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A $20 billion AI deal while you were away?
We make our big Linux predictions for 2026, but first, we score how we did for 2025.Sponsored By:Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. 1Password Extended Access Management: 1Password Extended Access Management is a device trust solution for companies with Okta, and they ensure that if a device isn't trusted and secure, it can't log into your cloud apps. CrowdHealth: Discover a Better Way to Pay for Healthcare with Crowdfunded Memberships. Join CrowdHealth to get started today for $99 for your first three months using UNPLUGGED.Unraid: A powerful, easy operating system for servers and storage. Maximize your hardware with unmatched flexibility. Support LINUX UnpluggedLinks:
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Mike Bakon to explore the fascinating intersection of hardware hacking, blockchain technology, and decentralized systems. Their conversation spans from Mike's childhood fascination with taking apart electronics in 1980s Poland to his current work with ESP32 microcontrollers, LoRa mesh networks, and Cardano blockchain development. They discuss the technical differences between UTXO and account-based blockchains, the challenges of true decentralization versus hybrid systems, and how AI tools are changing the development landscape. Mike shares his vision for incentivizing mesh networks through blockchain technology and explains why he believes mass adoption of decentralized systems will come through abstraction rather than technical education. The discussion also touches on the potential for creating new internet infrastructure using ad hoc mesh networks and the importance of maintaining truly decentralized, permissionless systems in an increasingly surveilled world. You can find Mike in Twitter as @anothervariable.Check out this GPT we trained on the conversationTimestamps00:00 Introduction to Hardware and Early Experiences02:59 The Evolution of AI in Hardware Development05:56 Decentralization and Blockchain Technology09:02 Understanding UTXO vs Account-Based Blockchains11:59 Smart Contracts and Their Functionality14:58 The Importance of Decentralization in Blockchain17:59 The Process of Data Verification in Blockchain20:48 The Future of Blockchain and Its Applications34:38 Decentralization and Trustless Systems37:42 Mainstream Adoption of Blockchain39:58 The Role of Currency in Blockchain43:27 Interoperability vs Bridging in Blockchain47:27 Exploring Mesh Networks and LoRa Technology01:00:25 The Future of AI and DecentralizationKey Insights1. Hardware curiosity drives innovation from childhood - Mike's journey into hardware began as a child in 1980s Poland, where he would disassemble toys like battery-powered cars to understand how they worked. This natural curiosity about taking things apart and understanding their inner workings laid the foundation for his later expertise in microcontrollers like the ESP32 and his deep understanding of both hardware and software integration.2. AI as a research companion, not a replacement for coding - Mike uses AI and LLMs primarily as research tools and coding companions rather than letting them write entire applications. He finds them invaluable for getting quick answers to coding problems, analyzing Git repositories, and avoiding the need to search through Stack Overflow, but maintains anxiety when AI writes whole functions, preferring to understand and write his own code.3. Blockchain decentralization requires trustless consensus verification - The fundamental difference between blockchain databases and traditional databases lies in the consensus process that data must go through before being recorded. Unlike centralized systems where one entity controls data validation, blockchains require hundreds of nodes to verify each block through trustless consensus mechanisms, ensuring data integrity without relying on any single authority.4. UTXO vs account-based blockchains have fundamentally different architectures - Cardano uses an extended UTXO model (like Bitcoin but with smart contracts) where transactions consume existing UTXOs and create new ones, keeping the ledger lean. Ethereum uses account-based ledgers that store persistent state, leading to much larger data requirements over time and making it increasingly difficult for individuals to sync and maintain full nodes independently.5. True interoperability differs fundamentally from bridging - Real blockchain interoperability means being able to send assets directly between different blockchains (like sending ADA to a Bitcoin wallet) without intermediaries. This is possible between UTXO-based chains like Cardano and Bitcoin. Bridges, in contrast, require centralized entities to listen for transactions on one chain and trigger corresponding actions on another, introducing centralization risks.6. Mesh networks need economic incentives for sustainable infrastructure - While technologies like LoRa and Meshtastic enable impressive decentralized communication networks, the challenge lies in incentivizing people to maintain the hardware infrastructure. Mike sees potential in combining blockchain-based rewards (like earning ADA for running mesh network nodes) with existing decentralized communication protocols to create self-sustaining networks.7. Mass adoption comes through abstraction, not education - Rather than trying to educate everyone about blockchain technology, mass adoption will happen when developers can build applications on decentralized infrastructure that users interact with seamlessly, without needing to understand the underlying blockchain mechanics. Users should be able to benefit from decentralization through well-designed interfaces that abstract away the complexity of wallets, addresses, and consensus mechanisms.
Crazy Wisdom: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- In this episode of the Crazy Wisdom Podcast, host Stewart Alsop speaks with Aaron Borger, founder and CEO of Orbital Robotics, about the emerging world of space robotics and satellite capture technology. The conversation covers a fascinating range of topics including Borger's early experience launching AI-controlled robotic arms to space as a student, his work at Blue Origin developing lunar lander software, and how his company is developing robots that can capture other spacecraft for refueling, repair, and debris removal. They discuss the technical challenges of operating in space - from radiation hardening electronics to dealing with tumbling satellites - as well as the broader implications for the space economy, from preventing the Kessler effect to building space-based recycling facilities and mining lunar ice for rocket fuel. You can find more about Aaron Borger's work at Orbital Robots and follow him on LinkedIn for updates on upcoming missions and demos. Check out this GPT we trained on the conversationTimestamps00:00 Introduction to orbital robotics, satellite capture, and why sensing and perception matter in space 05:00 The Kessler Effect, cascading collisions, and why space debris is an economic problem before it is an existential one 10:00 From debris removal to orbital recycling and the idea of turning junk into infrastructure 15:00 Long-term vision of space factories, lunar ice, and refueling satellites to bootstrap a lunar economy 20:00 Satellite upgrading, servicing live spacecraft, and expanding today's narrow space economy 25:00 Costs of collision avoidance, ISS maneuvers, and making debris capture economically viable 30:00 Early experiments with AI-controlled robotic arms, suborbital launches, and reinforcement learning in microgravity 35:00 Why deterministic AI and provable safety matter more than LLM hype for spacecraft control 40:00 Radiation, single event upsets, and designing space-safe AI systems with bounded behavior 45:00 AI, physics-based world models, and autonomy as the key to scaling space operations 50:00 Manufacturing constraints, space supply chains, and lessons from rocket engine software 55:00 The future of space startups, geopolitics, deterrence, and keeping space usable for humanityKey Insights1. Space Debris Removal as a Growing Economic Opportunity: Aaron Borger explains that orbital debris is becoming a critical problem with approximately 3,000-4,000 defunct satellites among the 15,000 total satellites in orbit. The company is developing robotic arms and AI-controlled spacecraft to capture other satellites for refueling, repair, debris removal, and even space station assembly. The economic case is compelling - it costs about $1 million for the ISS to maneuver around debris, so if their spacecraft can capture and remove multiple pieces of debris for less than that cost per piece, it becomes financially viable while addressing the growing space junk problem.2. Revolutionary AI Safety Methods Enable Space Robotics: Traditional NASA engineers have been reluctant to use AI for spacecraft control due to safety concerns, but Orbital Robotics has developed breakthrough methods combining reinforcement learning with traditional control systems that can mathematically prove the AI will behave safely. Their approach uses physics-based world models rather than pure data-driven learning, ensuring deterministic behavior and bounded operations. This represents a significant advancement over previous AI approaches that couldn't guarantee safe operation in the high-stakes environment of space.3. Vision for Space-Based Manufacturing and Resource Utilization: The long-term vision extends beyond debris removal to creating orbital recycling facilities that can break down captured satellites and rebuild them into new spacecraft using existing materials in orbit. Additionally, the company plans to harvest propellant from lunar ice, splitting it into hydrogen and oxygen for rocket fuel, which could kickstart a lunar economy by providing economic incentives for moon-based operations while supporting the growing satellite constellation infrastructure.4. Unique Space Technology Development Through Student Programs: Borger and his co-founder gained unprecedented experience by launching six AI-controlled robotic arms to space through NASA's student rocket programs while still undergraduates. These missions involved throwing and catching objects in microgravity using deep reinforcement learning trained in simulation and tested on Earth. This hands-on space experience is extremely rare and gave them practical knowledge that informed their current commercial venture.5. Hardware Challenges Require Innovative Engineering Solutions: Space presents unique technical challenges including radiation-induced single event upsets that can reset processors for up to 10 seconds, requiring "passive safe" trajectories that won't cause collisions even during system resets. Unlike traditional space companies that spend $100,000 on radiation-hardened processors, Orbital Robotics uses automotive-grade components made radiation-tolerant through smart software and electrical design, enabling cost-effective operations while maintaining safety.6. Space Manufacturing Supply Chain Constraints: The space industry faces significant manufacturing bottlenecks with 24-week lead times for space-grade components and limited suppliers serving multiple companies simultaneously. This creates challenges for scaling production - Orbital Robotics needs to manufacture 30 robotic arms per year within a few years. They've partnered with manufacturers who previously worked on Blue Origin's rocket engines to address these supply chain limitations and achieve the scale necessary for their ambitious deployment timeline.7. Emerging Space Economy Beyond Communications: While current commercial space activities focus primarily on communications satellites (with SpaceX Starlink holding 60% market share) and Earth observation, new sectors are emerging including AI data centers in space and orbital manufacturing. The convergence of AI, robotics, and space technology is enabling more sophisticated autonomous operations, from predictive maintenance of rocket engines using sensor data to complex orbital maneuvering and satellite servicing that was previously impossible with traditional control methods.
I denne episode af Scrum med mere dykker vi ned i det emne, som alle taler om: AI. Men hvad er det egentlig for en størrelse? Vi tager fat på de store sprogmodeller (LLM’er) og forsøger at give et nøgternt billede af, hvad de kan – og i særdeleshed hvad de ikke kan. Vi gennemgår […] Source
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop speaks with Aaron Borger, founder and CEO of Orbital Robotics, about the emerging world of space robotics and satellite capture technology. The conversation covers a fascinating range of topics including Borger's early experience launching AI-controlled robotic arms to space as a student, his work at Blue Origin developing lunar lander software, and how his company is developing robots that can capture other spacecraft for refueling, repair, and debris removal. They discuss the technical challenges of operating in space - from radiation hardening electronics to dealing with tumbling satellites - as well as the broader implications for the space economy, from preventing the Kessler effect to building space-based recycling facilities and mining lunar ice for rocket fuel. You can find more about Aaron Borger's work at Orbital Robots and follow him on LinkedIn for updates on upcoming missions and demos. Check out this GPT we trained on the conversationTimestamps00:00 Introduction to orbital robotics, satellite capture, and why sensing and perception matter in space 05:00 The Kessler Effect, cascading collisions, and why space debris is an economic problem before it is an existential one 10:00 From debris removal to orbital recycling and the idea of turning junk into infrastructure 15:00 Long-term vision of space factories, lunar ice, and refueling satellites to bootstrap a lunar economy 20:00 Satellite upgrading, servicing live spacecraft, and expanding today's narrow space economy 25:00 Costs of collision avoidance, ISS maneuvers, and making debris capture economically viable 30:00 Early experiments with AI-controlled robotic arms, suborbital launches, and reinforcement learning in microgravity 35:00 Why deterministic AI and provable safety matter more than LLM hype for spacecraft control 40:00 Radiation, single event upsets, and designing space-safe AI systems with bounded behavior 45:00 AI, physics-based world models, and autonomy as the key to scaling space operations 50:00 Manufacturing constraints, space supply chains, and lessons from rocket engine software 55:00 The future of space startups, geopolitics, deterrence, and keeping space usable for humanityKey Insights1. Space Debris Removal as a Growing Economic Opportunity: Aaron Borger explains that orbital debris is becoming a critical problem with approximately 3,000-4,000 defunct satellites among the 15,000 total satellites in orbit. The company is developing robotic arms and AI-controlled spacecraft to capture other satellites for refueling, repair, debris removal, and even space station assembly. The economic case is compelling - it costs about $1 million for the ISS to maneuver around debris, so if their spacecraft can capture and remove multiple pieces of debris for less than that cost per piece, it becomes financially viable while addressing the growing space junk problem.2. Revolutionary AI Safety Methods Enable Space Robotics: Traditional NASA engineers have been reluctant to use AI for spacecraft control due to safety concerns, but Orbital Robotics has developed breakthrough methods combining reinforcement learning with traditional control systems that can mathematically prove the AI will behave safely. Their approach uses physics-based world models rather than pure data-driven learning, ensuring deterministic behavior and bounded operations. This represents a significant advancement over previous AI approaches that couldn't guarantee safe operation in the high-stakes environment of space.3. Vision for Space-Based Manufacturing and Resource Utilization: The long-term vision extends beyond debris removal to creating orbital recycling facilities that can break down captured satellites and rebuild them into new spacecraft using existing materials in orbit. Additionally, the company plans to harvest propellant from lunar ice, splitting it into hydrogen and oxygen for rocket fuel, which could kickstart a lunar economy by providing economic incentives for moon-based operations while supporting the growing satellite constellation infrastructure.4. Unique Space Technology Development Through Student Programs: Borger and his co-founder gained unprecedented experience by launching six AI-controlled robotic arms to space through NASA's student rocket programs while still undergraduates. These missions involved throwing and catching objects in microgravity using deep reinforcement learning trained in simulation and tested on Earth. This hands-on space experience is extremely rare and gave them practical knowledge that informed their current commercial venture.5. Hardware Challenges Require Innovative Engineering Solutions: Space presents unique technical challenges including radiation-induced single event upsets that can reset processors for up to 10 seconds, requiring "passive safe" trajectories that won't cause collisions even during system resets. Unlike traditional space companies that spend $100,000 on radiation-hardened processors, Orbital Robotics uses automotive-grade components made radiation-tolerant through smart software and electrical design, enabling cost-effective operations while maintaining safety.6. Space Manufacturing Supply Chain Constraints: The space industry faces significant manufacturing bottlenecks with 24-week lead times for space-grade components and limited suppliers serving multiple companies simultaneously. This creates challenges for scaling production - Orbital Robotics needs to manufacture 30 robotic arms per year within a few years. They've partnered with manufacturers who previously worked on Blue Origin's rocket engines to address these supply chain limitations and achieve the scale necessary for their ambitious deployment timeline.7. Emerging Space Economy Beyond Communications: While current commercial space activities focus primarily on communications satellites (with SpaceX Starlink holding 60% market share) and Earth observation, new sectors are emerging including AI data centers in space and orbital manufacturing. The convergence of AI, robotics, and space technology is enabling more sophisticated autonomous operations, from predictive maintenance of rocket engines using sensor data to complex orbital maneuvering and satellite servicing that was previously impossible with traditional control methods.
