siri AI to Your Spatial Computing Environmenthttps://appleinsider.com/articles/26/09/14/visionos-27-adds-siri-ai-to-your-spatial-computing-environmentvisionOS 27 Launched for Apple Vision Pro Headsetshttps://www.uploadvr.com/visionos-27-launched-for-apple-vision-pro-headsets/EU Gets Siri AI on Vision Pro — but Not on iPhonehttps://mixed-news.com/en/visionos-27-siri-ai-apple-vision-pro-eu/Ask Siri Questions While Watching VR 180 — Community Threadhttps://www.reddit.com/r/VisionPro/comments/1wm8r00/ask_siri_any_questions_if_you_are_watching_vr_180/INDUSTRY & BUSINESSApple Layoffs 2026 — Fitness+ Team Faces Cuts After Siri, Vision Pro Restructuringhttps://www.analyticsinsight.net/jobs/apple-layoffs-2026-fitness-team-faces-cuts-after-siri-vision-pro-restructuringCONTRARIAN TAKESThe Adoption Curve, Ep. 24: Apple Kills Vision Pro Headsets to Chase Meta's Smart Glasses Leadhttps://str8digital.com/shows/the-adoption-curve/episode-24.htmlFriday Fury: Apple Vision Pro — One User's Blunt Takehttps://kiakamgar.com/posts/friday-fury-apple-vision-proRESEARCHnextViewer Scores 1.7/2.0 Among Neurosurgeons for Surgical Planninghttps://pubmed.ncbi.nlm.nih.gov/42729479/APPS & GAMINGFlow Chaser: Build a Rhythm Level from Any Song You Own — $14.99https://www.uploadvr.com/flow-chaser-brings-procedural-spatial-rhythm-gameplay-to-apple-vision-pro/https://mixed-news.com/en/flow-chaser-vision-pro-rhythm-levels-from-your-own-music/Developer post: https://x.com/Brian_Corrieri/status/2099877065428222036Gameplay reaction: https://x.com/robiegomez/status/2101386311076573330PATENT WATCHPatently Apple — New Vision Pro Patent Filinghttps://x.com/PatentlyApple/status/2099868867598377078XR COMMUNITY VOICESVoices from the Field on visionOS 27https://x.com/hunter_spatial/status/2100329478329450672https://x.com/EinarJohnson_XR/status/2100018160531542267DEVELOPER CORNERHow to Build Vision Pro WebXR Apps: 5 Coding Secretshttps://msinformationtech.blogspot.com/2026/09/how-to-build-vision-pro-webxr-apps-5.htmlCONTACT & FOLLOWVision ProFiles is part of The PodTalk Network — https://www.thepodtalk.netYouTube.com/@VisionProFilesThePodTalkNetwork@gmail.com

Communities across the U.S. are being asked to make increasingly consequential decisions about data centers at the same time that AI infrastructure development is moving faster than traditional municipal planning processes. On this episode of the Data Center Frontier Show, DCF Editor-in-Chief Matt Vincent speaks with Ilissa Miller, founder and CEO of iMiller Public Relations and a board member of the Open Infrastructure Exchange (OIX), about a new effort to help communities prepare before specific data center projects arrive. At the center of the conversation is the OIX Digital Infrastructure Framework, designed to give municipal planners and elected officials a structured set of questions for evaluating data centers and other digital infrastructure. Rather than prescribing what communities should approve, Miller says the framework is intended to help them determine where digital infrastructure fits within their own long-term land-use strategies. Many municipalities, she notes, still do not explicitly recognize data centers as an acceptable land use — even on parcels already designated for industrial activity. That can send developers into conditional-use or zoning processes while residents and public officials are still trying to understand what exactly is being proposed. Miller argues that comprehensive planning offers a better starting point. Communities should be deciding in advance where different types of digital infrastructure might be appropriate, what information developers will need to provide, and how data centers fit alongside other economic-development priorities. The need has become particularly acute as opposition to data centers increasingly overlaps with broader public anxiety about artificial intelligence. “Most opposition is about more than the data center itself,” Miller says. Concerns over AI governance, automation and societal impacts are legitimate topics for debate, she argues, but they are not necessarily the same questions local officials must answer when evaluating land use, power, water, noise, construction and community impacts. For developers, Miller says earlier community engagement is equally important. Engagement should begin before a conditional-use application and before a project design has effectively been finalized. Developers should hold listening sessions, understand local business and political dynamics and give communities a meaningful opportunity to influence project plans. “The key to those engagements and those listening events is actually listening,” Miller says. That means showing communities what was heard, explaining what changed as a result and tailoring community benefits to actual local priorities rather than arriving with a standardized package. But Miller also emphasizes that communications cannot compensate for a poorly conceived project. “Not all data center developments should be built,” she says. Her firm will decline engagements involving certain attempts to rezone agricultural or otherwise inappropriate land for data center development. Miller argues that developers should look first toward properly zoned industrial locations, redevelopment opportunities and sites where intensive land use already exists. That principle gets to the larger question of social license: community trust begins with project execution and site selection, not simply better messaging. The conversation also explores perhaps the most difficult challenge facing both the industry and municipalities — speed. AI chip development is occurring on cycles measured in months or a few years, while data center development, municipal planning and infrastructure investment historically operate over much longer timelines. Miller says the industry itself is struggling to absorb that pace. Looking five years ahead, she envisions communities incorporating digital infrastructure directly into comprehensive master plans, distinguishing between hyperscale AI campuses, colocation, carrier hotels, edge facilities and other forms of digital infrastructure. Not every community needs — or can support — a massive AI data center. But Miller argues that communities still need to understand the infrastructure requirements of their hospitals, manufacturers, businesses and public services. The objective is not to ensure that every data center gets built. It is to ensure that when a proposal does arrive, the community is no longer beginning the conversation from zero.

An Auckland developer says house-building projects she has in the city sitting idle, may become viable under new development levy rules. 

Malcolm Shaw is a former geologist, sell-side analyst and hedge fund energy and mining investor. He is a proven junior resource stock picker and has invested for himself since the end of 2011. This is his first ever podcast interview. Malcolm keeps a low profile and grows his newsletter, The Circle, almost entirely by word of mouth. Bill and Malcolm first crossed paths on a due diligence call about five years ago. They cover Malcolm's path from Calgary geologist to Bay Street, why he doesn't try to call commodity prices, how he sizes and exits positions, and the stories behind his biggest winners and one current loser. In this MSE episode, Malcolm explains his rational approach to junior resource speculation. Listen and learn! 00:00 Intro 00:29 Meet Malcolm Shaw 01:09 From Geologist to Analyst 02:35 Sell Side vs Buy Side 04:05 Going Independent 05:38 Why Start a Newsletter 09:51 No Forecasting Just Positioning 13:36 Deal Flow and Watchlists 16:40 Holding Periods and Exits 18:56 Portfolio Construction and Big Bets 21:32 Tenaz Energy Case Study 26:19 Mining Winner Alpha Minerals 29:27 Developers and Production Plays 32:05 Marketing and Sector Allocation 34:22 Niche Metals and Competence 36:05 Network Driven Due Diligence 38:17 Biggest Loser Lessons Malcolm's newsletter: https://www.thecircle.ca/ Sign up for our free newsletter and receive interview transcripts, stock profiles and investment ideas: http://eepurl.com/cHxJ39 Mining Stock Education (MSE) offers informational content based on available data but it does not constitute investment, tax, or legal advice. It may not be appropriate for all situations or objectives. Readers and listeners should seek professional advice, make independent investigations and assessments before investing. MSE does not guarantee the accuracy or completeness of its content and should not be solely relied upon for investment decisions. MSE and its owner may hold financial interests in the companies discussed and can trade such securities without notice. MSE is biased towards its advertising sponsors which make this platform possible. MSE is not liable for representations, warranties, or omissions in its content. By accessing MSE content, users agree that MSE and its affiliates bear no liability related to the information provided or the investment decisions you make. Full disclaimer: https://www.miningstockeducation.com/disclaimer/