Note: Steve and Gene's talk on Vibe Coding and the post IDE world was one of the top talks of AIE CODE: https://www.youtube.com/watch?v=7Dtu2bilcFs&t=1019s&pp=0gcJCU0KAYcqIYzv From building legendary platforms at Google and Amazon to authoring one of the most influential essays on AI-powered development (Revenge of the Junior Developer, quoted by Dario Amodei himself), Steve Yegge has spent decades at the frontier of software engineering—and now he's leading the charge into what he calls the "factory farming" era of code. After stints at SourceGraph and building Beads (a purely vibe-coded issue tracker with tens of thousands of users), Steve co-authored The Vibe Coding Book and is now building VC (VibeCoder), an agent orchestration dashboard designed to move developers from writing code to managing fleets of AI agents that coordinate, parallelize, and ship features while you sleep. We sat down with Steve at AI Engineer Summit to dig into why Claude Code, Cursor, and the entire 2024 stack are already obsolete, what it actually takes to trust an agent after 2,000 hours of practice (hint: they will delete your production database if you anthropomorphize them), why the real skill is no longer writing code but orchestrating agents like a NASCAR pit crew, how merging has become the new wall that every 10x-productive team is hitting (and why one company's solution is literally "one engineer per repo"), the rise of multi-agent workflows where agents reserve files, message each other via MCP, and coordinate like a little village, why Steve believes if you're still using an IDE to write code by January 1st, you're a bad engineer, how the 12–15 year experience bracket is the most resistant demographic (and why their identity is tied to obsolete workflows), the hidden chaos inside OpenAI, Anthropic, and Google as they scale at breakneck speed, why rewriting from scratch is now faster than refactoring for a growing class of codebases, and his 2025 prediction: we're moving from subsistence agriculture to John Deere-scale factory farming of code, and the Luddite backlash is only just beginning. We discuss: Why Claude Code, Cursor, and agentic coding tools are already last year's tech—and what comes next: agent orchestration dashboards where you manage fleets, not write lines The 2,000-hour rule: why it takes a full year of daily use before you can predict what an LLM will do, and why trust = predictability, not capability Steve's hot take: if you're still using an IDE to develop code by January 1st, 2025, you're a bad engineer—because the abstraction layer has moved from models to full-stack agents The demographic most resistant to vibe coding: 12–15 years of experience, senior engineers whose identity is tied to the way they work today, and why they're about to become the interns Why anthropomorphizing LLMs is the biggest mistake: the "hot hand" fallacy, agent amnesia, and how Steve's agent once locked him out of prod by changing his password to "fix" a problem Should kids learn to code? Steve's take: learn to vibe code—understand functions, classes, architecture, and capabilities in a language-neutral way, but skip the syntax The 2025 vision: "factory farming of code" where orchestrators run Cloud Code, scrub output, plan-implement-review-test in loops, and unlock programming for non-programmers at scale — Steve Yegge X: https://x.com/steve_yegge Substack (Stevie's Tech Talks): https://steve-yegge.medium.com/ GitHub (VC / VibeCoder): https://github.com/yegge-labs Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction: Steve Yegge on Vibe Coding and AI Engineering 00:00:59 The Backlash: Who Resists Vibe Coding and Why 00:04:26 The 2000 Hour Rule: Building Trust with AI Coding Tools 00:03:31 The January 1st Deadline: IDEs Are Becoming Obsolete 00:02:55 10X Productivity at OpenAI: The Performance Review Problem 00:07:49 The Hot Hand Fallacy: When AI Agents Betray Your Trust 00:11:12 Claude Code Isn't It: The Need for Agent Orchestration 00:15:20 The Orchestrator Revolution: From Cloud Code to Agent Villages 00:18:46 The Merge Wall: The Biggest Unsolved Problem in AI Coding 00:26:33 Never Rewrite Your Code - Until Now: Joel Spolsky Was Wrong 00:22:43 Factory Farming Code: The John Deere Era of Software 00:29:27 Google's Gemini Turnaround and the AI Lab Chaos 00:33:20 Should Your Kids Learn to Code? The New Answer 00:34:59 Code MCP and the Gossip Rate: Latest Vibe Coding Discoveries
Podcast: Within Reason with Hank GreenPodcast: Within Reason with VsaucePodcast: Acquired: Microsoft Volume IFavorite Cup o' Go episodes of 2025May 17, Episode 110: Thanks, Ian.
How Shopify Is Building The Future of AI Commerce with Andrew McNamaraShopify's Director of Applied ML, Andrew McNamara, reveals how the new Sidekick Pulse and SimGym features are revolutionizing e-commerce for merchants of all sizes. With 15 years of experience building AI assistants—dating back to pre-Siri days—Andrew breaks down how Shopify is using "LLM as a judge" to ensure quality and why "vibe entrepreneurship" is the future of business.Andrew explains how Sidekick has evolved from a simple chatbot into a proactive "AI Co-founder" that can democratize data for small business owners. He shares behind-the-scenes details on Sidekick Pulse, which performs deep research to surface actionable insights (like finding shipping errors that cost sales), and Simgym, a powerful simulator that uses AI shoppers to A/B test store changes before they go live.We also dive into the technical side of how Shopify evaluates these models using statistical rigor and why the ability for merchants to build admin apps with a single prompt is a game-changer for productivity.---Topics Covered- The 15-year evolution of AI assistants from rule-based systems to LLMs- How Sidekick Pulse proactively finds and fixes business-critical errors- Simgym: Using AI shoppers to simulate A/B tests without risking live traffic- The "LLM as a Judge" framework Shopify uses for product quality control- "Vibe Entrepreneurship" and reducing technical barriers for founders- Building custom Admin Apps in seconds using natural language prompts- Real-world examples from Andrew's own maple syrup store- The difference between general chatbots (Copilot) and specialized agents (Sidekick)- How "App Gen" allows merchants to create custom workflows instantlyEpisode Timestamps00:03 - Introduction to Andrew McNamara and his 15-year history with AI01:01 - Comparing early AI assistants (BlackBerry/Samsung) to modern LLMs06:45 - How Sidekick democratizes data analytics for small merchants11:25 - Deep Dive: Sidekick Pulse and proactive business research15:43 - Using "LLM as a Judge" to replace human evaluation at scale18:41 - Generating custom Admin Apps with a single prompt ("App Gen")21:58 - Andrew's personal experience running a Shopify store25:31 - The concept of "Vibe Entrepreneurship" as a North Star26:30 - Using AI to edit online store themes and layouts in real-time37:39 - Simgym: Simulating buyer behavior to predict experiment results42:06 - Why simulation is critical for both small and large enterprise merchants48:04 - The culture of technical depth and passion at Shopify51:34 - Why Andrew has dedicated his entire career to building assistants---## About Andrew McNamaraAndrew McNamara is the Director of Applied Machine Learning at Shopify, where he leads the development of Sidekick and other intelligent merchant features. Previously the Director of the Montreal Research Lab at Microsoft and a key contributor to Bing Chat (Copilot), Andrew has over 15 years of experience building and deploying AI assistants at scale.Shopify is the leading global commerce company, providing trusted tools to start, grow, market, and manage a retail business of any size. It powers millions of businesses in more than 175 countries and offers a unified platform for physical and digital commerce.Resources Mentioned- Shopify Sidekick (AI Commerce Assistant)- Sidekick Pulse (Proactive Research Agent)- Simgym (AI Shopper Simulator)- Microsoft Copilot & Bing Chat- "LLM as a Judge" Evaluation Framework---Partner Links- Book Enterprise Training — https://www.upscaile.com/- Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube
Ho Ho Ho, Alex here! (a real human writing these words, this needs to be said in 2025) Merry Christmas (to those who celebrate) and welcome to the very special yearly ThursdAI recap! This was an intense year in the world of AI, and after 51 weekly episodes (this is episode 52!) we have the ultimate record of all the major and most important AI releases of this year! So instead of bringing you a weekly update (it's been a slow week so far, most AI labs are taking a well deserved break, the Cchinese AI labs haven't yet surprised anyone), I'm dropping a comprehensive yearly AI review! Quarter by quarter, month by month, both in written form and as a pod/video! Why do this? Who even needs this? Isn't most of it obsolete? I have asked myself this exact question while prepping for the show (it was quite a lot of prep, even with Opus's help). I eventually landed on, hey, if nothing else, this will serve as a record of the insane week of AI progress we all witnessed. Can you imagine that the term Vibe Coding is less than 1 year old? That Claude Code was released at the start of THIS year? We get hedonicly adapt to new AI goodies so quick, and I figured this will serve as a point in time check, we can get back to and feel the acceleration! With that, let's dive in - P.S. the content below is mostly authored by my co-author for this, Opus 4.5 high, which at the end of 2025 I find the best creative writer with the best long context coherence that can imitate my voice and tone (hey, I'm also on a break!
In this episode, Dr. Wayne Pernell sits down with Dr. Subhan Ali, Silicon Valley–based co-founder of Gekit, a next-generation data + AI infrastructure company. Subhan shares his unconventional journey from structural engineering into data science, product management, and ultimately entrepreneurship. The conversation explores: • How data infrastructure underpins all modern AI • Why context is the secret weapon of LLM performance • How to make bold, non-linear career transitions • The mindset required to leave “safe paths” to create something new • The importance of conviction, constant learning, and self-belief in leadership
Stop making million-dollar decisions alone. Hampton gives you a personal board of eight vetted founders in your city who meet monthly to tackle your hardest problems. Find your group: https://joinhampton.com/What makes a founder truly successful? It's not blind risk-taking or pure hustle. After two years of interviews and supporting research, we break down the five core personality traits that show up again and again in top-performing founders – from billion-dollar exits to early-stage wins. If you're building a company, understanding these traits might just be your cheat code.Here's what we talk about:Why openness and curiosity is the #1 trait in founders (with research to back it up)How a need for achievement often comes from past pain – and how to harness itThe powerful drive for agency and autonomy, and why it often makes founders unemployableWhy emotional regulation might be the most underrated skill in entrepreneurshipWhy successful founders don't love risk – they just know how to manage uncertaintyThe science behind personality types and founder performanceWhen focus becomes the essential balance to curiosityHow therapy, journaling, and self-awareness are now founder-edge toolsThe myth of the stoic leader – and what really works insteadCool Links:Hampton https://www.joinhampton.com/Lower Street https://www.lowerstreet.co/Sponsors:Join 700+ founders hiring A-players in Latin America at hirewithnear.com/moneywiseAchieve your dream body with dailybodycoach.com/moneywiseRank higher in AI tools and LLM results with Mentions.soChapters:(0:46) How Curiosity Drives Founder Success(2:13) Turning Achievement into a Competitive Edge(4:08) Autonomy: The Fuel Behind Entrepreneurial Drive(5:39) Building Emotional Resilience for the Long Haul(6:53) Managing Uncertainty – Not Chasing Reckless Risks(8:17) Grit: The Unseen Force Behind Every Win(13:55) What Happens After the Big Exit?This podcast is a ridiculous concept: high-net-worth people reveal their personal finances. Inspired by real conversations happening in the Hampton community.Your Host: Jackie LamportNot really the host, but the producer.Wrote this sentence.
The adaptation of A.I. has just begun heading into 2026 according to David Nelson, as more companies learn to use A.I. as part of their daily business and adapt their models to take advantage of cost savings, according to David Nelson. He thinks that Salesforce (CRM) will be able to take advantage of companies looking to expand their use of A.I. He also thinks that Alphabet's (GOOGL) Gemini has surpassed ChatGPT and that competition is continuing to heat up in the LLM space.======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
The world of prehospital medicine is constantly evolving, driven by new research, technological advancements, and a shared commitment to improving patient care and provider well-being. As EMS professionals, staying informed about these developments goes beyond a professional obligation; it is an opportunity to improve our practice, champion our profession, and ultimately make a greater impact on saving lives. In this article, we will explore some of the latest research findings that are reshaping our field, from workplace culture to cutting-edge technology. The Culture of Care: Supporting EMS Providers Our work is demanding, both physically and emotionally, and the culture within our agencies plays a critical role in our well-being. A recent systematic review in the International Journal of Environmental Research and Public Health revealed that many EMS providers avoid using organizational mental health services due to stigma and a perception that these programs lack genuine care. The study emphasizes the need for person-centered support and a cultural shift that normalizes seeking help as a sign of strength (Johnston et al., 2025). This cultural component also impacts retention. Another study in the same journal found that agencies with collaborative, team-oriented "clan" cultures had significantly lower turnover rates compared to those with rigid or chaotic structures. For leaders in EMS, fostering a supportive environment is not just about morale. It is a strategic imperative for retaining skilled clinicians (Kamholz et al., 2025). Professional Recognition: Breaking Barriers Across the globe, paramedics are striving for recognition as integrated healthcare professionals. A qualitative study in BMC Health Services Research identified common barriers, including outdated legislation, inconsistent regulation, and insufficient funding. While the pandemic temporarily highlighted our capabilities, the momentum has waned. The study calls for targeted policy reforms and investments in education and leadership to solidify our role in the broader healthcare system (Feerick et al., 2025). Physical Demands and Injury Prevention The physical toll of our work is undeniable. A scoping review in Applied Ergonomics confirmed that musculoskeletal injuries, particularly to the back, are rampant in EMS. Tasks like handling stretchers and patient extractions are among the most strenuous. The review also highlighted fitness disparities, with male paramedics generally showing more strength but less flexibility than their female counterparts. These findings underscore the need for targeted injury prevention programs and realistic physical standards to keep us safe throughout our careers (Marsh et al., 2025). Advancements in Cardiac Arrest Care When it comes to cardiac arrest, every second counts. A study in Resuscitation reinforced the value of bystander CPR, showing that dispatcher-assisted CPR significantly improves outcomes for untrained bystanders. For those with prior CPR training, acting independently yielded even better results. This highlights the importance of public CPR education alongside dispatcher support (Tagami et al., 2025). On the scene, our interventions matter immensely. Research in The Journal of Emergency Medicine found that for traumatic cardiac arrest patients, aggressive interventions like prehospital thoracostomy can be lifesaving (McWilliam et al., 2025). Meanwhile, a study in Critical Care Medicine revealed that extracorporeal CPR (ECPR) significantly improves outcomes for patients with refractory ventricular fibrillation, emphasizing the need for early transport to specialized centers. The Role of Technology in EMS Technology is poised to revolutionize EMS, from dispatch to diagnosis. A study in The American Journal of Emergency Medicine demonstrated that large language models (LLMs) like ChatGPT could prioritize ambulance requests with remarkable accuracy, aligning with expert paramedic decisions over 76 percent of the time. This proof of concept suggests that AI could one day enhance resource allocation in dispatch centers (Shekhar et al., 2025). On the diagnostic front, machine learning is opening new possibilities. For example, a study in Bioengineering showed that analyzing photoplethysmography waveforms could estimate blood loss in trauma patients, offering a non-invasive way to guide resuscitation (Gonzalez et al., 2025). Similarly, research in Medical Engineering & Physics explored using multidimensional data to differentiate ischemic from hemorrhagic strokes in the field, potentially enabling more targeted prehospital care (Alshehri et al., 2025). Addressing Disparities in Care Equity in EMS is a cornerstone of our profession, yet recent studies highlight troubling disparities. Research in JAMA Network Open found that ambulance offload times were significantly longer in communities with higher proportions of Black residents (Zhou et al., 2025). Another study in JAMA Surgery revealed that Black and Asian trauma patients were less likely to receive helicopter transport compared to White patients. These findings are a call to action for all of us to examine our systems and biases to ensure equitable care for every patient (Mpody et al., 2025). Looking Ahead The research discussed here represents just a fraction of the advancements shaping EMS today. From improving workplace culture and injury prevention to leveraging AI and addressing systemic inequities, these findings have real-world implications for our protocols, training, and advocacy efforts. As EMS professionals, we have a responsibility to stay informed and apply these insights to our practice. For a deeper dive into these topics and more, I invite you to listen to the podcast, EMS Research with Professor Bram latest episode, https://youtu.be/rt_1AFzSLIk "Research Highlights and Innovations Shaping Our Field.” References Alshehri, A., Panerai, R. B., Lam, M. Y., Llwyd, O., Robinson, T. G., & Minhas, J. S. (2025). Can we identify stroke sub-type without imaging? A multidimensional analysis. Medical Engineering & Physics. https://doi.org/10.1016/j.medengphy.2025.104364 Feerick, F., Coughlan, E., Knox, S., Murphy, A., Grady, I. O., & Deasy, C. (2025). Barriers to paramedic professionalisation: A qualitative enquiry across the UK, Canada, Australia, USA and the Republic of Ireland. BMC Health Services Research, 25(1), 993. https://doi.org/10.1186/s12913-025-10993-7 Gonzalez, J. M., Holland, L., Hernandez Torres, S. I., Arrington, J. G., Rodgers, T. M., & Snider, E. J. (2025). Enhancing trauma care: Machine learning-based photoplethysmography analysis for estimating blood volume during hemorrhage and resuscitation. Bioengineering, 12(8), 833. https://doi.org/10.3390/bioengineering12080833 Johnston, S., Waite, P., Laing, J., Rashid, L., Wilkins, A., Hooper, C., Hindhaugh, E., & Wild, J. (2025). Why do emergency medical service employees (not) seek organizational help for mental health support?: A systematic review. International Journal of Environmental Research and Public Health, 22(4), 629. https://doi.org/10.3390/ijerph22040629 Kamholz, J. C., Gage, C. B., van den Bergh, S. L., Logan, L. T., Powell, J. R., & Panchal, A. R. (2025). Association between organizational culture and emergency medical service clinician turnover. International Journal of Environmental Research and Public Health, 22(5), 756. https://doi.org/10.3390/ijerph22050756 Marsh, E., Orr, R., Canetti, E. F., & Schram, B. (2025). Profiling paramedic job tasks, injuries, and physical fitness: A scoping review. Applied Ergonomics, 125, 104459. https://doi.org/10.1016/j.apergo.2025.104459 McWilliam, S. E., Bach, J. P., Wilson, K. M., Bradford, J. M., Kempema, J., DuBose, J. J., ... & Brown, C. V. (2025). Should anything else be done besides prehospital CPR? The role of CPR and prehospital interventions after traumatic cardiac arrest. The Journal of Emergency Medicine. https://doi.org/10.1016/j.jemermed.2025.02.010 Mpody, C., Rudolph, M. I., Bastien, A., Karaye, I. M., Straker, T., Borngaesser, F., ... & Nafiu, O. O. (2025). Racial and ethnic disparities in use of helicopter transport after severe trauma in the US. JAMA Surgery, 160(3), 313–321. https://doi.org/10.1001/jamasurg.2024.5678 Shekhar, A. C., Kimbrell, J., Saharan, A., Stebel, J., Ashley, E., & Abbott, E. E. (2025). Use of a large language model (LLM) for ambulance dispatch and triage. The American Journal of Emergency Medicine, 89, 27–29. https://doi.org/10.1016/j.ajem.2025.05.004 Tagami, T., Takahashi, H., Suzuki, K., Kohri, M., Tabata, R., Hagiwara, S., ... & Ogawa, S. (2025). The impact of dispatcher-assisted CPR and prior bystander CPR training on neurologic outcomes in out-of-hospital cardiac arrest: A multicenter study. Resuscitation, 110617. https://doi.org/10.1016/j.resuscitation.2025.110617 Zhou, T., Wang, Y., Zhang, B., & Li, J. (2025). Racial and socioeconomic disparities in California ambulance patient offload times. JAMA Network Open, 8(5), e2510325. https://doi.org/10.1001/jamanetworkopen.2025.10325
AI is moving from chat to action.In this episode of Big Ideas 2026, we unpack three shifts shaping what comes next for AI products. The change is not just smarter models, but software itself taking on a new form.You will hear from Marc Andrusko on the move from prompting to execution, Stephanie Zhang on building machine-legible systems, and Sarah Wang on agent layers that turn intent into outcomes.Together, these ideas tell a single story. Interfaces shift from chat to action, design shifts from human-first to agent-readable, and work shifts to agentic execution. AI stops being something you ask, and becomes something that does. Resources:Follow Marc Andrusko on X: https://x.com/mandrusko1Follow Stephanie Zhang on X: https://x.com/steph_zhang Follow Sarah Wang on X: https://x.com/sarahdingwangRead more all of our 2026 Big IdeasPart 1: https://a16z.com/newsletter/big-ideas-2026-part-1Part 2: https://a16z.com/newsletter/big-ideas-2026-part-2/Part 3: https://a16z.com/newsletter/big-ideas-2026-part-3/ Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease 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.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 http://a16z.com/disclosures. Stay Updated:Find 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.
We explore how to align sales, marketing, and operations so growth becomes predictable, not chaotic. Luis Baez shares practical frameworks to productize services, unify data, and raise conversion rates in a world where buyers consult AI before they call you.• breaking silos between sales, marketing and ops• why unified data beats dueling spreadsheets• shifting websites to knowledge bases for LLM era• productizing services into a signature method• pricing to outcomes and standardizing delivery• sprinting to validate offers before scaling• improving microconversions across the funnel• practical tech stack and revenue intelligence tools• managing AI anxiety and proving value with quick wins• human connection as a competitive advantageGuest Contact Information: Website: luisbaez.comLinkedIn: linkedin.com/in/baezluisYouTube: youtube.com/@unhustlingMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: 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 LLM Visibility™ and 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
Richard Gearhart and Elizabeth Gearhart, co-hosts of Passage to Profit Show interview Author or The Real Environmentalists, Jim Beach from The School for Startups, Joe Massa from Podtopia and Nicky Wake from Chapter 2 Dating. In this eye-opening episode, entrepreneur and author of The Real Envivonmentalists, Jim Beach challenges everything you think you know about climate change and environmentalism. He makes the bold case that the real heroes aren't politicians or celebrity activists, but profit-driven entrepreneurs quietly solving massive environmental problems through innovation and hard work. He also shares insights from his experience as the founder of the School for Startups. Read more at: https://realenvironmentalist.com/ and at: https://schoolforstartups.com/ Joe Massa is a podcasting veteran, media strategist, and host of The Measuring Post, and the owner of Podtopia Network, a full-service podcast network that helps creators launch, grow, and monetize their shows while connecting them with top-tier guests and sponsors. Read more at: https://www.podtopianetwork.com/ Nicky Wake is the inspiring founder of Chapter 2 Daing, who transformed her own heartbreaking loss into a powerful, compassionate community helping widows and widowers find connection, hope, and their next chapter. Read more at: https://chapter2dating.app/ Whether you're a seasoned entrepreneur, a startup, an inventor, an innovator, a small business or just starting your entrepreneurial journey, tune into Passage to Profit Show for compelling discussions, real-life examples, and expert advice on entrepreneurship, intellectual property, trademarks and more. Visit https://passagetoprofitshow.com/ for the latest updates and episodes. Chapters (00:00:00) - PODCAST: Starting a Business(00:00:36) - Passive to Profit(00:01:54) - What's the One Mind Shift That separates Business Startups from Just(00:04:15) - Mel Robbins on Just Do It(00:04:56) - How to Start a Law Practice(00:06:45) - Real Environmentalists: The Real Heroes(00:13:58) - The 10 Biggest Celebrity Hypocrites(00:16:11) - In the Elevator With Climate Change(00:17:20) - Are We Harming the Climate?(00:19:22) - Jim Beach on Capitalism and Environmentalism(00:23:51) - Car Shield(00:25:05) - Better Health Insurance for You(00:26:05) - Jim Beach on His School of Entrepreneurship(00:31:45) - What Does an Entrepreneur Need to Know About Law?(00:33:22) - Pioneer Program: Passage to Profit(00:34:40) - AI in Business(00:36:20) - How AI is Automating Your Business(00:38:21) - Are You Using AI In Your Dating Apps?(00:41:47) - Talking Tech: ChatGPT and More(00:43:43) - Are You Using AI in Your Law Firm?(00:47:01) - AI for Business: Considering Your Blind Spots(00:48:30) - Divorce Debt Relief Hotline(00:51:08) - Copyright Law: Singing Songs Should Be Paid(00:54:58) - Podtopia Network: Full-Service Podcast Network(00:58:38) - How to Get Your Voice Heard in the Media(01:03:25) - SEO for Podcasts and LLM's(01:05:37) - How to Break Through in Podcasting(01:08:04) - In the Elevator With Podcast Creator Joe Massa(01:10:28) - How to Connect with Joe Massa(01:10:58) - Widow Dating(01:16:10) - Widows' Fire vs. Chapter 2 Dating App(01:18:53) - Widows in Tech: From Business to Community(01:24:34) - How Can People Find You?(01:25:14) - Turnabout Ranch(01:26:19) - Old Keys, New Life(01:27:31) - Secrets of the Entrepreneurial Mind(01:28:49) - Jim Beach(01:30:06) - Inventors: The Corridor Principle(01:31:08) - What's Your Secret to Success as an Entrepreneur?(01:32:55) - Passage to Profit
In the Pit with Cody Schneider | Marketing | Growth | Startups
If you're not getting cited by ChatGPT, your “AI SEO” strategy isn't working, no matter what your dashboards say. Most of it is observability theater: dashboards, charts, synthetic prompts — and zero actual placement.In this episode, we chat with Shawn Schneider, founder of Eldil AI, about what actually determines whether your company shows up in ChatGPT answers. The short answer: LLMs don't reward more content, clever prompts, or prettier dashboards. They reward a small set of trusted third-party sources — and most brands aren't mentioned in any of them.Shawn breaks down why observability alone creates a false sense of progress, how to identify the specific citations that dominate your category, and how to turn that insight into real placements through outreach and negotiation. We also unpack why Google Search Console is still the best signal we have for AI-driven queries, how to prioritize the one citation that actually matters, and what the first 30–90 days can look like when you do this correctly.GuestShawn Schneider — founder of Eldil AI, a GEO / AI SEO platform focused on identifying and securing the citations LLMs rely on most; helps brands and agencies win visibility in ChatGPT by targeting the power-law sources that shape AI answers.Guest LinksLinkedIn: https://www.linkedin.com/in/shawn-schneider-61b2b5207/ Company Website: https://www.eldil.ai/What You'll LearnWhy most GEO / AI SEO observability tools are meaningless without actual placements The only thing that reliably improves AI search visibility: citation placementsHow to use Google Search Console to surface AI fan-out queriesWhy synthetic prompt data is still unreliable (and what to trust instead)The power law of citations: why only 1–3 sources actually matterHow Eldil turns citation discovery into outreach and negotiated placementsWhat 30–90 days can look like when you secure the right citationWhich industries should invest heavily — and which should ignore this for nowWhy ChatGPT dominates referral traffic compared to other LLMsWhat happens when ads arrive inside AI search resultsTimestamps00:00 — GEO, AI SEO, AEO: noise vs. reality00:21 — Why observability tools don't move the needle03:55 — Where GEO tools get their data (and why it's messy)07:16 — Using Google Search Console as a prompt proxy09:40 — The three pillars: technical, content, authority12:07 — Citations as the dominant ranking lever13:07 — The power law: thousands of citations, one winner19:07 — How fast results actually show up20:39 — When building your own citation content makes sense30:41 — Which business models win with GEO37:11 — ChatGPT ads and the future of AI search41:32 — Where to find Shawn and closing thoughts Key Topics & Ideas1. Why dashboards feel good but don't create outcomes.Most tools are essentially “Google Analytics for LLMs”ChatGPT referrals rise naturally as usage increasesCharts go up even if you do nothingWithout placements, observability is just vanity2. The three common approaches in the market today:Guessing prompts with LLMsClickstream data sourced from Chrome extensions and brokersSynthetic prompts without transparencyEldil uses Google Search Console + Analytics as the best available proxy for real intent.3. How to spot AI-generated fan-out queries:50+ character queriesHigh impressionsLow or zero clicksThese often represent LLMs expanding short prompts into long-form searches.4. The three pillars: Technical, Content, AuthorityTechnical — can an LLM crawl and understand your site?Content — does useful information exist?Authority — does anyone credible back it up?Authority is the multiplier most teams ignore.5. What actually shapes AI answers:Citations are not backlinks, they are semantic explanationsLLMs repeatedly return to the same trusted sourcesThird-party listicles and niche blogs dominate citation share6. The Power Law of Citations10k–15k citations may exist200–300 matter1–3 actually move the needleIf you're not in those, content volume won't save you.7. The real workflow:Identify high-value customer questionsExtract dominant citationsRank them by weightContact site ownersNegotiate placementMonitor AI visibility and referral trafficThis is where most tools stop — and where Eldil focuses.8. How many placements do you need?Surprisingly few.You don't need 100 placementsYou need the right oneThen expand into adjacent verticalsThis is concentrated betting, not spray-and-pray SEO.9. Why GEO feels different from traditional SEO:You are inserting into sources that already rankChanges can show up in weeks, not yearsMeaningful referral growth often appears within ~60–90 days10. Who Should (and Shouldn't) Do ThisBest fit:High-ACV B2B SaaSLong buying cyclesHigh-LTV e-commerce (supplements, skincare)ICPs that already live in ChatGPTIf your customers do not use LLMs yet, start elsewhere.11. Why ChatGPT is the main eventBased on Eldil's data:ChatGPT referrals dwarf Perplexity and othersFor most companies, this is where focus belongsSmaller channels still matter for high-ticket sales12. What's coming nextPaid placements inside LLMsOrganic plus paid becoming a one-two punchCitation inventory getting expensive fastThe window for cheap dominance will not last.SponsorToday's episode is brought to you by Graphed – an AI data analyst & BI platform.With Graphed you can:Connect data like GA4, Facebook Ads, HubSpot, Google Ads, Search Console, AmplitudeBuild interactive dashboards just by chatting (no Looker Studio/Tableau learning curve)Use it as your ETL + data warehouse + BI layer in one placeAsk:“Build me a stacked bar chart of new users vs. all users over time from GA4”…and Graphed just builds it for you.
Here it is! We review the year where scaling large AI models hit its ceiling, Google reclaimed momentum with efficient vertical integration, and the market shifted from hype to viability. Join us as we talk about why human-in-the-loop is failing, why generative AI agents validating other agents compounds errors, and how small expert data quietly beat the big models.• Google's resurgence with Gemini 3.0 and TPU-driven efficiency• Monetization pressures and ads in co-pilot assistants• Diminishing returns from LLM scaling• Human-in-the-loop pitfalls and incentives• Agents vs validation and compounding error• Small, high-quality data outperforming synthetic• Expert systems, causality, and interpretability• Research trends return toward statistical rigor• 2026 outlook for ROI, governance, and trustWe remain focused on the responsible use of AI. And while the market continues to adjust expectations for return on investment from AI, we're excited to see companies exploring "return on purpose" as the new foray into transformative AI systems for their business. What are you excited about for AI in 2026? What did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.
The search landscape has fundamentally shifted. 60% of Google searches now result in zero clicks. People are getting answers from AI without ever visiting websites. If you've noticed declining organic traffic or wondered why your content isn't getting clicks despite good rankings, this episode reveals what's happening and what to do about it. This compilation brings together five search and PR experts on how AI is changing buyer behavior and what actually works now. Jon Gillham from Originality.ai explains why citations, statistics, and quotes are essential for LLM visibility. Patty Parobek reframes the conversation with a surprising stat: Google grew by four ChatGPTs in 2024. Maurice White details the technical foundation that makes GEO work, while Chris Harihar explains why PR is now both top and bottom of the funnel. Gareth Cunningham ties it together with the reality that GEO only works when solid SEO fundamentals are in place. The shift isn't about producing more content. It's about strategic placement, quality sourcing, and building topical authority that AI engines trust. From structured data to brand mentions, from Google Business profiles to cited content, this episode provides a roadmap for 2026 and beyond. Featured Experts: Jon Gillham - Founder of Originality.ai shares proven strategies for LLM visibility and avoiding AI content detection. Listen to the full episode Patty Parobek - VP of AI and ML at Mod Op Transformation Breaks down the zero-click phenomenon and what it means for traffic strategies. Listen to the full episode Maurice White, Senior SEO Strategist at Mod Op, details the technical foundation required before GEO optimization works. Listen to the full episode Chris Harihar - EVP of PR at Mod Op explores how PR and SEO converge in the AI search era. Listen to the full episode Gareth Cunningham - Director of Search Experience at Mod Op explains why GEO only works on top of solid SEO fundamentals. Listen to the full episode This isn't about abandoning SEO. It's about evolving your strategy for how people actually research and buy today.