Tickets for AIE NYC now open, and apply for the invite-only AIE CODE. Join us!We have an unusual relationship with today's guest: for years since coauthoring the InstructGPT paper, Diogo Almeida had been saying that API-available frontier models have been going down the wrong path, everything from the alignment to refusals to reliability perspectives, that we have dropped every mode other than autoregressive chat-tuned LLMs because of the overwhelming success of ChatGPT.In a launch video now viewed ~40M times (by comparison, GPT4o was 22M, Fable 5 was 15M, Navier Stokes was 74M, and 6 Astra was 137M), Diogo introduced Jev and it immediately took over the AI timeline — we'll skip full Jev explainers because your favorite AI influencer/educator has probably already done one. We also collected:* the official patterns and cookbooks you should see first, from Allie* Jev usecases* speed based - games and computer use* the voice + computer use example we discuss at 1h34 mins* voice + browser control* The must not miss Doom demo* Driving cars in games* Excalidraw* virtual try-ons* “Smart Games”/smart NPCs* guided responses in text messages* Jev for coding agents has an official guide * jev for linting* compacting tool calls* reasonable pushback from Theo - Diogo has published a note on the Tyranny of the KV Cache that you should read as a followup after the pod for Jev + coding agents, because of his belief that Cache Rules Everything* Programming Languages built atop Jev (Diogo's fave)* Jev for analytics replay and user journey review* “dark data”* entity resolution* natural language search* “smart software”* a core goal of Jev is to “disappear into the background” - eg as unremarkable as regex* Jev as a judge* Jev memes* Jev vs LLM capabiltiies* blending transformers and classifiers* about the confidence api* Jev vs GLiNER (note difference/pushback, agreed, agreed, agreed)* Jev on trolley problem* Jev BushInstead we'll focus on what we can uniquely offer — a broader philosophical and mission-based understanding of how and why Jev was created, and what you should expect next in terms of future models from TypeSafe (ReasoningJev?) and what usecases and ideas you should work on vs the 55th low effort clone of Jev's API or doing a generic JevBench benchmark - something Diogo has rejected publicly.Why RLCD: Three kinds of RLHF, and why they are ALL the wrong north starDiogo knows a good deal about RLHF, given that he was on the team that pioneered post-training at OpenAI — and traces the three branches to Christiano et al 2017 (the robot backflip demo), Stiennon et al 2020 (learning to summarize) and his baby, Ouyang et al 2022 (InstructGPT). From there on, every innovation from Function Calling to Structured Outputs to Reasoning felt like a hack on top of the string based, sequence to sequence prediction paradigm. As he mentions on the pod, from 2023-2024 he struggled unsuccessfully, due to both personal and organization underestimation, to train a model that accurately addressed what he saw as the core problem with making LLMs the heart of software: reliability.Jev's core innovation is "Reinforcement Learning for Calibrated Decisions”, a novel, unpublished technique that optimizes for “answers with epistemically honest probabilities on System One tasks” rather than human rated feedback (RLHF) — which causes hallucinations, sycophancy, and permanent reliance on humans — or programmatically verifiable outputs with rubrics (RLVR) — which solves Navier Stokes but exacerbates jagged intelligence and doesn't integrate well with other software.We've talked about the calibration problem before on the pod, but probably the single best place to understand why RLCD became necessary is Diogo's AIE talk, which discusses why a generation of training helpful AI assistants for humans has impaired them for training models for composable, programmable AI for automation.At the end he also teases his contrarian opinion on scaling laws - which teases how to build a modern neolab without the billions of dollars the major labs have…The Bitterest Lesson: Tasks and Data beats ComputeWe spend a good amount of time discussing Diogo's essay on the Bitterest Lesson:His point is that “You get what you optimize for and the bitterest lesson in ML is that the most important part of it isn't ML at all.” - and picking the right north star, eg upvoting for user preference vs being integrated into tool calls - makes everything else fall in line.We're excited to catch up with a freshly dyed Diogo to discuss:* Why AI can solve extraordinarily hard problems but still fail to automate basic work* What System One Models are and why Jev is built for software rather than chat* RLHF, mode collapse, calibration, and the hidden costs of optimizing for human preferences* Why refusals become a problem when AI is buried inside software dependencies* Why TypeSafe rejects public benchmarks and optimizes for intelligence per dollar* The “bitterest lesson”: why the right task and the right data can matter more than compute* Why TypeSafe thinks of itself as a data lab rather than a model lab* RLCD vs. RLHF and RLVR as fundamentally different North Stars for AI* Why reliability and robustness matter more than simple determinism* Jev's programming primitives and how intelligence maps into software control flow* Why developers should decompose AI workflows into small, measurable decisions* How structured state replaces giant prompts and system messages* Why Diogo thinks AI should eventually disappear into the background of software* The “inverse SaaS-pocalypse” and how AI could supercharge existing software* System One vs. System Two intelligence and the limits of reasoning models* Dark data, computer use, real-time intelligence, and Jev's biggest early use cases* Why Jev could reshape coding agents built around a single-model architecture* Why Diogo says he wouldn't pre-train with $1 billion* The OpenAI journey that led to TypeSafe and why he thinks many neo-labs are approaching AI incorrectly* Coding agents beyond the KV cache, shared state, sub-agents, and the multi-agent futureDiogo Almeida* LinkedIn: https://www.linkedin.com/in/diogomda* X: https://x.com/CompleteSkeptic* TypeSafe AI: https://typesafe.ai/Timestamps00:00:00 Jev Launch Week and the AI Economic Revolution00:02:50 What Is Jev? System One Models and Programmable AI00:05:54 RLHF, Mode Collapse, Calibration, and Yann LeCun00:10:29 Programmatic AI, Refusals, and Safety Alignment00:17:21 Why TypeSafe Rejects Public Benchmarks00:20:43 The Bitterest Lesson: Data, Compute, and the Right Task00:24:59 RLCD vs. RLHF and RLVR00:28:42 Why Powerful AI Still Hasn't Automated the Economy00:39:55 Reliability, Robustness, and Determinism00:48:11 Model Versioning, LTS, Speed, and Intelligence per Dollar00:54:04 Inside Jev's API and Programming Primitives00:58:28 How to Build with Jev: Structure, Decomposition, and Small Decisions01:18:28 The Inverse SaaS-pocalypse and AI Disappearing into Software01:33:21 Computer Use, Dark Data, and Jev's Biggest Use Cases01:38:48 How Jev Could Reshape Coding Agents01:41:00 AI Safety, Frontier Pacing, and the Limits of RLVR01:48:03 Why Diogo Wouldn't Pre-Train with $1 Billion01:55:19 The OpenAI Story Behind TypeSafe02:01:41 Why Diogo Thinks Most Neo-Labs Are Getting AI Wrong02:08:00 Coding Agents Beyond the KV Cache and the Multi-Agent FutureTranscriptIntroduction: Jev Launch Week and Developer MomentumSwyx [00:00:00]: Okay, we're in the studio. A special occasion because this week, Diogo, my good buddy, launched Jev, and it's been taking over the complete timeline. How do you feel? What's it like to be you right now?Diogo Almeida [00:00:16]: Emotionally?Swyx [00:00:17]: Yeah.Diogo Almeida [00:00:17]: Never been worse. Like, I'm a ragged corpse of a person right now because there's so much going on, and I'm like a technical CEO, so I have, like, a lot of fires to fight.Swyx [00:00:29]: Yeah.Diogo Almeida [00:00:29]: But mentally, I feel—I say this all the time, and I've been saying this kind of for years in my over-under events. Like, I feel like the entire AI field is like one of those, like, carnival house of mirrors, and everyone is just insane and saying the weirdest stuff that doesn't make sense. And it feels like for just this week, like, I'm on a better in sync with reality and like, oh, people see it now. AI can be so much more than what was once thought.Diogo Almeida [00:01:06]: And like, yes, we are going to make. Like, an AI-based economic revolution is back on the table, and this is f*****g awesome.Diogo Almeida [00:01:17]: I'm so jazzed the developers get it. It's, it's, Yeah, and I want to show my eternal gratitude to the developers andSwyx [00:01:25]: Yeah.Diogo Almeida [00:01:26]: I'm so jazzed about the community and everything. It's so great.Swyx [00:01:28]: Yeah, you were saying yesterday that you decided to prioritize the town hall and not a bunch of, like, VIP, investor-type people because you wanted to make sure that they are the people that you get your most, attention, right? The engineers, the developers.Diogo Almeida [00:01:43]: Yeah, it felt a little like, oh man, I'm talking to, like, really important people right now.Swyx [00:01:47]: Yeah.Diogo Almeida [00:01:47]: I probably shouldn't reveal who.Swyx [00:01:48]: Yeah.Diogo Almeida [00:01:48]: But it feels a little bit dirty for me to, I'm, like, perhaps overly genuine in things. Like, it feels, like, dirty if, like, in my gigantic calendar event of people to talk to, the community isn't one of those.Swyx [00:02:04]: Yeah.Diogo Almeida [00:02:04]: And actually, in my ideal world, it would be, like, community all the time. I was thinking, “Should I host a town hall while walking to your studio?” And I'm like, “No, that's too crazy.”Swyx [00:02:12]: Sure. Yeah. Well, you guys have been hosting town halls on Discord. Discord is now 100,000 people. Your Twitter'sDiogo Almeida [00:02:19]: I don't follow these stats.Swyx [00:02:20]: Yeah.Diogo Almeida [00:02:20]: So holy s**t.Swyx [00:02:21]: Your Twitter's blown up. It was, it was really funny ‘cause, like, at AIE, you were like, “Yeah, follow me please,” and then you didn't, like, provide even your handle.Diogo Almeida [00:02:29]: I'm a noob. I'm a noob.Swyx [00:02:29]: You're such a noob.Diogo Almeida [00:02:30]: I'm a noob.Swyx [00:02:31]: But no, but that, like, that's, like, positive aura that, likeDiogo Almeida [00:02:33]: CoolSwyx [00:02:33]: You don't know how to promote yourself.Diogo Almeida [00:02:35]: Yeah. Someone, like, called me out when I posted, like, “Holy s**t, we're all three twending-- trending topics.” And then they're like, “That's a personal feed.”Swyx [00:02:42]: That's a personal, yeah.Diogo Almeida [00:02:43]: And I'm like, “Oh, no.”Swyx [00:02:44]: Of course, of course it'll trend to you.Diogo Almeida [00:02:45]: Cringe. Yeah.Swyx [00:02:45]: Yes, ‘cause it's what you clicked on.Diogo Almeida [00:02:47]: Yeah.Swyx [00:02:47]: So okay. Let's, Yeah, so congrats on everything.What Is Jev? System 1 Models and Intelligence per DollarDiogo Almeida [00:02:50]: Thank you.Swyx [00:02:50]: We'll talk about more, details as you have them. But let's, for people who are, like, living under a rock or just want, like, the definitive thing, what is Jev?Diogo Almeida [00:03:02]: Whew. Let me think about. That's a hard one.Swyx [00:03:07]: Okay. And I'm happy to, like, re-ask if you wanna kind ofDiogo Almeida [00:03:09]: No. I'm happy toSwyx [00:03:10]: OkayDiogo Almeida [00:03:10]: I'm happy to, like, just jam on it.Swyx [00:03:12]: Yeah.Diogo Almeida [00:03:13]: I will say, like, the first thing that I'm relieved about with this question is now I don't have to answer that question to my parents anymore ‘cause ChatGPT can just explain it.Swyx [00:03:20]: Nice.Diogo Almeida [00:03:21]: So the way I see it is we new-- need a new class of models. We're not attached to naming that class of models. Our-- the most accurate name we've come up with is System 1 models.Swyx [00:03:33]: Yeah.Diogo Almeida [00:03:33]: There will be reasons, but it's-- there's a reason why we don't call them decision models, because, like, they will be. Like, System 1 is beyond that. That's all I can say. We didn't expect this to be our big launch, so we have stuff in the tank.Swyx [00:03:48]: You should have said low-key research preview.Diogo Almeida [00:03:52]: It kind of was, right? It kind of was. But we. So there's a class of models that we describe them as, like, machine-native, System 1, large programmable. I think these are-- is the class of models where the goal is for code to be the consumer. So as opposed to, lar-- pre-trained large language models, which are meant for, like, autocomplete of the internet, or RLHF models, like chatbot instruction-following models, which are meant to, like, reply to text, or RLVR. It's in a weird gray area with RLHF. Like, these are meant to have things that directly are consumed by code, hence the name type safe. So the thing we really want is to have, like, AI, like, be as powerful as possible, and we think the way to do that is to integrate it with software. And we are designing everything, beyond just the outside, the deep internals of the model to be optimized for software. So number one, Jev is our first large programmable model, or a System 1 model, whatever you want to call it. Jev is meant to be optimized for intelligence per dollar, hence the name Jev.Swyx [00:05:03]: Jevons Paradox.Diogo Almeida [00:05:03]: Jevons Paradox, yeah. And it's optimized for intelligence per dollar. I love this debate with people about what is the most important between reliability, cost, calibration, and speed. And Jev is meant to be. Jev will be the name of models that will be on the frontier of intelligence per dollar. There's other ways to optimize it, like, ML, or at least if you're good at ML, it's all about trade-offs. And we are just going all out on that.Calibration, Mode Collapse, and the Limits of RLHFSwyx [00:05:31]: Yeah. And to me, like, calibration is one of the new things that people weren't talking about as much. We've done an episode In the past, with Clementine Foreia of Hugging Face, where they were like, “Yeah, actually, y- they're just.” Or, and this is your whole argument about RLHF, is they're more collapsing towards what you want to hear the mostDiogo Almeida [00:05:50]: OohSwyx [00:05:50]: Or what is most likely, instead of, like, their own internal confidence about a thing.Diogo Almeida [00:05:54]: Can I soapbox on that for a second?Swyx [00:05:56]: Go ahead. Yeah.Diogo Almeida [00:05:57]: Cool. Like, I've been heard that your audience is the most technical, so I actually want to get into that.Swyx [00:06:02]: Yeah.Diogo Almeida [00:06:03]: And if- I went through extreme precision to make sure everything in our launch video is accurate and real. Apparently, that's very unusual. One of the things that no one paid attention to was the downsides of RLHF, in particular mode dropping.Swyx [00:06:17]: Mode dropping or mode collapse?Diogo Almeida [00:06:19]: It's the same thing.Swyx [00:06:19]: Is that what you call it?Diogo Almeida [00:06:20]: It's the same thing.Swyx [00:06:20]: All right.Diogo Almeida [00:06:21]: And I wanna have a blog on this eventually, but I, like, want to tell as many people this as possible ‘cause I think it's a very interesting thing. So the spicy take, I believe in Yann LeCun a lot. I think Yann LeCun's takes are actually among the closest toSwyx [00:06:36]: What about this?Diogo Almeida [00:06:37]: Well, should I address this now or should I wait and go into mode collapse?Swyx [00:06:40]: No, later. Go mode, go mode collapse. I don't know.Diogo Almeida [00:06:42]: So I actually think that among takes, Yann LeCun's is among the most accurate. But he has this very famous/infamous slide about,Swyx [00:06:52]: The cake?Diogo Almeida [00:06:53]: LLMs are doomed.Swyx [00:06:54]: Okay.Diogo Almeida [00:06:54]: Like that one where he, like, has, like, a pie chart with, like, a tiny par-- tiny little thing- and says that as you increase sequence length, the probability of it making an error goes in. Yes, this one. This one. I love this one, because it's one of these things that seems mathematically obvious, but is obviously wrong, right? Like, it's mathematically obvious, but it doesn't empirically hold. And this is my favorite thing to teach people about, like, where youSwyx [00:07:21]: What's the disconnect, right?Diogo Almeida [00:07:22]: Exactly. And may I or you want to tell me?Swyx [00:07:27]: About mode collapse?Diogo Almeida [00:07:28]: Oh, no. Oh, so mode clop-- collapse is related to this.Swyx [00:07:31]: Yeah.Diogo Almeida [00:07:31]: The disconnect happens because if you are in a mode covering or a calibrated distribution, you are, like, not. You are not overly punished about having outliers. You'd expect, like, something. Some amount of the time you'd be out of distribution, some amount of time you'd be in distribution. That's what happens when you cover the distribution. This was like models before GANs. They made blurry images, right?Diogo Almeida [00:07:54]: Instead, GANs mode drop. They, like, drop the minority classes and just do the really common ones. And this is why this effect doesn't happen, right? Like, instead of be-- in order to generate really long strings, without making errors, they need to, like, be extremely conservative because it's e- really easy to see when an error happens. It's very hard to see when, like, a subtle thing that looks correct happens. And that calibration is, like, total poison into, like, the probability distributions of strings.Swyx [00:08:22]: Yeah.Diogo Almeida [00:08:23]: And it's, it's a nuanced take and like, I think that This is why this doesn't happen, and this is why strings are so bad at, decision-making or, overloading the string models are for decision-making is, like, a bad time.Yann LeCun, JEPA, Scaling Laws, and Practical ResearchSwyx [00:08:38]: And while we're on the topic of Yann, do you agree that his fix i- with-- which is like a world model, like a JEPA-type, embedding thing is the right solve? So basically, like, the. One of the reasons that it could fail is because you're trying to reason over token outputs and then, and then just looping back again and going. Keep, continuing going until you reach, like, a end of sentence. Like, is that, And his solve is JEPA, right?Diogo Almeida [00:09:02]: Yes.Swyx [00:09:02]: Which is, like, joint ambition,Diogo Almeida [00:09:04]: YeahSwyx [00:09:04]: Joint embedding prediction. So like, is that the solve or, like, do you have a. Do you have a take on that?Diogo Almeida [00:09:10]: Oh, man. I probably shouldn't talk too much about the insides of ML, but I will say that my brand, other than unhinged, is practical.Diogo Almeida [00:09:20]: Like, even