Есть предположение, что злоупотребление LLM в общем и вайбкодинг в частности отупляет программистов. С другой стороны, этот наброс похож на квохтание Vim-еров на IDE-шников. Где же правда?Спасибо всем, кто нас слушает. Ждем Ваши комментарии.Музыка из выпуска: - https://artists.landr.com/056870627229- https://t.me/angry_programmer_screamsВесь плейлист курса "Kubernetes для DotNet разработчиков": https://www.youtube.com/playlist?list=PLbxr_aGL4q3SrrmOzzdBBsdeQ0YVR3Fc7Бесплатный открытый курс "Rust для DotNet разработчиков": https://www.youtube.com/playlist?list=PLbxr_aGL4q3S2iE00WFPNTzKAARURZW1ZShownotes: 00:00:00 Вступление00:06:15 Из-за чего тупеют люди?00:09:00 Если LLM не подошел, проблема в тебе00:15:35 Плохо ли генерить тесты LLM?00:20:00 Терминальный вайбкодинг00:29:00 Поиск API через LLM 00:34:30 Проектирует человек, а кодит LLM00:42:40 Катастрофа мотивации00:46:15 Эффект циганского гипноза00:51:20 Тупеем ли от поиска через LLM?01:00:00 LLM ловит нас на крючекСсылки:- https://www.youtube.com/watch?v=COovfRQ9hRM : Наше будущее - https://www.linkedin.com/posts/nityan_we-all-know-vibe-coding-has-technical-debt-activity-7339687364216193025-nY2E : Исследование отупения от ИИ - https://codeua.com/ai-coding-tools-can-reduce-productivity-study-results/ : AI Coding Tools Can Reduce Productivity: Study ResultsВидео: https://youtube.com/live/HU7m31-NZmM Слушайте все выпуски: https://dotnetmore.mave.digitalYouTube: https://www.youtube.com/playlist?list=PLbxr_aGL4q3R6kfpa7Q8biS11T56cNMf5Twitch: https://www.twitch.tv/dotnetmoreОбсуждайте:- Telegram: https://t.me/dotnetmore_chatСледите за новостями:– Twitter: https://twitter.com/dotnetmore– Telegram channel: https://t.me/dotnetmoreCopyright: https://creativecommons.org/licenses/by-sa/4.0/
What are the advantages of spec-driven development compared to vibe coding with an LLM? Are these recent trends a move toward declarative programming? This week on the show, Marc Brooker, VP and Distinguished Engineer at AWS, joins us to discuss specification-driven development and Kiro.
How do you build an AI product that's powerful, reliable, and grounded in real user needs? In this podcast hosted by Qventus Product Director Mark Bailes, Google Product Lead Alankar Agnihotri discusses what it really takes to build impactful AI and LLM-driven products. He shares the hidden complexities behind model behavior, the shift from deterministic to probabilistic design, and what product managers must do to deliver AI experiences that scale. You'll hear firsthand insights from someone shaping Gemini in Android Automotive and building the future of in-car intelligence.
Renegade Thinkers Unite: #2 Podcast for CMOs & B2B Marketers
GenAI now sits inside content workflows, SDR outreach, and competitive intelligence. Marketing teams are seeing real wins and real growing pains, and the open question is where to focus next. To answer that, Drew brings together Kelly Hopping, John McKinney (Cornerstone Licensing), and Brian Hankin (Altium Packaging) to share the AI plays they are running right now and how they're leading the charge. Here's how: In this episode: Kelly shows how AI weaves through content, SDR workflows, web chat, product work, and SEO, plus how OKRs and certifications lift AI fluency across the team. John uses AI agents for competitor tracking, outbound support, and coding, and treats AI as a sparring partner for strategy before it reaches the C suite. Brian runs an AI campaign engine that builds multi-touch programs in minutes and tracks lifts in engagement, qualified leads, proposals, and wins. Plus: How AEO connects to SEO and what needs to shift for LLM-driven discovery How leaders model AI use with internal knowledge bases and cross-functional pilots How to structure AI readiness Where CMOs can start Tune in if you want AI use cases you can put to work now and a clearer view of where to point your team next. For full show notes and transcripts, visit https://renegademarketing.com/podcasts/ To learn more about CMO Huddles, visit https://cmohuddles.com/
The Philadelphia Inquirer never had an AI engineer on staff until the Lenfest AI Collaborative & Fellowship program changed that.The collaborative is a $5 million partnership between the Lenfest Institute, OpenAI, and Microsoft that placed 10 AI fellows in American newsrooms for two years. These engineers work within the organizations, building tools that solve real newsroom problems.This week on Newsroom Robots, host Nikita Roy sits down with Jim Friedlich, CEO and Executive Director of the Lenfest Institute, David Chivers, lead advisor to the Lenfest AI Collaborative and Matt Boggie, CTO of The Philadelphia Inquirer, to walk through how the program works and what the Inquirer has built as a result.The Inquirer came to the collaborative with an idea to build a full-archive search tool that would let reporters query decades of journalism. They expected it to take 24 months. Within two weeks of a Microsoft hackathon, they had working code. The tool, now called Dewey, searches everything the Inquirer has published since 1978.This episode covers:03:02 — How the Lenfest AI Collaborative got started05:34 — Can newsrooms trust big tech partners?08:33 — How the fellowship works day to day14:52– Inside the Microsoft hackathon that built Dewey in two weeks21:37 — Training journalists to understand LLM limitations24:07 — How AI literacy has changed newsroom culture29:45 – How small newsrooms can get started with AI35:14 — AI answers, search decline, and the future of audience traffic38:15 — Rethinking journalism's role in an AI-mediated world41:23 — Closing reflections and personal AI useThis episode of Newsroom Robots is supported by the Lenfest Institute for Journalism. Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.
The three guys are back this week with special guest Nathan Leamer (CEO, Fixed Gear Strategies) to discuss artificial intelligence (AI). As CEO and Ruling Elder (PCA), Nathan navigates the intersection of technology, public policy, and the kingdom of God in this insightful and engaging conversation. Of note, Barry learns what LLM means and also …
When Jacob Dean looks back on his career, the through-line isn't a straight path — it's a steady climb built on curiosity, discipline, and the courage to rethink what success should look like. Raised in Northeast Ohio in a family of educators, Jacob grew up with a traditional definition of stability: find a good job, work hard, and build a dependable life. Entrepreneurship wasn't part of the conversation. Yet over time, Jacob discovered that he was drawn to something bigger — the intersection of law, business, and strategy.After majoring in finance, Jacob chose law school at a time when the economy was uncertain and job prospects were slim. But that step opened the door to a series of defining opportunities: working in the tax department at Procter & Gamble, clerking for the U.S. Tax Court, completing an LLM at Georgetown, and gaining meaningful experience in both law firm and in-house roles. Each chapter gave him new layers of expertise — tax structure, corporate operations, nonprofit compliance, and business management.Despite the steady progression, something deeper was brewing. Jacob realized that what energized him most wasn't just the practice of law — it was understanding how businesses run, how decisions get made, and how structure shapes success. He enjoyed the legal work, but he felt most at home thinking like an operator and strategist.Then came a turning point: turning 40. Instead of seeing it as a crisis, Jacob treated it as a moment of reflection — a chance to pause long enough to ask, What do I want the next decade to look like? The answer was clear: it was time to build something of his own.With support from family and colleagues, Jacob made the leap into entrepreneurship and launched his own firm. Unlike many attorneys who see the business side as a distraction, Jacob embraces it. He believes law firms should operate like true businesses — strategic, structured, and growth-minded — rather than relying on outdated norms or reactive hiring. His combined experience in tax and corporate law gives him a unique ability to help founders avoid pitfalls and build with intention.In this episode of The Inventive Journey, Jacob shares the decisions that shaped him, the pressure he once felt to take opportunities out of fear, and the mindset shift that now guides his career. He talks openly about learning to trust himself, redefining what a “successful” legal career looks like, and why entrepreneurship still excites him every day.His advice for new founders is refreshingly simple: get good help. Whether you're forming a company, raising capital, managing risk, or planning for growth, trying to do everything alone can cost far more than it saves. Good advisors, good structure, and good decision-making create the runway that businesses need to thrive.Jacob's story isn't just about leaving a job — it's about stepping into a role he was already preparing for through every chapter of his career. It's a reminder that experience compounds, reflection matters, and it's never too late to build a business on your own terms.
We're really moving from a world where humans are authoring search queries and humans are executing those queries and humans are digesting the results to a world where AI is doing that for us.Jeff Huber, CEO and co-founder of Chroma, joins Hugo to talk about how agentic search and retrieval are changing the very nature of search and software for builders and users alike.We Discuss:* “Context engineering”, the strategic design and engineering of what context gets fed to the LLM (data, tools, memory, and more), which is now essential for building reliable, agentic AI systems;* Why simply stuffing large context windows is no longer feasible due to “context rot” as AI applications become more goal-oriented and capable of multi-step tasks* A framework for precisely curating and providing only the most relevant, high-precision information to ensure accurate and dependable AI systems;* The “agent harness”, the collection of tools and capabilities an agent can access, and how to construct these advanced systems;* Emerging best practices for builders, including hybrid search as a robust default, creating “golden datasets” for evaluation, and leveraging sub-agents to break down complex tasks* The major unsolved challenge of agent evaluation, emphasizing a shift towards iterative, data-centric approaches.You can also find the full episode on Spotify, Apple Podcasts, and YouTube.You can also interact directly with the transcript here in NotebookLM: If you do so, let us know anything you find in the comments!
Alexandru Voica, Head of Corporate Affairs and Policy at Synthesia, discusses how the world's largest enterprise AI video platform has approached trust and safety from day one. He explains Synthesia's "three C's" framework—consent, control, and collaboration: never creating digital replicas without explicit permission, moderating every video before rendering, and engaging with policymakers to shape practical regulation. Voica acknowledges these safeguards have cost some business, but argues that for enterprise sales, trust is competitively essential. The company's content moderation has evolved from simple keyword detection to sophisticated LLM-based analysis, recently withstanding a rigorous public red team test organized by NIST and Humane Intelligence. Voica criticizes the EU AI Act's approach of regulating how AI systems are built rather than focusing on harmful outcomes, noting that smaller models can now match frontier capabilities while evading compute-threshold regulations. He points to the UK's outcome-focused approach—like criminalizing non-consensual deepfake pornography—as more effective. On adoption, Voica argues that AI companies should submit to rigorous third-party audits using ISO standards rather than publishing philosophical position papers—the thesis of his essay "Audits, Not Essays." The conversation closes personally: growing up in 1990s Romania with rare access to English tutoring, Voica sees AI-powered personalized education as a transformative opportunity to democratize learning. Alexandru Voica is the Head of Corporate Affairs and Policy at Synthesia, the UK's largest generative AI company and the world's leading AI video platform. He has worked in the technology industry for over 15 years, holding public affairs and engineering roles at Meta, NetEase, Ocado, and Arm. Voica holds an MSc in Computer Science from the Sant'Anna School of Advanced Studies and serves as an advisor to MBZUAI, the world's first AI university. Transcript Audits, Not Essays: How to Win Trust for Enterprise AI (Transformer) Synthesia's Content Moderation Systems Withstand Rigorous NIST, Humane Intelligence Red Team Test (Synthesia) Computerspeak Newsletter
Datawizz is pioneering continuous reinforcement learning infrastructure for AI systems that need to evolve in production, not ossify after deployment. After building and exiting RapidAPI—which served 10 million developers and had at least one team at 75% of Fortune 500 companies using and paying for the platform—Founder and CEO Iddo Gino returned to building when he noticed a pattern: nearly every AI agent pitch he reviewed as an angel investor assumed models would simultaneously get orders of magnitude better and cheaper. In a recent episode of BUILDERS, we sat down with Iddo to explore why that dual assumption breaks most AI economics, how traditional ML training approaches fail in the LLM era, and why specialized models will capture 50-60% of AI inference by 2030. Topics Discussed Why running two distinct businesses under one roof—RapidAPI's developer marketplace and enterprise API hub—ultimately capped scale despite compelling synergy narratives The "Big Short moment" reviewing AI pitches: every business model assumed simultaneous 1-2 order of magnitude improvements in accuracy and cost Why companies spending 2-3 months on fine-tuning repeatedly saw frontier models (GPT-4, Claude 3) obsolete their custom work The continuous learning flywheel: online evaluation → suspect inference queuing → human validation → daily/weekly RL batches → deployment How human evaluation companies like Scale AI shift from offline batch labeling to real-time inference correction queues Early GTM through LinkedIn DMs to founders running serious agent production volume, working backward through less mature adopters ICP discovery: qualifying on whether 20% accuracy gains or 10x cost reductions would be transformational versus incremental The integration layer approach: orchestrating the continuous learning loop across observability, evaluation, training, and inference tools Why the first $10M is about selling to believers in continuous learning, not evangelizing the category GTM Lessons For B2B Founders Recognize when distribution narratives mask structural incompatibility: RapidAPI had 10 million developers and teams at 75% of Fortune 500 paying for the platform—massive distribution that theoretically fed enterprise sales. The problem: Iddo could always find anecdotes where POC teams had used RapidAPI, creating a compelling story about grassroots adoption. The critical question he should have asked earlier: "Is self-service really the driver for why we're winning deals, or is it a nice-to-have contributor?" When two businesses have fundamentally different product roadmaps, cultures, and buying journeys, distribution overlap doesn't create a sustainable single company. Stop asking if synergies exist—ask if they're causal. Qualify on whether improvements cross phase-transition thresholds: Datawizz disqualifies prospects who acknowledge value but lack acute pain. The diagnostic questions: "If we improved model accuracy by 20%, how impactful is that?" and "If we cut your costs 10x, what does that mean?" Companies already automating human labor often respond that inference costs are rounding errors compared to savings. The ideal customers hit differently: "We need accuracy at X% to fully automate this process and remove humans from the loop. Until then, it's just AI-assisted. Getting over that line is a step-function change in how we deploy this agent." Qualify on whether your improvement crosses a threshold that changes what's possible, not just what's better. Use discovery to map market structure, not just validate hypotheses: Iddo validated that the most mature companies run specialized, fine-tuned models in production. The surprise: "The chasm between them and everybody else was a lot wider than I thought." This insight reshaped their entire strategy—the tooling gap, approaches to model development, and timeline to maturity differed dramatically across segments. Most founders use discovery to confirm their assumptions. Better founders use it to understand where different cohorts sit on the maturity curve, what bridges or blocks their progression, and which segments can buy versus which need multi-year evangelism. Target spend thresholds that indicate real commitment: Datawizz focuses on companies spending "at a minimum five to six figures a month on AI and specifically on LLM inference, using the APIs directly"—meaning they're building on top of OpenAI/Anthropic/etc., not just using ChatGPT. This filters for companies with skin in the game. Below that threshold, AI is an experiment. Above it, unit economics and quality bars matter operationally. For infrastructure plays, find the spend level that indicates your problem is a daily operational reality, not a future consideration. Structure discovery to extract insight, not close deals: Iddo's framework: "If I could run [a call where] 29 of 30 minutes could be us just asking questions and learning, that would be the perfect call in my mind." He compared it to "the dentist with the probe trying to touch everything and see where it hurts." The most valuable calls weren't those that converted to POCs—they came from people who approached the problem differently or had conflicting considerations. In hot markets with abundant budgets, founders easily collect false positives by selling when they should be learning. The discipline: exhaust your question list before explaining what you build. If they don't eventually ask "What do you do?" you're not surfacing real pain. Avoid the false-positive trap in well-funded categories: Iddo identified a specific risk in AI: "You can very easily run these calls, you think you're doing discovery, really you're doing sales, you end up getting a bunch of POCs and maybe some paying customers. So you get really good initial signs but you've never done any actual discovery. You have all the wrong indications—you're getting a lot of false positive feedback while building the completely wrong thing." When capital is abundant and your space is hot, early revenue can mask product-market misalignment. Good initial signs aren't validation if you skipped the work to understand why people bought. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM
We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit
We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit
We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit
In this 5 Insightful Minutes episode, David Dorf, Head of Retail Industry Solutions at AWS, joins Omni Talk to cut through the AI hype and reveal what's actually coming for retail in 2026. From LLM limitations to agentic commerce reality checks, David breaks down why domain-specific models are replacing frontier model fantasies, how answer engines will reshape search, and why shopping agents will start with your grocery delivery. If you've ever wondered what AI predictions are worth believing, this episode delivers the clarity you need.