my take here is practical. And like, I'm. Am I a scaling law fan? Depends. It dep-- it's, it's, it's, like, it's. Scaling laws tell you how much better you get at a thing for amount in.Diogo Almeida [00:09:33]: A scaling law does mean exponentially more resources for normally sublinear gains, which looks to be a bad investment unless those, like, linear gains are, like, really valuable. But it's all. To me, it's all about, like, what can we do with what we have to make the biggest possible f*****g difference? I can curse.Swyx [00:09:51]: Yeah.Diogo Almeida [00:09:51]: Yeah.Swyx [00:09:52]: Yeah.Diogo Almeida [00:09:52]: Yeah.Swyx [00:09:53]: We're, we're, we're approved for adults.Diogo Almeida [00:09:54]: Hell yeah.Swyx [00:09:55]: And also we have a scaling law thing if you wanna go into that later.Diogo Almeida [00:09:58]: Oh, I could if we. See, that part is not super relevant right now.Swyx [00:10:02]: Yeah.Diogo Almeida [00:10:03]: I actually. If you wanna go into my bitterest lesson, I think that's more relevant.Swyx [00:10:06]: Okay.Diogo Almeida [00:10:06]: But like, to me, I'm all about, like, pragmatics. And I think that the JEPA stuff is really cool early research. I really love awesome research. Is it practical yet?Diogo Almeida [00:10:21]: Probably shouldn't say. But like, there's just a lot of.Diogo Almeida [00:10:29]: I just think there's just, like, so many diamonds in the rough let all over the research world right now that haven't been polished because people don't know how to, like, do the right task. And I think that what our launch did, it. Does it kickstart us as a company? Like, yes. Will it be great for us as a company? Yes. I think it's gonna be, like, even greater for this direction of, like, programmatic AI. There was going to be, like, a gold rush on top of us for. ‘cause, like, software is super f*****g charged. But I think there's gonna be a gold rush parallel to us as well on, like, all the different ways we can expose things to make software more powerful so people can make even cooler stuff. And then we are back to, like, early internet energy?Swyx [00:11:12]: Yeah.Diogo Almeida [00:11:12]: And I think that's why, like, the Twitter is just like, “Jev.”? It's, it's like. It is a partySwyx [00:11:18]: It's inspiring because it's, it's, like, so different than what we're used to, which is, “I'm sorry you can't do this, but we do scaling laws and only the big labs can do it,” right?Diogo Almeida [00:11:28]: That. Actually, if I. I'll, I'll make a tangent if that's okay.Swyx [00:11:32]: Yeah.Diogo Almeida [00:11:32]: I think you might enjoy this.Swyx [00:11:33]: Really? Our five tangents in. It's good. It's fun. Yeah.Diogo Almeida [00:11:35]: Oh, yeah. I get lost at all my tangents.Swyx [00:11:37]: This is gonna be horrible for the listeners to figure it out, but they're gonna figure it out. It's fine.Safety Alignment, Refusals, and API PhilosophyDiogo Almeida [00:11:40]: Yeah, we can edit it in post.Swyx [00:11:40]: This is my response. Yeah.Diogo Almeida [00:11:41]: So popular thing on Discord, that people keep asking me, I haven't had the time to explain it yet, is why am I opposed to safety alignment and why do we not refuse? I'm not opposed to safety as a principle, but I think that safety alignment is generally misaligned with users. And refusal is just, like, obviously a type error. Like, if you're a human being and you're chatting with, like, a bot or whatever, you're cloud coding, and a refusal happens, like, “I'm sorry, I can't read DNA.py.” that's an annoying time. It's anno- it's, it's annoyingDiogo Almeida [00:12:18]: Right? But you can work with it, right? And you're forced to work with it ‘cause of Stockholm syndrome.Diogo Almeida [00:12:23]: I have stories about that too. I need another tangent deep in here. But like, if you ever want this in a dependency running in the background, what happens if that refuses? What if someone else is using that dependency? They don't know what that system is. Like, you want the software to just stochastically break because a user sent, like, a weird message in there?Diogo Almeida [00:12:42]: Like, that is, like, straight-up insanity. It's coming from a place of, like, people who do not understand software, do not understand programming, and like, they are obsessed with, like, I believe this, horseless carriage of, like, AI coworker instead of unearthing, like, the full power of AI.Swyx [00:13:01]: Fair enough.Diogo Almeida [00:13:01]: Yeah.Swyx [00:13:01]: You want something that is the core kernel that is usable everywhere.Diogo Almeida [00:13:05]: Yes. Exactly. Like, the cognitive core, right?Swyx [00:13:07]: Yeah.Diogo Almeida [00:13:08]: And you need this thing to be s- like, so general, so optimized for its use cases. You want it to be, like, you want it to work on all the future use cases, all the weird s**t that people are doing.Swyx [00:13:19]: Yeah.Diogo Almeida [00:13:19]: We obviously didn't train on any of that stuff. Is it surprising that it works? No, ‘cause we trained on weirder stuff, my friend.Diogo Almeida [00:13:28]: So. But one tangent up about, like, safety alignment.Swyx [00:13:32]: Okay.Diogo Almeida [00:13:32]: Safety alignment makes sense for a product, in my opinion, for, like, ChatGPT and Claude. Like, it, What safety, what makes safety and capability alignment different is capability alignment is, like, about doing what the user wants. That is sick for software engineers. They want their thing to do the thing, and the more predictable it is, the less they have to test it and play around with it. Jeb is not anywhere close to that yet. It could be, but like, there's so many more nines of reliability that we want in order to make it so good, like a database query, that you don't even have to think about it. It is just there when you need intelligence. But safety alignment is, like, the opposite of instruction following. It's when you want to follow someone else's instructions, like OpenAI and AnthropicSwyx [00:14:13]: The RAGs value stack.Diogo Almeida [00:14:14]: Exactly. And this makes a lot of sense for a product. Again, like, ChatGPT should do. Y- you sh- like, if they don't want to, like, do, like, some, not-safe-for-work role play with ChatGPT, that's on them because, like, maybe that's, what their users who have, like, parents and kids want. Like, n- that's fine. But in an API, that's nuts, right? Like, that's completely unacceptable because, like, people need to, like, program around this, and that is, that's so anti-user that it's. It. I'm. Huh. I can be an angry person, so I should try to calm down.Swyx [00:14:52]: It's, People get your passion, and I think that's really good. The one pushback I'll give you is, like, what if we use it to kill people, right? Like, that is the actual. Like, n- the not-safe-for-work thing, it's private, personal, whatever. But like, yes, like, we will use it in war. And like, that is, something that companies can reasonably prefer their APIs not be used for.Diogo Almeida [00:15:14]: I get that. I think that there's, like, pragmatic places where that opinion can be held. I don't think the foundation of, like, a general-purpose technology is that place, personally.Diogo Almeida [00:15:27]: Like, would I prefer that our stuff is not used to kill people? Obviously. Would I prefer it's used for, like, all sorts of, like, great stuff in the world? Obviously. Will I put my thumb in the scale for that? Yes. Will I do it at the technological layer? Absolutely not, because that will fracture the intelligence. Every single time you mean it to overfit to some weird stuff, you're fracturing its intelligence more and more. And like, these things are fractured to the, like. They're so darn fractured right now.Swyx [00:15:54]: Yeah.Diogo Almeida [00:15:54]: So and as a furthermore thing, to me, it's like I think intelligence will be more like a database than a coworker. Like, I don't think it's up to databases to add checks on whether or not they're used for, like, what's something that's not great? Like, CIA. Actually, I don't know what the CIA does, really. You can imagine. You can imagine, killing people who are not even bad or whatever.Diogo Almeida [00:16:21]: And like, I don't think it's the database's responsibility for that. And furthermore, like, a thing that has been weird to me is when people, like, sign up for our thing on Slack and they're like, “Hey, we're gonna deploy this. Can we deploy this thing?” I am just like, “My brother, we are an API. You are a developer. It's none of my business,” right? Like, you shouldn't know what the whole task even isSwyx [00:16:46]: YeahDiogo Almeida [00:16:46]: Because it should be decomposed into small things. We shouldn't be able to know what the downstream users are doing, and that is, like, a good boundary to give software engineers maximum power. Ideally, they use it for the good stuff, and ideally, we can, like, help them and like, we've talked about, like, doing open source and charity and all of that. We have absolutely no time for anything else right now. But like, they will get any of that bias out of the technological layer as long as I'm in charge.Privacy, Benchmarking, and Trusting IntelligenceSwyx [00:17:11]: Yeah, that's great. While we're on the topic, let's also briefly talk about your privacy stuff, terms of ser- terms of use, which, got a little bit ofDiogo Almeida [00:17:18]: OohSwyx [00:17:18]: Misunderstanding. I just wanna clarify that upfront.Diogo Almeida [00:17:21]: Hell yeah.Swyx [00:17:21]: I think this probably takes two sentences from you about, like, you will not. You're not being that restrictive about your API. Like, clearlyDiogo Almeida [00:17:27]: Oh, yeah. Oh, yeah, so yeahSwyx [00:17:27]: Ideologically, you articulate your role as a platform very seriously.Diogo Almeida [00:17:30]: Yes. Yes. I don't know what you're referring to, but like, this was. I've seen a couple of things about, like, benchmarking.Swyx [00:17:38]: Yes.Diogo Almeida [00:17:38]: Like, obviously we're not stopping people from do. Oh, man, I should be careful about what I say. I'm realizingSwyx [00:17:43]: No, you said, you said it publicly thatDiogo Almeida [00:17:44]: YeahSwyx [00:17:44]: That was in the preview period. You didn't take it out for the launch.Diogo Almeida [00:17:47]: Yeah. Okay.Swyx [00:17:47]: And now you're gonna take it out.Diogo Almeida [00:17:48]: So the team is doing stuff thatSwyx [00:17:49]: YesDiogo Almeida [00:17:49]: I'm not even aware of, so it's great to know the team communicated that. I asked them to check in with the lawyers about that.Swyx [00:17:54]: Yeah.Diogo Almeida [00:17:54]: Like, we are obviously not stopping people from doing that type of thing. I'm extremely in favor. So I'm extremely anti-public benchmarks. I'm extremely in fa- I'm medium about private benchmarks that are proxies. ISwyx [00:18:09]: So are you worried about, saturation or, like, training on public benchmarks? So it's, like, easy to cheat.Diogo Almeida [00:18:15]: Not only is it easy to cheat, there's a lot of ins. So I think that we are. Or anyone who's, like, competition with us that, vaguely there is. Like, you could say, likeSwyx [00:18:28]: There's like 50 Jev clones, yeah.Diogo Almeida [00:18:30]: Well, sure.Swyx [00:18:31]: Yeah.Diogo Almeida [00:18:32]: Well, the, these. Let's say that there is competition.Swyx [00:18:34]: And we'll talk about those. Yeah.Diogo Almeida [00:18:34]: Or let's just say that there's. Let's just assume that there's an industry two years from now of people who are doing similar things to us. The thing that we are selling is intelligence per something, per, like, dollar or per second. The. No one. Like, people obsess about the cost and the speed. I believe that is. It's cool, but like, the thing that matters is the intelligence. Like, the cost and the speed are, like, are bad things. You're paying them for something, and you need the thing back, and the intelligence is what truly matters. The problem with intelligence is that there's a je ne sais quoi to it, right? Like, the good model smell. Like, the thing that happened after we launched of, like, two hours later that actually went way bigger than the video, which was like, “Holy s**t.”Swyx [00:19:16]: This is actually usable.Diogo Almeida [00:19:17]: It. WellSwyx [00:19:17]: Yeah.Diogo Almeida [00:19:17]: It's, like, beyond that.Swyx [00:19:20]: Yeah.Diogo Almeida [00:19:20]: Like, the. Whew, the launch was crazy, and people could really sense how hard we care about that, and that's truly what I think the long term of this is. And I think public benchmarks are antithetical to this. Like, they are a way to get people trust in intelligence because intelligence has a je ne sais quoi, but the public benchmarks are extremely gameable. Even if they try not to, they still will. Like, back in the old days, every lab had a team to collect data that looks like MMLU to make it look better, which is just benchmarking with extra steps.Diogo Almeida [00:19:58]: So I believe that in the long run, it needs to be vibes and trust until you put it into a workflow and evaluate it for that workflow and measure it and have your own sense of, like, how it does on the exact workflow that matters. And our job is to keep moving the nines of reliability. This is like an ever-present part of o- of what we need to be doing as a company, and we need to do everything to have people know that this is something we care so much about. Like, if we wanted to, we could have released Jev, like, a year and a half ago if we wanted it to be dumb.The Bitterest Lesson: Tasks, Data, and North StarsSwyx [00:20:34]: Oh.Diogo Almeida [00:20:34]: It. Like, the. My bitterest lesson, right? Like, architecture and Yeah.Swyx [00:20:40]: I'll bring it upDiogo Almeida [00:20:40]: Hell yeahSwyx [00:20:41]: Since you, since you talked about it, here.Diogo Almeida [00:20:43]: Hell yeah. T- like, Sutton says that algorithms beats compute very roughly. Data matters way more than compute, obviously. And doing the right task, having the North Star is the hardest, most important thing. This has happened, in LLM land twice so far, right? Maybe 2.2 times. There's RLHF, which, like, shifted the task to instruction following. No one realized that was possible. RLVR did, like, a tiny little, like, edit to the, to the direction, and now us, right? RLCD. We have a new task, and the goal is, programs in the loop. And yeah, data matters soSwyx [00:21:28]: RightDiogo Almeida [00:21:28]: Unbelievably much.Swyx [00:21:29]: SoDiogo Almeida [00:21:29]: Like, I can't, I can't emphasize it less.Swyx [00:21:31]: Yeah, you consider yourself a data lab rather than, like, a model lab. Is thatDiogo Almeida [00:21:35]: AbsolutelySwyx [00:21:35]: Something. That's the wording you guys use?Diogo Almeida [00:21:37]: Yeah. We are. We will always, like, care so much about data. To me, model capabilities means data. Data is so unbelievably complicated, and that is what gets nines. Like, you have no idea how much data can shift everything. Data is so important.TypeSafe as a Data Lab and Synthetic Data StrategySwyx [00:21:57]: Yeah.Diogo Almeida [00:21:57]: Holy crap. So if people are looking for a job, we are hiring infinite data people, actually infinite.Swyx [00:22:04]: What is a good data person? Like, clearly somebody who cares about reading through the transcripts of, whatever. You've said, for example, that y- all your data is synthetic.Diogo Almeida [00:22:15]: Yep.Swyx [00:22:15]: But that's only, like, the scratching the surface, right?Diogo Almeida [00:22:18]: Yeah.Swyx [00:22:19]: Like, it's not. Like, synthetic, so what, right? Synthetic, but we have people with a lot of taste and a lot of care looking at, looking at these, articulating what's wrong, going back, regenerating. Is that what a good data person is these days?Diogo Almeida [00:22:31]: Let me try to figure out how to. Like, it's, it's super complicated, and like, I literally onboard the data people with a Talk that I assume is longer than this podcast will end up being. So I will try to say, like, the high level of it. So number one, we don't do the kind of synthetic data that people ki. Well, I'll do. Actually, number is zero. Data and synthetic data depends on your task. Like, the shape of your data. The shape of your task changes the data. Like, RLVR's data is kind of environments, right?Swyx [00:23:03]: Yes.Diogo Almeida [00:23:04]: RLHF's is the human feedback? Each task has its own unique kind of data, and we, of course, have our own unique kind of data, right? So number one, we have that. Number two, the thing I. The reason why we don't want to train on our users' data, even if we could, right? Like, we could probably ask for any terms right now, and it will. We. I don't know if it would make a difference. We truly don't want that, because no matter what, the real-world data has so much bias. There's, like, a power law of, like, people, like, asking the same things where you'll end up, like, overfitting to it and like, fracturing to it and all of that. And number two, we are, like, aiming for, like, a complete sci-fi future years from now where, like, these models are going to be, like, the general infrastructure, layers and layers and layers and deep down the stack to, like, things people can't even imagine. Like, I would like to think of our model, like, kind of like, UDP as LLMs and TCP as our models. All sorts of stuff can be built on top of that, and we need to be able to nail those futuristic use cases such that software developers can actually build that futuristic stuff. And the way to do that is even if we had all of the data of the present, we would just overfit to the present, and then it wouldn't work. What we need is to, like.Diogo Almeida [00:24:21]: It almost feels like a. Like, they're the artists? They study this cognitive core. Our cognitive core is, like, way less jagged than anyone else's. And then they find the jaggednesses, and then they address them surgically in a way that. And you can never perfectly do this, right? But they do it in such a way that it addresses it in every single possible, like, dimension, past, present, future.Swyx [00:24:45]: The general case rather than the specific case.Diogo Almeida [00:24:47]: Exactly. And like, that requires a lot of intelligence every time.RLCD vs. RLHF: Defining a New TaskSwyx [00:24:50]: Okay, so we mentioned a little bit. You sort of criticized my thinking as r-- like, very RLVR influence, which is, like, very fair. Let us actually mention RLCDDiogo Almeida [00:24:59]: OohSwyx [00:24:59]: Which obviously