We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit
In this episode of the Microsoft Threat Intelligence Podcast, host Sherrod DeGrippo is joined by security researchers Geoff McDonald and JBO to discuss Whisper Leak, new research showing that encrypted AI traffic can still unintentionally reveal what a user is asking about through patterns in packet size and timing. They explain how LLM token streaming enables this kind of side-channel attack, why even well-encrypted conversations can be classified for sensitive topics, and what this means for privacy, national-level surveillance risks, and secure product design. The conversation also walks through how the study was conducted, what patterns emerged across different AI models, and the steps developers should take to mitigate these risks. In this episode you'll learn: Why packet sizes and timing patterns reveal more information than most users realize How user-experience choices like showing streamed text create a larger attack surface The difference between classic timing attacks and the new risks uncovered in Whisper Leak Resources: View JBO on LinkedIn View Geoff McDonald on LinkedIn View Sherrod DeGrippo on LinkedIn Learn more about Whisper Leak Related Microsoft Podcasts: Afternoon Cyber Tea with Ann Johnson The BlueHat Podcast Uncovering Hidden Risks Discover and follow other Microsoft podcasts at microsoft.com/podcasts Get the latest threat intelligence insights and guidance at Microsoft Security Insider The Microsoft Threat Intelligence Podcast is produced by Microsoft, Hangar Studios and distributed as part of N2K media network.
We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit
The Steam machine will use an older HDMI standard because of arbitrary rules, more details about running X86 Windows games on Arm Linux, and the Steam Controller lives on. Plus Calibre is adding “AI”, and we laugh at another LLM. News Why won't Steam Machine support HDMI 2.1? Digging in on the display standard drama Steam Machine today, Steam Phones tomorrow Remember Google Stadia? Steam finally made its gamepad worth rescuing Talk to your Fedora system with the linux-mcp-server! Calibre adds AI “discussion” feature Because the Calibre ebook library software just acquired AI garbage it has *already* been forked AI and GNOME Shell Extensions Tailscale Tailscale is an easy to deploy, zero-config, no-fuss VPN that allows you to build simple networks across complex infrastructure. Go to tailscale.com/lnl and try Tailscale out for free for up to 100 devices and 3 users, with no credit card required. Use code LATENIGHTLINUX for three free months of any Tailscale paid plan. Support us on patreon and get an ad-free RSS feed with early episodes sometimes See our contact page for ways to get in touch. RSS: Subscribe to the RSS feeds here
Hey CX Nation,In this week's episode of The CXChronicles Podcast #274, we welcomed Dave Rennyson, President & CEO at SuccessKPI based in the Washington, DC area. SuccessKPI is an on-demand insight and action platform that removes the obstacles that agents, managers, and executives encounter in delivering exceptional customer service.SuccessKPI is trusted by some of the world's largest government, BPO, financial, healthcare, and technology contact centers in the United States, Europe, and Latin America.In this episode, Dave and Adrian chat through the Four CX Pillars: Team, Tools, Process & Feedback. Plus share some of the ideas that his team think through on a daily basis to build world class customer experiences.**Episode #274 Highlight Reel:**1. Why the best organizations & teams invest in constant training efforts 2. How music and business are wildly similar 3. Leveraging & investing in AI over the next 1,000 days 4. Understanding the power of your data architecture 5. Tomorrow's leading tech-companies will bring solutions, not headaches Click here to learn more about Dave RennysonClick here to learn more about SuccessKPIHuge thanks to Dave for coming on The CXChronicles Podcast and featuring his work and efforts in pushing the customer experience & contact center space into the future. For all of our Apple & Spotify podcast listener friends, make sure you are following CXC & please leave a 5 star review so we can find new members of the "CX Nation". You know what would be even better?Go tell your friends or teammates about CXC's custom content, strategic partner solutions (Hubspot, Intercom, & Freshworks) & On-Demand services & invite them to join the CX Nation, a community of 15K+ customer focused business leaders!Want to see how your customer experience compares to the world's top-performing customer focused companies? Check out the CXC Healthzone, an intelligence platform that shares benchmarks & insights for how companies across the world are tackling The Four CX Pillars: Team, Tools, Process & Feedback & how they are building an AI-powered foundation for the future. Thanks to all of you for being apart of the "CX Nation" and helping customer focused business leaders across the world make happiness a habit!Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!
In this episode of Building Better Foundations, we interview Hunter Jensen, founder and CEO of Barefoot Solutions and Barefoot Labs, to explore what it really takes when getting started with AI in your business. As companies rush toward AI adoption, Hunter offers grounded, practical advice on avoiding early mistakes, protecting your data, and choosing the right starting point. About Hunter Jensen Hunter Jensen is the Founder and CEO of Barefoot Solutions, a digital agency specializing in artificial intelligence, data science, and digital transformation. With over 20 years of experience, Hunter has worked with startups and Fortune 500 companies, including Microsoft and Salesforce, to implement innovative technology strategies that drive measurable ROI. A seasoned leader and expert in the AI space, Hunter helps businesses harness cutting-edge technologies to achieve growth and efficiency. Facebook / Twitter (X) / LinkedIn / Website Why "Just Add AI" Is Not a Strategy When Getting Started with AI in Your Business Hunter begins by addressing the biggest misconception leaders face when getting started with AI in their business: the belief that a single, all-knowing model can absorb everything your business does and instantly deliver insights across every department. "Leaders imagine an all-knowing model. We are nowhere near that being safe or realistic." – Hunter Jensen The core issue is access control. Even the best models cannot safely enforce who should or should not see certain data. If an LLM is trained on HR data, how do you stop it from sharing salary information with an employee who shouldn't see it? This is why getting started with AI in your business must begin with clear boundaries and realistic expectations. Safe First Steps When Getting Started with AI in Your Business As Hunter explains, companies don't need to dive straight into custom models. A safer, simpler path exists for getting started with AI in your business, especially for teams on Microsoft 365 or Google Workspace. Start With Tools Already Built Into Your Environment Hunter recommends two solid, low-risk entry points: Microsoft 365 Copilot Google Gemini for Workspace These platforms provide: Built-in enterprise protections Familiar workflows Safe, contained AI access A gentle learning curve for employees Hunter emphasizes that employees are already using public AI tools, even if policy forbids it. When getting started with AI in your business, providing approved tools is essential to keeping data safe. "If you're not providing safe tools, your team will use unsafe ones." – Hunter Jensen These tools won't solve every AI need, but they are an ideal first step. Choosing the Right Model for Your Needs Another common question when getting started with AI in your business is: Which model is best? ChatGPT? Gemini? Claude? Hunter explains that the landscape changes weekly—sometimes daily. Today's leading model could be irelevent tomorrow. For this reason, businesses should avoid hard commitments to a single model. Experiment Before Committing Hunter suggests opening multiple LLMs side-by-side—such as ChatGPT, Claude, and Perplexity—and testing each for quality and speed. This gives teams a feel for what works before deciding how AI fits into their workflow. This experimentation mindset is essential when getting started with AI in your business because: Different models excel at different tasks Some models are faster or cheaper Some handle long context or code better New releases constantly change the landscape Your AI system should remain flexible enough to shift models as needed. Protecting Your Data from Day One One of Hunter's strongest warnings is about data safety. If you're serious about getting started with AI in your business, you must pay attention to licensing. If you are not paying for AI, you have no control over your data. Some industries—like legal, finance, and healthcare—may need even stricter controls or private deployments. This leads naturally to the next stage of AI adoption. The Next Step After Getting Started with AI in Your Business Once companies understand their needs, the next phase is building an internal system that: Connects securely to business software Honors existing user permissions Keeps all data inside the company network Uses models selected for specific tasks Hunter's product Compass is perfect for this phase. Instead of trusting the model to protect data, you rely on your own systems and access controls. This is how AI becomes truly safe and powerful. "The model should only see what the user is allowed to see—nothing more." – Hunter Jensen Final Thoughts on Getting Started with AI in Your Business Part 1 of our interview with Hunter Jensen makes one thing clear: getting started with AI in your business isn't about chasing the latest model. It's about protecting your data, giving your team safe tools, and preparing for a multi-model future. Stay tuned for Part 2 as we dive deeper into internal AI deployment, advanced architectures, and building long-term AI strategy. Stay Connected: Join the Developreneur Community We invite you to join our community and share your coding journey with us. Whether you're a seasoned developer or just starting, there's always room to learn and grow together. Contact us at info@develpreneur.com with your questions, feedback, or suggestions for future episodes. Together, let's continue exploring the exciting world of software development. Additional Resources Leveraging AI for Business: How Automation and AI Boost Efficiency and Growth Business Automation and Templates: How to Streamline Your Workflow Why Bother With Automated Testing? Building Better Foundations Podcast Videos – With Bonus Content
The Steam machine will use an older HDMI standard because of arbitrary rules, more details about running X86 Windows games on Arm Linux, and the Steam Controller lives on. Plus Calibre is adding “AI”, and we laugh at another LLM. News Why won't Steam Machine support HDMI 2.1? Digging in on the display standard drama Steam Machine today, Steam Phones tomorrow Remember Google Stadia? Steam finally made its gamepad worth rescuing Talk to your Fedora system with the linux-mcp-server! Calibre adds AI “discussion” feature Because the Calibre ebook library software just acquired AI garbage it has *already* been forked AI and GNOME Shell Extensions Tailscale Tailscale is an easy to deploy, zero-config, no-fuss VPN that allows you to build simple networks across complex infrastructure. Go to tailscale.com/lnl and try Tailscale out for free for up to 100 devices and 3 users, with no credit card required. Use code LATENIGHTLINUX for three free months of any Tailscale paid plan. Support us on patreon and get an ad-free RSS feed with early episodes sometimes See our contact page for ways to get in touch. RSS: Subscribe to the RSS feeds here
Tech leaders are pushing the idea that automation can strengthen democracy — but as usual, their bold suggestions are based on castles made of sand. Alex and Emily tear down some flimsy arguments for AI governance, exposing their incorrect assumptions about the democratic process.References:"This Is No Way to Rule a Country""Four ways AI is being used to strengthen democracies worldwide"Also referenced:Collective Intelligence Project surveysInterview with CalMatters CEOFresh AI Hell:Amazon introduces AI translation for Kindle authorsNature op ed recommends AI versions of Einstein, Bohr, and FeynmanAn AI Podcasting Machine Is Churning Out 3,000 Episodes a WeekAI dating café to open in New YorkRecipe slop flooding social mediaAI slop about Autism published in NatureUpwork ad for fixing LLM editorial"Hundreds of Chicago residents sign petition to pause robot delivery pilot program over safety concerns"Check out future streams on Twitch. Meanwhile, send us any AI Hell you see.Our book, 'The AI Con,' is out now! Get your copy now.Subscribe to our newsletter via Buttondown. Follow us!Emily Bluesky: emilymbender.bsky.social Mastodon: dair-community.social/@EmilyMBender Alex Bluesky: alexhanna.bsky.social Mastodon: dair-community.social/@alex Twitter: @alexhanna Music by Toby Menon.Artwork by Naomi Pleasure-Park. Production by Ozzy Llinas Goodman.
About this episode: Attacking health care facilities and providers is becoming a standard strategy of war in places like Colombia, Lebanon, Ukraine, and Gaza, and it is increasingly being perpetrated by state actors. In this episode: Health and human rights lawyer Leonard Rubenstein discusses these disturbing trends, why there's so little accountability for attacks on health care, and what it would take to see meaningful progress. Guests: Leonard Rubenstein, JD, LLM, is a lawyer who has spent his career in health and human rights in armed conflict. He is core faculty of the Johns Hopkins Center for Public Health and Human Rights and the Berman Institute of Bioethics. Host: Dr. Josh Sharfstein is distinguished professor of the practice in Health Policy and Management, a pediatrician, and former secretary of Maryland's Health Department. Show links and related content: How attacking healthcare has become a strategy of war—British Medical Journal Safeguarding Health in Conflict Coalition, 2024 Report Violence Against Health Care in Conflict: 2024 Report—Public Health On Call (June 2025) Transcript information: Looking for episode transcripts? Open our podcast on the Apple Podcasts app (desktop or mobile) or the Spotify mobile app to access an auto-generated transcript of any episode. Closed captioning is also available for every episode on our YouTube channel. Contact us: Have a question about something you heard? Looking for a transcript? Want to suggest a topic or guest? Contact us via email or visit our website. Follow us: @PublicHealthPod on Bluesky @PublicHealthPod on Instagram @JohnsHopkinsSPH on Facebook @PublicHealthOnCall on YouTube Here's our RSS feed Note: These podcasts are a conversation between the participants, and do not represent the position of Johns Hopkins University.
We explore how buying decisions now pivot inside large language models and why e‑commerce brands must earn trust through proof, consistency, and email systems that never sleep. Nikita shares practical frameworks for list growth, deliverability, and flows that convert.• LLM visibility as a new trust signal• Post‑discovery research inside ChatGPT• Rising skepticism and the need for social proof• E‑commerce maturity from hacks to systems• Small brands out‑innovating slower incumbents• Case study of at‑home aligners capturing demand• Building an email list with pop‑ups and content• Essential automations across the customer journey• Deliverability safeguards and sunsetting strategyGuest Contact Information: Website: aspektagency.comInstagram: instagram.com/nikitavakhrushvLinkedIn: linkedin.com/in/nikita-vTwitter/X: x.com/nikitavakhrushvYouTube: youtube.com/NikitaVakhrushevTVMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: 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 LLM Visibility™ and 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
In this episode, Charu Navatia, Associate Vice President of Automation at Infinx, walks through the Document Capture AI Agent platform and how it classifies, extracts, and routes high-volume fax and digital documents like orders, authorizations, and insurance cards. She explains the human-in-the-loop safety net, LLM-based accuracy tuning, and integration patterns that turn messy inbound documents into clean, system-ready data for downstream revenue cycle workflows.
Eric Bowman (CTO @ King.com, previously CTO at TomTom and VP Engineering at Zalando) returns to the alphalist podcast to unpack what “agentic engineering” really means in practice—and how to introduce it to teams without turning it into a mandate. We talk about the uncomfortable trade-offs behind “YOLO mode” tooling, why adoption should feel voluntary even when you set explicit goals (like “five AI-assisted commits” as a company-level key result), and why the real opportunity isn't just faster coding—it's building a learning system that relentlessly reduces time-to-learning and time-to-value. The conversation spans practical rollout patterns, DORA/value-stream thinking, Toyota's Andon-cord mindset applied to software, multi-agent decision support with MCP, and why the CTO role may keep converging with product as AI pushes organizations to optimize for iteration speed over output volume.