you have some secret sauces to our knowledge. You've never actually published a paper or anything like that on it. No, right?Diogo Almeida [00:25:05]: No, not yet.Swyx [00:25:06]: But like, what should people get from this? Like, what. Can you give people some confidence that you're just not just making up jargon for the sake of sounding cool, right? Like, one thing for me is, like, calibration I do think is a. To me, like, well understood because we've covered it in. On the podcast.Diogo Almeida [00:25:22]: Yeah.Swyx [00:25:22]: But I don't know what you mean when you say RLCD versus what people are familiar with.Diogo Almeida [00:25:26]: It's a great question.Swyx [00:25:27]: Yes.Diogo Almeida [00:25:27]: And actually, I will give a related question.Swyx [00:25:29]: Okay.Diogo Almeida [00:25:29]: What is RLHF?Swyx [00:25:31]: Okay.Diogo Almeida [00:25:31]: Right? And actually, RLHF means multiple different things, right?Swyx [00:25:34]: Okay.Diogo Almeida [00:25:34]: Like, there's the RLHF of the original. I think it was, like, Paul Christiano teaching a robot to backflip or something like that. Wasn't there somethingSwyx [00:25:42]: Was that it?Diogo Almeida [00:25:43]: That was the originalSwyx [00:25:44]: I referenced the PPO paper, but I don't know.Diogo Almeida [00:25:46]: And so PPO was not necessarily from human feedback, if I recall.Swyx [00:25:51]: Okay. That's trueDiogo Almeida [00:25:52]: But I b- I believe it was, like, an OpenAI alignment work that could teach hard to specify outputs, like a backflip. I'm not 100% sure. And then there was actually learning to summarize. This was work, by a bunch of the team that helped with, instruct-- and co-authored, the instruction following paper, which was teaching, doing PPO on language models.Swyx [00:26:15]: This is the, sorry. I'm trying to, tryingDiogo Almeida [00:26:19]: YeahSwyx [00:26:19]: Trying to manipulate this thing. This is 2017.Diogo Almeida [00:26:23]: Yeah.Swyx [00:26:23]: Right.Diogo Almeida [00:26:23]: I'm not 100% sure, but like, that looks quite right.Swyx [00:26:26]: Yeah.Diogo Almeida [00:26:26]: If it has, like, a robot doing backflips or something like that might be it. Yes. Okay, cool. I guess I got it right. Hell yeah.Swyx [00:26:35]: There you go.Diogo Almeida [00:26:36]: Yeah.Swyx [00:26:36]: That's the one.Diogo Almeida [00:26:36]: So the idea was can, like, can you do, like, ill-specified things with it? So that's, like, version one. Version two was, the learning to summarize work, that, like, OpenAI did, which is actually, like, PPO on language models to do something somewhat ill-specified. This is, like, another thing that people refer to as RLHF Which I did not co-author.Diogo Almeida [00:26:57]: Oh, Dario's there. Cool. Hell yeah.Swyx [00:27:01]: And Radford.Diogo Almeida [00:27:02]: Yeah. Shout-outs to Alec and Ryan. Love them.Swyx [00:27:04]: Yeah.Diogo Almeida [00:27:05]: But the thing that I refer to RLHF is the, Oh, man.Diogo Almeida [00:27:13]: I'll get toSwyx [00:27:14]: You have comments on that, yeah.Diogo Almeida [00:27:15]: I have comments on that paper, but like, we're so many, tangents deep.Swyx [00:27:18]: Yeah.Diogo Almeida [00:27:18]: So the thing that really got. To me, the thing that I'm calling to RLHF is the task of instruction following. It's not about the PPO. That part doesn't matter. It's about, like, setting a North Star of this is a valuable direction. It's kind of like the Bitris lesson North Star.Diogo Almeida [00:27:34]: And for us, RLCD is this new task. And it is not. I don't see it as jargon. Like, I try to communicate with precision. It's just that, “Hey, here's another North Star.” Just like DPO and all of its, like, descendants also do RLHF, despite not using the algorithm in that paper.Swyx [00:27:55]: And so clear- clearly stating the North Star is, being program- programmable AI is one, word that I really catch onto, removing the human in the loop,Diogo Almeida [00:28:06]: YesSwyx [00:28:06]: From. Because RLHF is tuningDiogo Almeida [00:28:09]: YesSwyx [00:28:09]: For this so that you can automate everything.Diogo Almeida [00:28:11]: Yes. Everything that makesSwyx [00:28:13]: Did I miss anything else in the, in the thesis of, like, what the North Star is?Diogo Almeida [00:28:17]: There is. That is. That is right. I'm overly nuanced in my communication. The one nuance is that we need to be practical. We need to be aware of what language models can do really well. Like what AI can do.Diogo Almeida [00:28:30]: Right? Like, there could be programmatic types that are, like, sick AF, but if you. If the technology is not ready for it to. It's not a tragedy if that's not out in the world.Why Programmable AI MattersSwyx [00:28:41]: Yeah.Diogo Almeida [00:28:42]: But to me, like, the pre-Jev world was a tragedy becau-- it sounds arrogant. Hear me out.Swyx [00:28:49]: No. I strongly believe you.Diogo Almeida [00:28:50]: Cool. It sounds arrogant, but like, I felt this way since long before I even had a company.Swyx [00:28:54]: Yeah. I can, I can vouch that,Diogo Almeida [00:28:56]: Yes, I've been talking about this for so longSwyx [00:28:57]: You said this at All Around Her for, like, three years.Diogo Almeida [00:28:58]: Yeah, I've been talking about this for so long. And I've been saying it because I thought it would have been easier. They say they do not do things because they. It. They're easy. They. It's ‘cause they thought it was easy, soSwyx [00:29:08]: Yeah, exactlyDiogo Almeida [00:29:09]: Something like that. I thought it. This whole project would take a week.Diogo Almeida [00:29:13]: And I was unbelievably wrong. So I am so sorry to everyone at OpenAI that I thought. I was like, “Man, I'm solving this right now.” but like, I think that the tragic thing is when. Well, I think overpromise, underdeliver is tragic too. And like, AI is super extreme on that axis. And I think RLVR is, like, the main. Well, both RLVR and RLHF are extreme perpetrators of this.Diogo Almeida [00:29:40]: But like, it. To me, it's like it's just there's just so much potential there. Like, AI is clearly so smart. I l- smart. I love this in my talks, when I ask people, like, “How can AI be so unbelievably smart? How can we, like, solve millennium prize problems in math, but still not automate even the most basics of works?” Like, really basic rote stuff that, like, the. It d- it doesn't take, like, extremely smart people to do this. It's not a satisfying job. Like, there's other things these people could be doing, but yet we need them to do, like, this ba- like, super basic- non- unsatisfying stuff because, like, we can't automate it yet, but we have this, like, supercharged engine of automation that just does not have, like, the right plugs and stuff to plug into all of this economically valuable work. And like, if the whole company of TypeSafe disappears, like, maybe it'll take, like, a year or two for people to, like, truly catch up. I actually don't know how long it'll take. If model quality matters, then we are gonna be in a very good position for a long time. But it, like, it's done, right? Like, there, like, this has changed the path of, like, technological history.Swyx [00:30:49]: Yeah.Diogo Almeida [00:30:49]: And like, we will be exploring that space as a field.Swyx [00:30:53]: Yeah. I think, I definitely agree with that. You've created possibilities. So I think, if I can paraphrase so that people can un- also understand, you should not take the success of TypeSafe and Jev as just like, “Well, that is a new model type. Now we're done. We go back to business.” Like, no. Like, actually, there's, there are, like, five other model types that you should be exploring and like, let a thousand flowers bloom.Diogo Almeida [00:31:15]: Absolutely.Swyx [00:31:16]: Right?Diogo Almeida [00:31:16]: Like, early internetSwyx [00:31:17]: And some of that, some of which you will probably also build.Diogo Almeida [00:31:18]: Of course, yes.Swyx [00:31:19]: Yes.Diogo Almeida [00:31:19]: Early internet energy. I think it's back to tech utopia. It's no longer like, “Oh, man, like, sometimes my coding agents work, but the, all of the best ones are hoarded internally.”Swyx [00:31:29]: Yeah.Diogo Almeida [00:31:30]: Right? It's like creation is back on the menu.Diogo Almeida [00:31:34]: ? Though it's gonna be a wild-ass world, and buckle up.Diogo Almeida [00:31:38]: It's. And I'm so jazzed about that.Manifesto, Launch Strategy, and Early Internet EnergySwyx [00:31:42]: Yeah. And now you have the funding and the momentum to do whatever you envision there, which I, which I think is, like, very gratifying to see you have after, so long of saying these thingsDiogo Almeida [00:31:53]: YeahSwyx [00:31:54]: But actually show the world.Diogo Almeida [00:31:55]: I know. I just. Such a, such an interesting thing to be a tease the whole time. Like, my talk, like, felt like it was a cliffhanger ‘cause I didn't say how the automation would occur.Swyx [00:32:05]: Yeah.Diogo Almeida [00:32:06]: Sean reviewed our manifesto And he's like, “It's a little bit vague in these parts.”Diogo Almeida [00:32:12]: And like, “What's step one? What is, what is the intelligence model?”Swyx [00:32:16]: Well, I asked you for model, and you were like, “Yeah, model coming.”Diogo Almeida [00:32:18]: Yeah.Swyx [00:32:18]: And like, Well, I just, I mainly objected to the word composable But build prod.god is fantastic.Diogo Almeida [00:32:24]: Thank you.Swyx [00:32:24]: Yeah.Diogo Almeida [00:32:25]: I. We've really rallied around that. I'd like to think we're not entirely a cult like some companies are.Diogo Almeida [00:32:32]: But like, we are, like, jazzed about what we're doing, and like, we are. Like, my brand is being practical, and like, we are all, like, so super-duper practical.Swyx [00:32:42]: Yeah.Diogo Almeida [00:32:42]: It's really great.Swyx [00:32:43]: Yeah. So here. And by the way, here is the step, the secret master plan, right?Diogo Almeida [00:32:47]: Yep.Swyx [00:32:47]: Shape, the shape of machine-native composable AI.Diogo Almeida [00:32:49]: It was your idea to make a secret master plan, soSwyx [00:32:51]: It's a, it's that Elon thing. When he started TeslaDiogo Almeida [00:32:53]: YeahSwyx [00:32:53]: He was like, “Here's what we'll do.”Diogo Almeida [00:32:54]: But I did. Yeah. I'm giving official credit to you.Swyx [00:32:56]: Oh, thank you. Thank you, thank you.Diogo Almeida [00:32:56]: Yeah.Swyx [00:32:56]: Thank you. But like, you should've told me your, you're also gonna do this model launch, ‘cause you, like, you told me, you told me half of the story, and then the other half, you didn't have the doom demo at the time.Diogo Almeida [00:33:08]: Yep.Swyx [00:33:08]: You didn't have any numbers to give me.Diogo Almeida [00:33:10]: Yep.Swyx [00:33:10]: I was like, “what?”Diogo Almeida [00:33:11]: Well, the problem is I don't believe in benchmarking.Swyx [00:33:13]: Exactly.Diogo Almeida [00:33:14]: Right?Swyx [00:33:14]: Exactly.Diogo Almeida [00:33:14]: So like, it is a thing that you need to feel, and like, I think that this is the way to build long-term trust, even though it, like, hurt, it hurt us a, us a lot? Like last year when we did fundraise, no one believed us.Diogo Almeida [00:33:27]: ? Like, and they wanted just benchmarks and stuff, and we're like, “We're not gonna do that. We are principled. We're gonna stand by our guns. That rewards bad actors. I don't give a s**t, like, what you want. Like, this is who we are, and we are standing by that.” So Sorry. It's notSwyx [00:33:43]: No, yeah. Well, and in some ways, I think, like, choosing the hard path, it. But you end up making the company that you wanna work in.Diogo Almeida [00:33:49]: Yep.Swyx [00:33:50]: Right? Otherwise, if you sell out, then you're just working in, like, OpenAI but with my people, right? Which is like.Diogo Almeida [00:33:56]: Yeah. Yeah. Like, I'm, I don't have too many regrets on that, obviously.Swyx [00:34:01]: Yeah.Diogo Almeida [00:34:01]: Like, it worked out so unbelievably well. And like, I, The. I was emotional last night when I was talking about, like, the reasons I left OpenAI, and because, like, it actually had to change my wording after the launch. My phrasing was, “If an AI winter did happen and I did not do every f*****g possible thing I could to, like, avert that, I would see myself as personally responsible both for, the RLHF direction, which I think really widened overpromise versus under-deliver, and also not going all in on this because I think this is, this is where value is going to just be, like, printed.” So. And it was really cool because I feel likeDiogo Almeida [00:34:47]: The AI winter I'm worrying about is averted. Like, AI will be useful. It'll be used for automation.Diogo Almeida [00:34:53]: It's been less than a week, and like, the numbers are already undeniableSwyx [00:34:57]: YeahDiogo Almeida [00:34:57]: That it's, like, being used for real work, and like, there's. It's, it's the Wild West. Yeah.Launch Traction, Tokens, Rate Limits, and Developer UsageSwyx [00:35:03]: Yeah. Can you sh- just if you have top of your head, what numbers are you seeing? Like, what's, what's, like, signups? Like, whatever you can share.Diogo Almeida [00:35:11]: I'm actually not super on top of everything. Like, the team is the ones who are telling me all of these things.Swyx [00:35:16]: Yeah, and I'm sure it's, like, changing every day, right?Diogo Almeida [00:35:17]: It's, it's,Swyx [00:35:18]: But likeDiogo Almeida [00:35:18]: It's kinda nutsSwyx [00:35:19]: If there's a milestone that you're like, “Well, yep, that's one thing we were hoping for. We reached it.”Diogo Almeida [00:35:23]: I will say a milestone that we've passed is tokens per day.Swyx [00:35:27]: Nice.Diogo Almeida [00:35:27]: And this is not, like, fleeting tokens per day.Swyx [00:35:32]: Yeah.Diogo Almeida [00:35:32]: This is, like, even at night, like, it's constantly training, so machines are calling it and not just people trying things out.Diogo Almeida [00:35:39]: So that is, That is so cool. A trillion tokens a day is a lot.Swyx [00:35:45]: Yeah.Diogo Almeida [00:35:45]: So surpassing that is awesome. Signups to me don't really matter. And actually, this was, like, a bit of a mistake we made, if I'm, like, totally honest. People on Twitter were calling us, like, marketing geniuses and all of that, and that was just us. We don't have a marketer. Also hiring. And we were just being our genuine, goofy, like, irreverent selves, and we were, we were just, like, offboarding people off the waitlist so hard. - Our platform team is so unbelievably cracked. I think we have more n- up nines of uptime than Anthropic while having the most Unprecedented launch ever. Like, that is kind of nuts, soSwyx [00:36:21]: YeahDiogo Almeida [00:36:21]: Like, props to them.Swyx [00:36:22]: Yeah.Diogo Almeida [00:36:23]: And the thing we didn't realize. So number one, waitlists, waitlist sign-ups don't matter for, like, a developer platform, in my opinion? I would guess that a large number of them are not even developers. So they go in, they try some queries, and a lot of people don't get it because they are not programming, right? Like, they're just like, “What? This is not a chatbot. Where's my ChatGPT 2?”Diogo Almeida [00:36:45]: Right? But if, like. I haven't exactly calculated this. My sense is that if every single human being in the world, like, just wrote a couple of queries, that would be a rounding error compared to, like, one power user's for loop that is just, like, creating value.Swyx [00:37:01]: Yeah.Diogo Almeida [00:37:01]: And the thing we are-- didn't realize with the waitlist is, like, we could just w- off-board anyone off the waitlist. It doesn't matter. The scary part is rate limits. And then once people start getting value from that, then they just want tons and tons of rate limits because this is what software is, right? Like, you spend effort upfront to specify your rote task, and then this rote task creates more value than it takes to put in. And then now that you have thatSwyx [00:37:25]: Set it and forget, yeah.Diogo Almeida [00:37:26]: Exactly, yeah. You run it in the background. You make it a dependency, to, like, other things. You can make, like, higher level stuff. And like, you just create so much value in the world. Early internet people probably did not imagine, like, the wonder of early 2000s internet, which is still not early internet. But like, it's, it's through, no offense, composabilitySwyx [00:37:47]: NoDiogo Almeida [00:37:47]: That all of the crazy stuff happens, and I just really wanted to emphasize that in our manifesto. We are going for emergence. We are going for, like, being the catalyst. We're wanting to empower people, and we are going to do whatever we can for that, be it, like, Discords in our town hall with me wearing a garbage bag or not.Swyx [00:38:05]: And podcasts and Diogo Almeida [00:38:08]: Hell yeahSwyx [00:38:09]: Getting all that.Diogo Almeida [00:38:09]: Absolutely.Swyx [00:38:09]: Like, ‘cause I want the long form, right?Diogo Almeida [00:38:11]: Yeah.Swyx [00:38:12]: It is like, yes, we'll get past the, some of the superficial things, and then we'll go deep andDiogo Almeida [00:38:15]: Hell yeahSwyx [00:38:15]: And people will really trust and understand your mission and like, the people that, will resonate that will end up joining you or, buying you. Or No, but sorry, as a, as a customer.Diogo Almeida [00:38:27]: Oh, as a customer.Swyx [00:38:28]: As a customer, as a customer.Diogo Almeida [00:38:28]: Okay, yeah. That was funny. I'm sorry.Swyx [00:38:30]: Sorry. I didn't, I didn't mean to say that. But no, any-- one version, one very flattering version of this, like, 36 million views of your launch video.Diogo Almeida [00:38:37]: Cool. Up to 38 now.Swyx [00:38:39]: Yeah, rounding error.Diogo Almeida [00:38:40]: Yeah.Swyx [00:38:40]: Navio still has got 74. Fable 5 got 57. So like, as far as, a- and I didn't, I didn't do the stats for, like, original ChatGPT, likeDiogo Almeida [00:38:48]: YepSwyx [00:38:49]: Which there was no video.Diogo Almeida [00:38:50]: Yep.Swyx [00:38:50]: So like, up there, right?Diogo Almeida [00:38:52]: Yep.Swyx [00:38:52]: Like, as far, as far as, like, if you were to launch a Neolab in 2026, I think you're, like, number one right now, which is, like, pretty crazy.Diogo Almeida [00:38:58]: Yeah. Well, I actually would rather. I do have the shirt, like, your favorites Neola-- favorite Neolab's favorite Neolab.Swyx [00:39:05]: Huh.Diogo Almeida [00:39:05]: I don't give a s**t about being a Neolab. I think being a Neolab. Actually, we have a lot