Welcome back to the Ultimate Guide to Partnering® Podcast. AI agents are your next customers. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ Jen Odess, Group Vice President of Partner Excellence at ServiceNow, joins Vince Menzione to discuss the company’s incredible transformation from an IT ticketing solution to a leading AI-native platform for business transformation. Jen dives deep into how ServiceNow has strategically invested in and infused AI into its unified platform over the last decade, enabling over a billion workflows daily. She also outlines the critical role of the partner ecosystem, which executes 87% of all implementations, and reveals the company’s strategic initiatives, including its commitment to the hyperscaler marketplaces, the goal to hit half a billion dollars in annual contract value for its Now Assist AI product, and the push for partners to adopt an ‘AI-native’ methodology to capitalize on the fact that customers still want over 70% of AI buying to be done through partners. Key Takeaways ServiceNow is an ‘AI-native’ company, having invested in and built AI directly into its unified platform for over a decade. The company’s core value today is in its unified AI platform, single data model, and leadership in workflows that connect the entire enterprise. ServiceNow will hit $500 million in annual contract value for its Now Assist AI products by the end of 2025, making it the fastest-growing product in company history. An astonishing 87% of all ServiceNow implementations are done by its global partner ecosystem, highlighting their crucial role. The company is leveraging the half-trillion-dollar opportunity of durable cloud budgets by driving marketplace transactions and helping customers burn down cloud commits using ServiceNow solutions. To win in the AI era, partners must adopt AI internally, co-innovate on the platform, and strategically differentiate themselves to rank higher in the forthcoming agentic matching system. Key Tags: ServiceNow, AI-native platform, Now Assist, Jen Odess, partner excellence, workflow leader, AI platform for business transformation, hyperscalers, Microsoft Azure, Google Cloud, AWS, marketplace transactions, cloud commits, AIDA model, agentic matching, F-Pattern, Z-Pattern, group vice president, MSP, GSI, co-innovation, autonomous implementation, technical constraints, visual hierarchy, UX, UI, responsive design. Ultimate Partner is the independent community for technology leaders navigating the tectonic shifts in cloud, AI, marketplaces, and co-selling. Through live events, UPX membership, advisory, and the Ultimate Guide to Partnering® podcast, we help organizations align with hyperscalers, accelerate growth, and achieve their greatest results through successful partnering. Transcript: Jen Odess Audio Podcast [00:00:00] Jen Odess: The AI platform for business transformation, and I love to say to people, it sounds like a handful of cliche words that just got stacked together. The AI platform for business transformation. Yeah. We all know these words, so many companies use ’em, but it is such deliberate language and I love to explain why. [00:00:20] Vince Menzione: Welcome to, or welcome back to The Ultimate Guide to Partnering. I’m Vince Menzi on your host, and my mission is to help leaders like you achieve your greatest results through successful partnering. Today we have a special leader, Jen Odes is the GVP for Partner Excellence at ServiceNow. And joins me here in the studio in Boca Raton. [00:00:40] Vince Menzione: Jen, welcome to the podcast. Thanks, Vince. It’s so great to be here. I am so thrilled to welcome you. To Boca Raton, Florida. Our podcast home look at this amazing background we have Here is this, and this is where we host our ultimate partner Winter retreat. Actually, in February, we’re gonna give that a plug. [00:00:58] Vince Menzione: Okay. I’d love to have you come back. I’d love to have an invite. And you flew in this morning from Washington DC [00:01:04] Jen Odess: I did. It was 20 degrees when I left my house this morning and this backdrop. Is definitely giving me, island South Florida like vibes. It’s fabulous. [00:01:13] Vince Menzione: And we’re gonna talk about ServiceNow. [00:01:14] Vince Menzione: And you’re also opening an office down here? We [00:01:17] Jen Odess: are [00:01:17] Vince Menzione: in West Palm Beach. Not too far from where we are. Yes. Later 2026. Yeah. I love that. And then so we’ll work on the recruiting year, but let’s dive in. Okay. So thrilled to have ServiceNow and to have you in the room. This has been an incredible time for your organization. [00:01:31] Vince Menzione: I have been watching, obviously I work with Microsoft. We’ve had Google. In the studio, Amazon onboard as well. And other than those three organizations, I can’t think of any other legacy organization that has embraced AI more succinctly than ServiceNow. And I thought we’d start there, but I really wanna spend some time getting to know you and getting to know your role, your mission, and your journey to this incredible. [00:01:57] Vince Menzione: Leadership role as a global vice president. We’ll talk about Or [00:02:01] Jen Odess: group. Group Vice president. I know it doesn’t roll off the tongue. I get it. A group vice president doesn’t roll. [00:02:05] Vince Menzione: G-V-P-G-V-P doesn’t roll off the time. And in some organizations it is global. It is in other organizations, it’s group. So let’s, you’re not [00:02:12] Jen Odess: the first to say global vice president. [00:02:14] Jen Odess: Okay. I’ll take either way. It’s fine. [00:02:15] Vince Menzione: Yeah. Yeah. And might be a promotion. Let’s talk. Let’s talk about that. Let’s talk about you and your career journey and your mission. [00:02:22] Jen Odess: Yeah, so I’ve been at ServiceNow for five years. In fact, January will be like the five year anniversary and then it will be the beginning of my sixth year. [00:02:31] Jen Odess: Amazing. And I actually got hired originally to build out the initial partner enablement function. So it didn’t really exist five years ago. There was certainly enablement that happened to Sure. All individuals that were. Using, consuming, buying ServiceNow, working with ServiceNow. But the partner enablement function from pre to post-sale, that whole life cycle didn’t exist yet. [00:02:54] Jen Odess: So that was my initial job. I got hired to run partner enablement and it before. And how big [00:02:59] Vince Menzione: was your partner organization at that point? It must have been pretty small. [00:03:01] Jen Odess: It was actually not as small as you would think. Gosh, that’s a great question. You’re challenging my memory from five years ago. [00:03:08] Jen Odess: I know that we’re over 2,500 partners today and we add hundreds every year, so it had to have been in the low one thousands. Wow. Is where we were five years ago. But the maturity of the ecosystem is grossly larger today than it was then. I can imagine. So back then there was less than 30,000 individuals that were skilled on ServiceNow to sell or solution or deliver. [00:03:34] Jen Odess: Today there’s almost a hundred thousand. Wow. So yeah that’s like the maturity in the capability within the ecosystem. But before I start on my ServiceNow and my group vice president. Which is a great role, by the way. Group Vice President. Yeah. Partner Excellence group. I’m very proud of it. [00:03:49] Jen Odess: But but let me tell you what brought me here, please. So I actually came from a partner, but not in the ServiceNow ecosystem. Okay. I won’t name the partner, but let’s just say it’s a competitor, a competitive ecosystem. And I worked for a services shop that today I would refer to as multinational. [00:04:11] Jen Odess: Kind of a boutique darling, but with over 1,500 consultants, so Okay. A behemoth as well? Yeah. Privately held. And we were a force to be reckoned with, and it was really fun. I held so many roles. I was a customer success manager. I led the data science practice at one point. I ran global alliances and partnerships. [00:04:35] Jen Odess: At one point I was the chief of staff to the CEO at the time that company was acquired. Big global si. And and then at one point I even spun off for the big global SI and helped run a culture initiative to transform co corporate culture. Wow. Very inside the whole organization. Wow. That is very, yeah. [00:04:54] Jen Odess: Really interesting set of roles. And the whole reason I came to ServiceNow is by the time I was concluding that journey in that ecosystem on the services side, I felt like. I didn’t fully understand what it meant to be on the software product side. And I often felt like I approached friction or moments of frustration and heartache with resentment for the software company. [00:05:20] Jen Odess: Sure. Or maybe just a lack of empathy for what they must be going through as well. It always felt like I was on the kind of [00:05:26] Vince Menzione: negative you were on the other side of the table. Totally. [00:05:27] Jen Odess: Yeah. And, or maybe like the redheaded stepchild kind of a concept as a partner. And so I sought out to. Learn more, which is probably a big piece of my journey is just constant curiosity. [00:05:38] Jen Odess: Nice. And I thought I think the thing I’m missing is seeing what it means firsthand to be on the software product side. And that was what led me to a career at ServiceNow. Five years strong. Yeah. So [00:05:50] Vince Menzione: talk about partner experience for those who don’t know what that means. [00:05:53] Jen Odess: Yeah. Today my role is partner excellence, but it used to be partner experience. [00:05:58] Jen Odess: Okay. And so the don’t. Yeah, that’s normal to say both things. And they actually mean two very different things. [00:06:04] Vince Menzione: Yeah, I would say so. [00:06:05] Jen Odess: And we deliberately changed the title about a year ago. So today, partner Excellence is about really ensuring that we build a vibrant AI led ecosystem. And that’s from the whole life cycle of the partner, from the day they choose to be a partner and onboard, and hopefully to the day they’re just. [00:06:23] Jen Odess: Thriving and growing like crazy, and then across the whole life cycle of the customer pre to post sale. So it’s, we are almost like the underpinning and the infras infrastructure. Someone once said it’s like we’re the insurance policy of all global partnerships and channels. That’s how we operate across global partnerships and channels and service Now. [00:06:42] Vince Menzione: And you have a very intimate relationship with those partners. We’re gonna dive in on that as well. Yes. But let’s talk about this time like no other. I talk about tectonic shifts at all of our events. People that listen to our podcasts know we talk about the acceleration of transformation, and it’s happening so fast. [00:06:58] Vince Menzione: It was happening fast even during COVID. But then. I’ll call this date or time period, the November 20, 22 time period when Chat GPT launched. Oh yeah. And that really changed the world in many respects, right? Yeah. Microsoft had already leaned in with chat, GPT, Google, we talked to Google about this. [00:07:17] Vince Menzione: Even having them in the room was like, they were caught flatfooted in a way, and they had a lot of the technology and they didn’t lean in. But it feels like ServiceNow was one of the first, certainly on the ISV side of the house and refer to the term ISV. Loosely, because hyperscalers are ISVs as well. [00:07:34] Vince Menzione: They were early to lean in and have leaned it in such a way from a business application perspective that I believe we haven’t seen embracing and infusing AI into your platform. I was hoping we could dive in a little bit on ServiceNow from a. Kinda legacy, what the organization was and is today. [00:07:56] Vince Menzione: And then also this infusion of AI into the platform. If you don’t mind, [00:07:59] Jen Odess: I love this topic. Okay. And I feel like it’s such a privilege to talk about ServiceNow on this topic because we really are a leader in the category. I’ll almost rewind back to over 20 years ago when the company was founded. [00:08:11] Jen Odess: Today, fast forward, we are so much more than an IT ticketing company. We are, [00:08:16] Vince Menzione: but that was the legacy. That’s how I knew service now 20 years ago. [00:08:19] Jen Odess: And what a beautiful legacy. Yeah. But we have expanded immensely beyond that. And that’s the beautiful story to tell customers. That’s so fun. [00:08:28] Jen Odess: But what what I love is that. So 20 years ago, that was where we started. And today, do you know that over a billion workflows are put to work every single day for our customers? A billion [00:08:38] Vince Menzione: workflows, over a billion workflows. That’s crazy. [00:08:40] Jen Odess: And 87% of all implementations for ServiceNow were done by partnerships. [00:08:46] Jen Odess: And channels. That’s fantastic. So you think about those billion plus workflows daily, all because of our partner ecosystem. This is my small plug. I’m just very proud 80, proud 86%. [00:08:56] Vince Menzione: Did you hear that? Part’s 86%. [00:08:57] Jen Odess: Amazing. And so that’s like what we’re, that’s what we’re a leader in the category. We are a leader in workflows categorically. [00:09:05] Jen Odess: But then over a decade ago, we started investing in ai. We started building it right into our platform, and this becomes the next kind of notch on our belt, which is we are a unified platform. Nothing is bolted on, nothing is just apid in. Yeah, it is a unified platform. So all of that AI that for the past decade we’ve been building in into our platform. [00:09:28] Jen Odess: Just in our AI platform, which is now what we are calling it, the AI platform. [00:09:34] Vince Menzione: And I would say that unless you were a startup starting up from scratch today and building on an LLM, we were building in a way I don’t think any other organization’s gonna actually state that [00:09:45] Jen Odess: what’s actually why we call ourselves AI native. [00:09:47] Jen Odess: Yeah, beca for that exact reason. And that’s who we’re competing with a lot these days, is the truly AI native startups where they didn’t have, the 20 years. Previously that we had, but that’s what makes us so unique in the situation, is that unified AI platform, a single data model that can connect to anything. [00:10:07] Jen Odess: And then the workflow leader. And when you put all those things together, AI plus data, plus workflows and that’s where the magic happens. Yeah. Across the enterprise. It’s pretty cool. [00:10:17] Vince Menzione: That is very cool. And you start thinking about, and we start talking about agent as a, as an example. Let’s talk about this for a second. [00:10:23] Vince Menzione: You, when what is this bolt-on, we could use the terms co-pilot, we could use Ag Agent ai, but they are generally bolted onto an existing application today. So take us through the 10 years and how it has become a portion or a significant portion. Of ServiceNow. [00:10:41] Jen Odess: When say the question a little bit more. [00:10:43] Jen Odess: Like when you say it’s, yeah, when which examples have bolted on? [00:10:47] Vince Menzione: So exa, we, what we see today is the hyperscalers coming out with their own solution sets, right? They’re taking and they’re offering it up to their ecosystem to infuse it into their product and portfolio. To me, those that look like bolted on in many respects, unless it’s an AI need as a native organization, a startup organization. [00:11:07] Vince Menzione: They’re mostly taking and re-engineering or bolting onto their existing solutions. [00:11:12] Jen Odess: I follow. Yeah. Thank you for giving me a little more context. So I call this our any problem. It’s like one of the best problems to have we can connect into. Anything, any cloud, any ai, any platform, any system, any data, any workflow, and that’s where any hyperscaler, and that’s the part that makes it so incredible. [00:11:32] Jen Odess: So your word is bolt on, and I use the word any the, any problem. Yeah. We’ve got this beautiful kind of stack visual that just, it’s like it just one on top of the other. Any. Any, and no one else can really say that. I gotta see [00:11:45] Vince Menzione: that visual. Yeah. Yeah. So talk about this a little bit more. So you’re uniquely positioned. [00:11:52] Vince Menzione: Let’s talk about how you position, you talked about being AI native. What does that imply and what does that mean in terms of the evolution of the platform? From ticketing to workflows to the business applications? What are the type of applications Yeah. Markets, industries that you’re starting to see. [00:12:08] Jen Odess: So I’ll actually answer this with, taking on a small, maybe marketing or positioning journey. So there was a time when our tagline would be The World Works with ServiceNow. There was a time when it was, we put AI to work for people and today and it, I think it was around Knowledge 2025, this came out. [00:12:28] Jen Odess: It was the AI platform for business transformation. And I love to say to people, it sounds like a handful of. Cliche words that just got stacked together. The AI platform for business transformation. Yeah. We all know these words, so many companies use ’em, but it is such deliberate language and I love to explain why. [00:12:46] Jen Odess: So the first is the AI platform is calling out that we are an AI native platform. We are a unified platform. It’s a chance to say all that goodness I already shared with you. Yeah. And the business transformation is actually telling the story of no longer being a solution. Point or no longer being an individual product that does X. [00:13:06] Jen Odess: It’s about saying. The ServiceNow platform can go north to south and east to west across your entire enterprise. Okay. Up and down the entire tech stack. Any. And then east to west, it can cut across the enterprise, the C-suite, the buying centers, all into one unified AI platform. With one data model. [00:13:26] Jen Odess: I love it. And so I love that AI platform for business transformation actually has so much purpose. [00:13:32] Vince Menzione: It does. So you’re going