of, like, swag that's being a parody of a Neolab. One of them, one of them I have is, like, Neolab with product, which actually is not a Neolab. Like, I don't care about that, really.Swyx [00:39:20]: Yeah.Diogo Almeida [00:39:20]: What I care about is being a reliable dev platform. So Swyx [00:39:23]: YesDiogo Almeida [00:39:24]: Appreciate the comparison, but likeSwyx [00:39:25]: YeahDiogo Almeida [00:39:25]: Hopefully we transcend past them and we go back into, like, a thing-- like, a revolutionary moment for developers and like, this stable thing that people can rely on and trust.Reliability, Robustness, and DeterminismSwyx [00:39:35]: Yes. To that end, I think that's one thing that really impressed me about you guys is that, yes, you do talk about reliability. I thought it was mostly about calibration, which, like, we talk about RLCD. But actually it's also about just, like, uptime and scalability and all those things, right? They're, they're all sort of the kind.Diogo Almeida [00:39:55]: And nines.Swyx [00:39:56]: And nines.Diogo Almeida [00:39:56]: It's, likeSwyx [00:39:57]: Which uptime is, in my opinion.Diogo Almeida [00:39:58]: Oh, but that's part of it. But like, there's reliability in, like, how intelligent the thing is. Like, how consistently does it do the thing that you want? And I think that, like, the big reasoning models are very smart. In my opinion, they still lack reliability. I think there's many use cases where you-- they look like they should be smart enough to automate their work. There is economic incentive to automate that work, yet still they're not reliable enough as, at an intern because they're optimized for different things. And so like, I think that there's the reliability of being able to, like, trust the outputs. And also we are. Like, there are dimensions of reliability that we are not yet at that I'm, like, so excited by.Swyx [00:40:38]: Yeah.Diogo Almeida [00:40:38]: Like, I want to automate the easy work before the hard work? Like, I think that's just a common sense thing to do. But to me, we will be sufficient. I don't know if there's such thing as sufficiently reliable, but I wanna get so good that people don't even need to try the model to know that it'll work. It's like, that's like what flow state is in programming, right? Like, I'm just, like, writing queries because I need intelligence in here. And like, when. For non-trivial branching, I can just write it in like a, like a type-safe System 1 query and then get the results out of it and it just branches accurately. Like, that would be so good. Like, that's the. That is the dream.Swyx [00:41:12]: Yeah.Diogo Almeida [00:41:12]: And that is, like, going to be, like, a long slog.Swyx [00:41:16]: Yeah. We're gonna go into your API design in a little bitDiogo Almeida [00:41:19]: OohSwyx [00:41:19]: Just to give people examples and like, maybe paths not taken, that kind of stuff.Swyx [00:41:23]: One thing up the front that I do wonder about in terms of reliability is I noticed that there's no seed. There's no, And so basically, same input, do I always get the same output?Diogo Almeida [00:41:34]: SoSwyx [00:41:36]: And if not, why not?Diogo Almeida [00:41:37]: Oh, great question. So this is actually, like, a common question we have between. So reliability is actually a catchall. Like, whenever AI can't automate something, it's due to some form of reliability. Could be, like, type safety. It could be determinism. It just could be, like, it's, it's jagged, right? So reliability is a catchall. I just think that it's also a catchall for, like, what the North Star is. Re- determinism is, like, same inputs, same outputs. I do believe that this is, like, slightly interesting for unit tests, but I believe that to be the wrong North Star. I believe robustness is what peopleDiogo Almeida [00:42:16]: I don't wanna tell people what they really want, ‘cause that would be a little arrogant of me.Diogo Almeida [00:42:19]: I believe that is, like, the more important property. You want, given similar inputs, get similar outputs. And it's kind of wild how unreliable LLMs are.Diogo Almeida [00:42:31]: Like, a way that we test this is you put, like, UUIDs in, like littleSwyx [00:42:36]: YeahDiogo Almeida [00:42:36]: I think they're called nonces In the prompt. And what you want is similar outputs from all of those, ‘cause it's truly semantically the same question, and that is the part where you really want. Th- like, that robustness is where, like, people get, like, burnt with AI making decisions. So I think that is the. A super-duper important property. We could also have determinism. That is, that is a thing that can be available. As far as I can, like, mentally model for programmers, like, it, I- it could be valuable for some use cases, so like, please educate me, in comments or view. But my. In general, it's easy. Determinism is something you can, like, trade off for better cost. Like, we are, we are constantly wanting to be on the intelligence per dollar frontier. We are doing, like, absolutely disgusting things to be there. Like, this is,Diogo Almeida [00:43:32]: I shouldn't say this, but no one's here to stop me.Swyx [00:43:37]: If you s- you sign off on your own PR.Diogo Almeida [00:43:40]: That is not how it works at this company. I believe for this week, my chief of staff, Kay, is the most powerful person in tech.Swyx [00:43:49]: Yeah. And shout-out to Kay for organizing this.Diogo Almeida [00:43:50]: Holy shSwyx [00:43:51]: Yeah.Diogo Almeida [00:43:51]: Holy s**t. She is so f*****g competent and powerful. She's incredible.Diogo Almeida [00:43:58]: She sucks. Don't poach her. But so I try to be a bit more filtered, but like, people are telling me, “Don't call it a Frankenstein's monster of models,” but because that has, like, negative implications. I think Frankenstein's monster was, like, the good guy in this whole. It was innocent, right? I didn't read it. Okay.Diogo Almeida [00:44:18]: I'll, I'll confess. Okay. That. Well, one facial expression, ISwyx [00:44:21]: This is aDiogo Almeida [00:44:21]: My cards on the tableSwyx [00:44:21]: Decent Jacob Elordi movie if you wanna seeDiogo Almeida [00:44:24]: ISwyx [00:44:25]: The adaptation. Anyway.Diogo Almeida [00:44:26]: The. You have no idea how little time I have right now.Swyx [00:44:28]: Yeah.Diogo Almeida [00:44:29]: My priorities are sleep?Swyx [00:44:31]: Developers.Diogo Almeida [00:44:32]: Developers, yes. Developers. But yes. It. We do, like, absolutely disgusting things to be on the Pareto curve of intelligence per dollar, and we are going to keep doing that.Swyx [00:44:47]: Yeah.Diogo Almeida [00:44:47]: We're gonna be doing crazy-ass stuff, and I think people really need to think outside of the box. Like, part of the reason we're surprising is, like, people Are thought inside the box, and we continue to do that. As of right now, we are obviously the best at this, and we want to continue being the best at that whole thing.Swyx [00:45:05]: Yeah.Diogo Almeida [00:45:05]: So Wait, where did, where did we tangent from?Swyx [00:45:07]: No. SoDiogo Almeida [00:45:08]: YeahSwyx [00:45:08]: I asked you about, will you have seeds and determinism?Diogo Almeida [00:45:11]: Oh, yes. SoSwyx [00:45:11]: And then you basically defined reliability and likeDiogo Almeida [00:45:14]: And robustnessSwyx [00:45:15]: How you see it. Yes.Diogo Almeida [00:45:16]: But like, determina- likeSwyx [00:45:17]: I have a robustness example that's, that's, real quick I can show you.Diogo Almeida [00:45:19]: I would love that. I will just say one thing.Swyx [00:45:21]: Yeah.Diogo Almeida [00:45:21]: We can make a deterministic model.Swyx [00:45:22]: Exactly.Diogo Almeida [00:45:23]: Like, we're hap- if people can convince us that is a valuable thing to doSwyx [00:45:27]: YeahDiogo Almeida [00:45:27]: And we don't have a gigantic GPU shortageSwyx [00:45:29]: YeahDiogo Almeida [00:45:29]: We can happily make all of these models. We live to please. And rev- and revolt, revolute,Swyx [00:45:38]: You will throw over everything, except you'll do it in a nice way.Diogo Almeida [00:45:41]: Yeah.Swyx [00:45:41]: And findDiogo Almeida [00:45:42]: So like, determinism could be on the cards.Swyx [00:45:44]: Yeah.Diogo Almeida [00:45:45]: It just gets you less intelligence per dollar.Swyx [00:45:46]: Yeah. Well, just having seen the trajectory of OpenAI and Anthropic, you will. Just trust me now that you will be peer pressured into doing it. So like, just people will want it even if they. If you tell them they don't need it. They'll still want it. So like, yeah, that's the TL;DR of that.Diogo Almeida [00:46:01]: Okay.Swyx [00:46:02]: Yeah.Diogo Almeida [00:46:02]: I will love to. Maybe one day we will see how that happens.Swyx [00:46:07]: Yeah.Diogo Almeida [00:46:07]: I've been told I'm, They say that part of our brand is being unshakeableSwyx [00:46:13]: HuhDiogo Almeida [00:46:13]: And they say that's just the nice way of saying stubborn.Swyx [00:46:15]:

Podcasting 2.0 Episode 271 - "Foot Terminal" Adam & Dave have their SCBA's on and go deep into index refactoring and ad loads! ShowNotes ------------------------------------------------------------------------------------------------------------------------------------- 00 -

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