across the stack, so you’re going all the way from the bottom layer, all the way up to the top from the ue. Ui. And then you’re going across the organization, right? You’re going across the C-suite, you’re going across all the business functions of an organization. [00:13:46] Vince Menzione: Correct. And so the workflows are going across each of those business functions? [00:13:49] Jen Odess: Correct. And then our AI control tower is sitting at the very top, governing over all of it. [00:13:53] Vince Menzione: I love the control tower. [00:13:54] Jen Odess: I know the governance, security risk protocol, managing all the agents interoperability. Yeah. [00:14:01] Vince Menzione: And then data at the very bottom right. [00:14:03] Vince Menzione: Controlling all those elements and the governance of the data and the right, the cleanliness of the data and so on. Yeah. That’s incredible. I we could probably talk about business applications. I know one, in fact, I’ve had a person sit in this, your chair from we’ll call it a large GSIA very significant GSI one of the top five. [00:14:21] Vince Menzione: And they took ServiceNow and they applied it to their business partnering function. And they used, and we, you probably don’t know about this one, but I know that that’s a, an example of taking it and applying it all across all the workflows, across all the geographies of the organization and taking a lot of the process that was all done manually. [00:14:40] Vince Menzione: That was stove pipe business processes that were all stove piped and removing the stove pipe and making for a fluid organizational flow. [00:14:47] Jen Odess: And I’ll bet you the end user didn’t even realize ServiceNow was the backend. That’s some of the greatest examples actually. [00:14:53] Vince Menzione: Yeah. Yeah. So Jen, we work with all the hyperscalers. [00:14:56] Vince Menzione: We have a very strong relationship with Microsoft. Goes back many years, my back to my days at Microsoft and we’ve had Google in the room. We have AWS now as well. We bring them all together because we believe that partners work with, need to work with all three. And I know that you have had an interesting transformation at ServiceNow around the hyperscalers. [00:15:16] Vince Menzione: I was hoping you could dive in a little deeper with us. [00:15:19] Jen Odess: Yeah. We are so proud of our relationships with the hyperscalers, so the same three, so it’s Microsoft Azure, Google Cloud, and AWS. And really it’s it’s a strategic 360 partnership and our goal is really to drive marketplace transactions. [00:15:34] Jen Odess: So ServiceNow selling in all of their marketplaces and then. Burn down of our customers cloud commits. I love it. It’s really a beautiful story for our customers and for the hyperscalers and for ServiceNow. And so we’ve, it’s brand, it’s a brand new announcement from late in the year 2025. Love it. And we’re really excited about it. [00:15:51] Vince Menzione: Yeah. And then we, and we get all of the marketplace leaders in the room. So we’ve worked with all of those people. And one of the key points about this is there is over a half a trillion dollars in durable cloud budgets with customers that [00:16:08] Vince Menzione: Already committed to, I know, so that tam available, a half a trillion dollars is available to customers to burn down and utilize your solutions and professional services with partners as well in terms of driving a complete solution. [00:16:21] Jen Odess: That’s exactly the motion we’re pushing is to go and leverage those cloud commits to get on ServiceNow and in some cases, maybe even take out other products to go with ServiceNow and actually end up funding the transition to ServiceNow. Yeah. Yeah. [00:16:37] Vince Menzione: So you serve thousands of customers today, thousands of customers. [00:16:42] Vince Menzione: I can’t even. Fathom the exact number, but you have this partner ecosystem that you described, and their reach is even more incredible, like hundreds of thousands. Yeah. So tell us a little bit more about how you think about that, and then how do you drive the partner ecosystem in the right way to drive this partner excellence that you described. [00:17:02] Jen Odess: Yeah, that’s a great question. So yeah, thousands of ServiceNow customers and we’re barely scratching the surface in comparison to our partners customers. So we have over 2,500 partners Wow. In our ecosystem. And today they cut across what I would call five routes to market. That partners can go to market with ServiceNow. [00:17:21] Jen Odess: Okay. The first is consulting and implementation. This will be your classic kind of consulting shop or GSI approach. The second is resell, just like it sounds. Yep. [00:17:30] Vince Menzione: Transactional. [00:17:31] Jen Odess: Yep. The third is managed service provider. [00:17:33] Vince Menzione: Okay. [00:17:34] Jen Odess: The fourth is what we call build, which is. The ISV, strategic Tech partner realm, and then the fifth is hyperscaler. [00:17:43] Jen Odess: Those are the five routes to market. So partners can choose to be in one or all or two. It doesn’t matter. It’s whichever one fits the kind of business they want to go drive. Nice. Where they’re. Expertise lies. And then we’ve got partners that show up globally, partners that show up multinational and partners that show up regionally and then partners that show up locally, in country and that’s it. [00:18:06] Jen Odess: And we really want a diverse set of partners capable of delivering where any of our customers are. So it’s important that we have that dynamic ecosystem where we really push them. We’re actually trying hard to balance this. Yeah, you would’ve heard it from many of your other partners. This direct versus indirect. [00:18:24] Jen Odess: Yes. Motion. For anyone listening that doesn’t know the difference, right? Direct is ServiceNow is selling direct to a customer, there might be a partner involved influencing that will implement. Yeah, likely but ServiceNow is really driving the sale versus indirect where the whole thing routes through the partner. [00:18:39] Jen Odess: Right? Which is your classic reseller or managed service provider and often a an ISV. And you know that balance is never gonna be perfect ’cause we’re not gonna commit to go all direct or all indirect. We’re gonna continue to sit in this space where we’re trying to find a healthy balance. [00:18:56] Jen Odess: So I find a lot of our time trying to figure out how do you set all those parties up for success? Yeah. The parties are the ServiceNow field sellers? And then you’ve also got the partnerships and channels, so the ecosystem, and then you’ve got the people in global partnerships and channels. So my broader organization, and we’re all trying to figure out how to work harmoniously together and it’s a lot of, it is my job to get us there. [00:19:19] Jen Odess: And so we use lots of things like incentives and benefits and we will put in place gated entry, really strategic gated entry. What does [00:19:29] Vince Menzione: gated entry mean? [00:19:30] Jen Odess: Yeah. What I mean is if you want to have a chance at being matched with a customer Yeah. For a very specific deal. Or it’s really one of three to get matched. [00:19:41] Jen Odess: ‘Cause you can never match one-to-one. It has to be three or more. Okay. We have good compliance rules in place. Yeah. But in order to even. Like surface to the top of the list to be matched. There’s a gated entry, which is, you’ve gotta have validated practices. Okay. Which is how, it’s these various ways, as you described, you quantify and qualify the partner’s capabilities. [00:20:00] Vince Menzione: Yeah. So you have to meet these qualifications. Yes. And you could be one of three to enter and be. Potentially matched, considered significant or Yes. Match for this deal? [00:20:08] Jen Odess: Yes, that’s exactly right. So we use, various things like that. And then we try to carve what I would call dance card space reseller in commercial, try to sit here and like carve by geo, by region, by country dance card space as well to help the partners really know exactly where they can unleash versus, hey, this is the process and the rules of engagement. To go and sell alongside the direct org sales organization [00:20:33] Vince Menzione: and you’re gonna have multiple partners in the same opportunities. [00:20:37] Vince Menzione: Absolutely not. Not necessarily competing with each other. There’s three competing each with each other, but also you’re gonna have other partners that provide different capabilities as well. You might have that have some that are just transac. Those are gonna be those channel or reseller partners. [00:20:52] Vince Menzione: You might have an MSP that’s actually delivering, or at least providing some type of managed service on top of the stack. Like supporting the customer. Yeah. And then you might have an SI GSI an integration partner that’s also doing the con the consulting work around getting the solution to meet with the customer’s requirements. [00:21:12] Vince Menzione: Would you say [00:21:13] Jen Odess: so? That’s exactly right. Yeah. And actually in. AI era, we’re seeing more of it than ever. And even on the smaller deals, maybe not the GSIs on the smaller deals, but we’re seeing multiple partners come in to serve up their specific expertise, which is actually a best practice. That’s [00:21:33] Vince Menzione: terrific. [00:21:33] Jen Odess: We don’t want. If you’ve got an area that’s a blind spot and you’re a partner, but that’s something your customer is buying from you, there’s no harm in saying let’s bring in an expert in that category to deliver that piece of the business. That’s right. And we’ll maybe shadow and watch alongside. [00:21:46] Jen Odess: So we’re seeing more and more of it. And I actually think like the world of. Partnerships and ecosystems. If I go back to like my previous ecosystem as well, it’s become so much more communal than ever before. Yes. This idea that we can share and be more open and maybe even commiserate over the things, gosh, I can’t believe we have the same frustrations or we have the same. [00:22:09] Jen Odess: Wow, that’s amazing. And you’re in this country. And I’m in this country. And so we’re seeing more and more coming together on deals which I really respect a lot. ’cause So one of the new facts we’ve just learned actually, Vince, is that. Of all the ai buying that customers are doing out there, they actually still want over 70% of it to be done by partners. [00:22:32] Vince Menzione: Yes. [00:22:33] Jen Odess: So even though it looks like it could be maybe set up easy configured, easy plug and play it. It to get, it’s not real ROI. You still need a partner with expertise in that industry or that domain, or in that location or in that language to come and bring the value to life. And we will certainly accelerate, help accelerate time to value with things that ServiceNow will do for our partners. [00:22:56] Jen Odess: But if over 70% is gonna go to partners and AI is so new, wouldn’t you want more than one partner Sometimes on a absolutely on a deal, at least while we’re all learning. I think we can keep ebbing and flowing [00:23:07] Vince Menzione: on this. We you, I dunno if Jay McBain, ’cause we’ve had him in the room here and he is a, he’s an analyst that does a lot of work around this topic. [00:23:14] Vince Menzione: And we talk about the seven seats at the table because there are, again, you need more you, first of all, you need to have your trusted, you need to have the organizations that you work with. And you also, in the world of ai, with all of the tectonic shifts, all the constant changing that’s going on right now, I need to make sure that I have the right. [00:23:31] Vince Menzione: People by my side that I can trust, they can help me deliver what I need to deliver. ’cause it might have changed from six months ago. And the technology is changing. Everything is changing so rapidly right now. So again, having all those right people I want to pick up on something ’cause we talked a little bit about MSPs and they’ve become a favorite topic of ours. [00:23:52] Vince Menzione: I have become acutely aware of the Ms P community recently. I kinda looked at them as well. There’s little small partners, but you’ve suggested this as well. They have regional expert, they have expertise in a specific area. And can be trusted, and maybe you’re integrating multiple solution sets for a customer. [00:24:11] Vince Menzione: But we’ve seen this MSP community become very vibrant lately, and I feel like they woke up to technology and to AI in such a big way. Can you comment on that? [00:24:20] Jen Odess: So we feel and see the same thing I’ve always valued what managed service providers bring to the table. It’s like that. [00:24:26] Jen Odess: Classic are you a transformation shop or are you a ta? The tail end or the run business shop? And so many partners are like we’re both, and I wanna be like, but are you? But now I feel like we finally are seeing the run business is so fruitful. So AI is innovating. All the time. [00:24:46] Jen Odess: We, we are innovating as a AI platform all the time. What used to be six month, every six months family releases of our software. Yeah. It became quarterly and now we’re practically seeing releases of new innovation every six to eight weeks. So why wouldn’t you want a managed service provider? Paying close attention to your whole instance on ServiceNow and taking into account all the latest innovation and building it into your existing instance, and then looking out for what new things you should be bringing in. [00:25:20] Jen Odess: So that’s the beauty of the, it’s almost partnerships, observing, and then suggesting how to keep. Doing better and more and better versus always jumping straight back to complete redesign and transformation. Yeah, and that’s one of the things I like about the MSPs in this space. [00:25:36] Vince Menzione: So let’s broaden out from this part of the conversation ’cause you’re giving specific guidance to the MSPs, but let’s think about this whole partner community. [00:25:43] Vince Menzione: And you’ve seen this transformation coming over to ServiceNow and even within ServiceNow these last five years. How do these organizations need to think differently? And how do they need to structure their services in this newent world? [00:25:58] Jen Odess: Great question. There’s really four things that I think they have to be thoughtful of. [00:26:02] Jen Odess: The first is maybe the most obvious they have to adopt AI as their own ways of doing work methodology. Delivery, whatever it is, because only through the, it’s not about taking out people in jobs, it’s about doing the job faster, right? It’s about getting the customer to value faster so that adoption of AI will make or break some partners. [00:26:24] Jen Odess: And our goal is that every partner comes on the other side of this AI journey, thriving and surviving. So we’re really pushing. This agenda. And maybe later I can talk to you a little bit more about this autonomous implementation concept. Please. ’cause I that will [00:26:37] Vince Menzione: resonate. So you’re saying they need to, we used to use the term eat their own dog food. [00:26:41] Vince Menzione: Now it’s drink your own champagne. Yeah. But they need to adopt it as well internally. [00:26:46] Jen Odess: Yeah. And I think whether they’re using, I hope they’re using ServiceNow as like a client, zero. To do some of that adoption. But there’s lots of other tools that are great AI tools that will make your job and your day-to-day life and the execution of that job easier. [00:26:59] Jen Odess: So we want them adopting all of that. The second is, we really need to see partners. Innovating on the ServiceNow platform. Yeah. And whether that’s building agents AI agents that go into the ServiceNow store, whether it’s building a really fantastic solution that we wanna joint jointly go to market with, or maybe it’s one of those embedded solutions you were commenting where the end user doesn’t even know that the backend, like a tax and audit solution that is actually just. [00:27:29] Jen Odess: The backend is all ServiceNow. Yeah. But that partner is going to market and selling it to all their customers. Exactly. So I think this co-innovation is gonna be a place that we will really win in market. The third is if a partner wants to stand out right now, they have to differentiate on paper too. [00:27:47] Jen Odess: It’s gotta like what does that mean? So if there’s 2,500 partners. And it’s not like we don’t walk around and just say, you should talk to this partner. Yeah. Or here’s my secret list. You should, we don’t do that. That’s not good business and it’s not compliant. So we have algorithms that take all the quantitative and qualitative data on our partners and they know all the data points ’cause it’s part of the partner program Nice. [00:28:10] Jen Odess: That they adhere to and then ranks them on status. And all those data points are what I’m referring to as on paper. You’ve gotta be differentiated. So whether or not you wanna be great at one thing or great across the whole thing, think about how all of those quantitative and qualitative data points are making you stand out, because that’s where those matches that I was referring to. [00:28:35] Jen Odess: Yes. That’s where that’s gonna come to life. And it’s skills, it’s capabilities. It’s deployments. So Proofpoint and deployments, customer success stories, csat, all the things. So [00:28:47] Vince Menzione: those are all the qualifi qualifiers for and more, but those are the types [00:28:49] Jen Odess: of qualifications. Yeah. [00:28:51] Vince Menzione: And then do your, does your sales organization do a match against that based on a customer’s requirements that they’re working with and who they work with and co-sell with? [00:29:00] Jen Odess: And I feel like you just lobbed me the greatest question. I didn’t even know you were gonna ask it, but I’m so glad you did. So today. Today there is something called a partner finder, which is which is nice, but it’s a little bit old school in a world of ai. Yeah. So you go to servicenow.com, you click partner from the top navigation, and then it says find a partner and you can literally type in the products you’re buying the country, you’re, that you’re headquartered out of. [00:29:26] Jen Odess: Whatever thing you’re looking for. And it will start to filter based on all those data points, the right partners, and you can actually click right there to be connected to a partner. So lead generation. Okay, interesting. But where we’re going is a agentic matching right in our CRM for the field. Oh. So those data points are gonna matter even more, and that’s where the gated. [00:29:48] Jen Odess: I say gated entry, which is probably too extreme, right? It’s really gated. If you wanna surface toward the top, there’s gated parameters to try to surface to the top, but those data points will feed the algorithm and it will genetically match right in our CRM for the field. Who are the best suited partners? [00:30:09] Jen Odess: Would you like to talk to them? [00:30:10] Vince Menzione: Okay. And so is it. Partner facing? Is it sales team facing [00:30:14] Jen Odess: Right now? It’s sales. It’ll, when it goes live, it will be sales team facing. Okay. But we have greater ambition for what partners can do with it. Yeah. Not just in the indirect motion, but also what partners may be able to do with it to interface with our field. [00:30:30] Jen Odess: The. [00:30:31] Vince Menzione: The, yeah the collaboration [00:30:33] Jen Odess: opportunity. Which is always a friction point that we’re working on [00:30:36] Vince Menzione: always because it’s very manual. It’s people intensive. Yeah. Partner development managers sitting on both sides of the equation and the interface between the sales organization and a partner organization is not always the. The easiest. So right. Automated, quite a bit of that. [00:30:49] Jen Odess: My boss is obsessed with the easy button, which I know is a phrase many of us in the US know from I think it’s an Office Depot, all these ways in which we can have easy button moments for the partner ecosystem is what we’re trying to focus on. [00:31:01] Jen Odess: I love the easy button. [00:31:02] Vince Menzione: Yeah. And I love your boss too. Yeah, he’s fabulous. Fabulous. So Michael and I go back like many years ago. You must have, [00:31:08] Jen Odess: yeah. You must have had paths crossing on numerous occasions. [00:31:12] Vince Menzione: Yeah we we worked together micro I’m going to hijack the session for a second here. [00:31:16] Vince Menzione: But when I first came to Microsoft, he was leading a, the se, a segment of the business, and he invited me to come to his event and interviewed me on stage at his event. [00:31:26] Jen Odess: No way. [00:31:26] Vince Menzione: And we got to know each other and yeah. So he was terrific. He was what a great find for, oh, he’s for service now. [00:31:32] Vince Menzione: He’s really [00:31:32] Jen Odess: has been a fantastic addition [00:31:34] Vince Menzione: to the global partnerships and channels team. And Michael, we have to have you on the podcast. Yes. Or cut down here in the studio at some point too with Jen and I. That’d be great. So this is terrific. We are getting it’s an incredible time. [00:31:44] Vince Menzione: It’s going so fast this time, 2022 was, seems like it was five, it feels like it was almost 10 years ago now. It wasn’t that we just started talking about it and you were implementing AI 10 years ago, but it wasn’t getting the attention that it’s getting today. And it really wasn’t until that moment that it really started to kick off in a way that everybody, yeah. It became pervasive overnight I would say. But now we’re starting 2026, like we’re at. This precipice of time and it’s continuing. I don’t even know what 2030 is gonna look like, right? So I’m a partner. [00:32:16] Vince Menzione: What are the one, two, or three things that I need to do now to win over and work with ServiceNow? [00:32:23] Jen Odess: One, two or three things? I’ll tell you the first thing. So today ServiceNow will end up hitting 500 million in annual contract value in our Now Assist, which is our AI products by the end of 2025, which is the fastest growing product in all of ServiceNow history. [00:32:37] Jen Odess: That’s one product that’s so there’s lots of SKUs. Yeah, but it is. It’s our AI product. Yeah. And it is, but yeah, because of all the various ways. [00:32:45] Vince Menzione: So half a billion dollars, [00:32:46] Jen Odess: half a billion by the end of 2025. And I think, someone’s gonna have to keep me honest here, but if memory serves me right, the first skews didn’t even launch until 2024. [00:32:54] Jen Odess: So we’re talking about wow, in a year it’s fast. Over 1,700 customers are live with our now assist products. Again, in a matter of, let’s call it over, a little over a year, 1,700 partners. So I think the first thing a partner needs to do is they’ve gotta get on this AI bandwagon, and they’ve gotta be selling and positioning AI use cases to their customers, because that’s the only way they’re gonna get. [00:33:20] Jen Odess: Experience and an opportunity to see what it feels like to deliver. So we have to do that. And I think you could sell a big use case like that big, we talked north, south, east, west, you could do that whole thing. Brilliant. But you could also start small. Go pick a single use case. Like a really simple example of something you wanna, some work you wanna drive productivity on. [00:33:41] Jen Odess: Yeah. And make sure you’ve got multiple stakeholders that love it and then go drive proving that use case. That’s what we’re telling a lot of partners. That’s the first thing. The second is they have got to build skills on AI and they have to keep up with it. And so we’re trying to really think about our broader learning and development team at ServiceNow is just next level. [00:34:00] Jen Odess: And they’re really re-imagining how to have more real time bite size. Training and enablement that will help individuals keep up with that pace of innovation. So individuals have got to get skilled. Yes. On AI today, of that a hundred thousand or so individuals in the ecosystem right now, about 35% of those individuals hold one or more AI credential. [00:34:25] Jen Odess: Again, that’s in a little over a year, which is the fastest growing skill development we’ve ever had, but it should be a hundred percent. Yeah. All of our goals should be that every account is being sold ai. ’cause that’s where the customer’s gonna get to value a ServiceNow is if they have the AI capabilities. [00:34:40] Jen Odess: And [00:34:41] Vince Menzione: how are you providing enablement and training? Is it all online? It’s, we have [00:34:44] Jen Odess: all sorts of ways of doing it. So that we have ServiceNow University, which is just a really robust, learning platform. Elba is our professor in residence. Very cool. Which is very cool. And they’re all content. [00:34:57] Jen Odess: Is free to partners. The training is free to partners that is on demand. Beyond that, partners can still get, instructor led training, whether that’s in person or virtual. And then my team offers enablement. That’s a little bit more, it’s like not formal training, it’s more like hands-on labs and experiences. [00:35:17] Jen Odess: We bring in lots of groups that sit around me that help and we very cool hands on with partners face-to-face. And do you do an annual event where you bring all these partners together? No, because we do we have three major milestones a year for partners. So the first is at sales kickoff, which is coming up the third week in January. [00:35:33] Jen Odess: And alongside sales kickoff is partner kickoff. Okay. And so we do a whole day of enabling them. So that’s your [00:35:39] Vince Menzione: partner kickoff? [00:35:40] Jen Odess: That’s partner kickoff. But of the, of all the partners in the ecosystem, it’s not like they can all make it. So we still also record and then live stream some of the content there. [00:35:49] Jen Odess: Then at Knowledge, there’s a whole partner track at Knowledge and same concept. Yeah, it’s like it’s all about customers and we wanna, build as much pipeline and wow as many customers as possible, but we also need to help our partners come along the journey. Then the third and final moment is in September, always, and it’s called our Global Partner Ecosystem Summit. [00:36:08] Jen Odess: We should have you, I’d love to join this next year. I love that. And it’s really, that’s the one time if sales kickoff is all about the sales motion in the field and knowledge is all about the customers and getting customers value. Global Partner Ecosystem Summit is only about the partners, what they need, why they need it, and what we’re doing to make their lives easier. [00:36:28] Jen Odess: I love it. Yeah. I’ll be there September. I love it. Dates yet set yet? I have to, it’s getting locked. I’ll get it to you. [00:36:34] Vince Menzione: Okay. All right. I’ll, we’ll be there. Okay. So you’ve been incredible. I just love having you. We could spend hours, honestly, and I want to have you back here. I’d love to, I have you back for a more meaningful conversation with the hyperscalers. [00:36:45] Vince Menzione: Talk to some of the partners that join us at Ultimate Partner events. We’ll find a way to do that, but I have this one question. It’s a favorite question of mine, and I love to ask all my guests this. Okay. You’re hosting a dinner party. And you could host a dinner party anywhere in the world. We could talk about great locations and where your favorite places are, and you can invite any three guests from the present or the past to this amazing dinner party. [00:37:11] Vince Menzione: We had one guest who wanted to do them in the future, like three people that hadn’t reached a future date. Whom would you invite Jen and why? [00:37:21] Jen Odess: Oh, first of all, you’re hitting home for me because I love to host dinner parties. I actually used to have a catering company. This is like one of those weird facts that, we didn’t talk about my pre services and ecosystem days, but I also had a catering company, so I love cooking and hosting dinner parties. [00:37:38] Jen Odess: So this is a great question. I feel like it’s a loaded question and I have to say my spouse. I love my husband dearly, but I have. To invite Lee to my dinner party. Okay. He’s in [00:37:47] Vince Menzione: Lee’s guest number one. Lee’s [00:37:49] Jen Odess: guest, number one. And the reason why is, first of all, I love him dearly, but he’s super interesting and he has such thought provoking topics to, to discuss and ways of viewing the world. [00:38:00] Jen Odess: He’s actually in security tech, so it’s like a tangential space, but not the same. [00:38:05] Vince Menzione: Yeah. But an important space right now, especially. Yeah. And [00:38:07] Jen Odess: he, yeah. And he’s, he’s just a delight to be around. So he’d be number one. Number two would be Frank Lloyd Wright. [00:38:15] Vince Menzione: Frank. Lloyd Wright. [00:38:17] Jen Odess: Yeah. I am an architecture and design junkie. [00:38:21] Jen Odess: Maybe I don’t do any of it myself, though. I dabble with friends that do it, and I try to apply it to my home life when I can. And Frank Lloyd Wright sort of embodies some of my favorite. Components of any kind of environment that you are experiencing, whether it’s a home or it’s an office building or it’s an outdoor space. [00:38:39] Jen Odess: I love the idea of minimalism and simplicity. I love the idea of monochromatic colors. I love the idea of spaces that can be used for multipurpose. And then I love the idea of the outside being in and the inside being out. I love it. So I would like love to pick his brain on some of his, how he came up with some of his ideas. [00:38:59] Jen Odess: Fascinating for some of his greatest. Yeah. Designs. Okay. That’s number two. Number three, I think it would be Pharrell Williams. Really? Yeah, I, Pharrell Williams. Yeah. I love fashion music and all things creativity. He’s got that, Annie’s philanthropic. He’s just yeah. The whole package of a good person. [00:39:26] Jen Odess: That’s super interesting and I very cool. I would love to pick his brain on what it was like to be behind the scenes on some of the fashion lines he’s collaborated with on some of his music collabs he’s had, and then just some of the work he’s doing around philanthropy. I would. I could just spend all night probably listening to him. [00:39:43] Jen Odess: This would be a [00:39:44] Vince Menzione: really cool conversation night. [00:39:45] Jen Odess: Don’t you wanna come to my dinner? Was gonna say, I’m sorry I didn’t invite you to identify. No [00:39:49] Vince Menzione: I was, can I bring dessert? [00:39:50] Jen Odess: Yeah. I come [00:39:50] Vince Menzione: for dessert. I, but it can’t, [00:39:51] Jen Odess: it has to be like a chocolate dessert. It’s gotta have [00:39:54] Vince Menzione: I love chocolate dessert. [00:39:55] Vince Menzione: Okay, great. So it would not be a problem for me, Jen. This is terrific. You have been absolutely amazing. So great to have you come here. Yeah. Such a busy time of year to have you make the trip here to Boca. We will have you back in the studio. I promise that I’ll have you back on stage. Stage. [00:40:10] Jen Odess: This is beautiful. [00:40:10] Jen Odess: Look at it. Yeah. This is [00:40:11] Vince Menzione: beautiful. And we transformed this into, to a room, basically a conference room. And then we also have our ultimate partner events. I would love to come, we would love to have you join us. Like I said, ServiceNow is such an impactful time. Your leadership in this segment market, and I wouldn’t say segment across all of AI in terms of all the use cases of AI is just so meaningful, especially for within the enterprise. [00:40:33] Vince Menzione: Yeah. Right now. So just really a jogger nut right now within the industry. So great to have you and have ServiceNow join us. So Jen, thank you so much for joining us. [00:40:42] Jen Odess: Thanks Vince. Appreciate the time. It’s a pleasure to be here. [00:40:44] Vince Menzione: Thank you very much. Thanks for tuning into this episode of Ultimate Eye to Partnering. [00:40:50] Vince Menzione: We’re bringing these episodes to you to help you level up your strategy. If you haven’t yet, now’s the time to take action and think about joining our community. We created a unique place, UPX or Ultimate partner experience. It’s more than a community. It’s your competitive edge with insider insights, real-time education, and direct access to people who are driving the ecosystem forward. [00:41:16] Vince Menzione: UPX helps you get results. And we’re just getting started as we’re taking this studio. And we’ll be hosting live stream and digital events here, including our January live stream, the Boca Winter Retreat, and more to come. So visit our website, the ultimate partner.com to learn more and join us. Now’s the time to take your partnerships to the next level.
Jim sits down with Sean Luke (Partner at SPMB Executive Search) to talk about the art of hiring senior engineering and product leaders—especially now that every job description on Earth has "AI" duct-taped to it. We get into why sticking with one great search firm beats "random recruiter roulette," why tech interviewing is tough (spoiler: engineers aren't always born interviewers), and the eternal tension between the two key roles - CTO (big brain science/vision) and VP Engineering (keep the trains running, preferably on the tracks). Then it's on to the AI gold rush: what a normal Head of Engineering should actually be doing with AI (hint: practical stuff like code review, QA, automation), why "Head of AI" is usually a totally separate job, and why "10 years of LLM experience" belongs in the same bin as Web3 buzzword soup. We also cover who's moving jobs right now, why PE can feel like a saner bet than venture (less "moonshot," more "actual exit"), and what candidates must be able to explain: what you did, and how it moved the business—numbers included. Plus: a few recruiting war stories, including the kind you can't make up and the kind that makes you grateful for a boring Tuesday.
Algorithms and automations have been buds for a decade plus.
Capabilities? Through the roof? Usage? Ground floor.Claude Agent Skills might be one of the most useful features of any front-end LLM. Yet....it's crickets in terms of chat around it. For this 'AI at Work on Wednesday' episode, we're breaking it down for beginners and will have you spinning up your own Claude Agent Skills in no time. Claude Skills: How to build Custom Agentic Abilities for beginners -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion:Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Claude Skills Agentic Features OverviewDifferences: Claude Skills vs. GPTs vs. GEMSModular Agentic Workflow File StructureStep-by-Step Guide: Building Claude SkillsClaude Skills YAML/Markdown Setup ProcessTesting and Validating Custom Claude SkillsAdvanced Capabilities: Executable Code & Sub-AgentsCommon Troubleshooting for Claude Skills CreationTimestamps:00:00 "Claude Skill Library Unveiled"06:27 "Claude Skills Explained"07:29 Custom GPTs and Gems Explained11:18 Claude Skills vs Projects17:31 "Refining Skill Triggers Effectively"20:17 "Beginner Cloud Skills Best Practices"23:39 "Preferring GPT and Memory Tools"25:54 "Saving Skill File Properly"28:09 Creating Skills on Claude33:43 "Creating AI News Searcher"35:36 Claude Skills Now Available37:39 "Optimizing Claude for Knowledge Tasks"41:05 "Skill Builder Library Access"Keywords:Claude skills, Claude agent skills, custom agentic abilities, large language model, agentic workflows, specialized tasks, coding capabilities, file creation, executable code, skills library, skill builder, skill creator, markdown file, skill.md, folder structure, YAML front matter, composable skills, modular instructions, automation, prompt engineering, skill triggers, skill testing, advanced features, API skill versioning, governance and efficiency,Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Vibe coding is dead simple. Head to AI.Studio/build to create your first app. Vibe coding is dead simple. Head to AI.Studio/build to create your first app.
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