Podcasts about agentic

Jordi Visser is a veteran macro investor with 30+ years of experience and the author of the VisserLabs Substack. In this conversation, we break down the AI trade and why it's far from over, the memory shortage driving Micron, which AI models are winning and losing, how agentic loops are replacing white collar jobs, why bitcoin and the debasement trade are selling off — and what comes next.=====================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~9% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at figure.com/disclosures/=====================Uphold is the easiest way to buy and sell crypto unlike any other platform allowing you to trade in just one step between any supported asset. Check them out at https://www.uphold.com/pomp/ This video includes a paid sponsorship with Uphold. I'm compensated by Uphold for promoting its products and services and may receive commissions from referrals. Terms apply. Not available in all jurisdictions. Digital assets are risky and may result in the total loss of your capital.=====================Bitget (https://bitget.com/promotion/futures-tradfi?channelCode=regd&vipCode=nkew) is the world's largest Universal Exchange (UEX) (https://bitget.com/promotion/futures-tradfi?channelCode=regd&vipCode=nkew), serving over 125 million users with access to over 2M+ crypto tokens, and TradFi markets such as 100+ tokenized stocks, ETFs, commodities, FX and precious metal like Gold. At launch, users can trade 79 instruments with USDT directly with the App. Users can also enjoy high liquidity and low slippage, while trading these assets with up to 500x leverage. For more information on Bitget TradFi, visit this article (https://bitget.com/support/articles/12560603846859). For more information, visit: Website (https://bitget.com/) | Twitter (https://x.com/bitget) | Telegram (https://t.me/BitgetENOfficial) | LinkedIn (https://linkedin.com/company/bitget-global/) | Discord (https://discord.com/invite/bitget)For media inquiries, please contact: media@bitget.com=====================Arch Public is an agentic trading platform that automates the buying and selling of your preferred crypto strategies. Sign up today at https://www.archpublic.com and start your automated trading strategy for free. No catch. No hidden fees. Just smarter trading.=====================0:00 - Intro1:13 - Is the AI trade over?4:11 - Micron, memory shortage, & the AI supply chain9:54 - Intel, TSMC & the AI arms race13:11 - Claude vs. ChatGPT vs. Gemini24:26 - Agentic loops & job displacement29:50 - What is the impact of regulation?34:55 - Stripe, solopreneurs & AI commerce38:12 - Bitcoin, gold & the debasement selloff43:11 - Tokenization & bitcoin's third wave45:04 - Jordi's upcoming video

AJ McGowan, VP of Research and Development at Reynolds & Reynolds. He breaks down why fragmented software platforms are quietly limiting what AI can see and do, uses a service drive scenario to show how a fully connected system could surface a high-value trade opportunity in real time, and explains why Reynolds is investing in its own hardware infrastructure to make that scale. Topics: 03:25 Why Auto AI Is Different. 06:45 Real AI Vs. Gimmicks. 08:45 Why Reynolds Is Buying Hardware. 13:15 The Bloomberg Terminal For Used Cars. 17:30 What Ray Actually Does. 22:50 Where Dealers Still Find An Edge. 28:35 Why Consolidation Is Now Critical. This episode is brought to you by: 1. Matador AI - Most dealerships are losing leads in the follow-up. Matador AI fixes that. It's not generic automation. It's dealership-trained AI, built on millions of real conversations and optimized around what converts. In a thin-margin business, every conversation matters. Book your demo today and get your first month free @ here. 2. Zurich - Zurich Advisor IQ is Zurich's AI-driven training and coaching platform built to help F&I teams perform more consistently and sell more effectively — using real transaction data, not theory. By analyzing actual F&I transactions, Zurich Advisor IQ helps identify behaviors and trends influencing results, delivers actionable insights and roleplay scenarios, and gives dealership leaders visibility into performance across managers, stores and rooftops. Connect with your Zurich representative to request a demo and see how Zurich Advisor IQ can help turn F&I insight into stronger dealership performance. Discover more @ here. 3. Reynolds and Reynolds - Turn cars faster and increase profit with AutoVision, an end-to-end inventory management suite that optimizes every step of the used vehicle lifecycle. From acquisition to sale, AutoVision gives you a clear way to manage inventory. Visit  AutoVision.com for more information. Check out Car Dealership Guy's stuff: For dealers: CDG Circles ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://cdgcircles.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Industry job board ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://jobs.dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Dealership recruiting ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgrecruiting.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Fix your dealership's social media ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.trynomad.co⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Request to be a podcast guest ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgguest.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ For industry vendors: Advertise with Car Dealership Guy ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgpartner.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Industry job board ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://jobs.dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Request to be a podcast guest ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.cdgguest.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Car Dealership Guy Socials: X ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠x.com/GuyDealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠instagram.com/cardealershipguy/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠tiktok.com/@guydealership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/company/cardealershipguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Threads ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠threads.net/@cardealershipguy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠facebook.com/profile.php?id=100077402857683⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Everything else ➤ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠dealershipguy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Everyone is racing to the same place chasing a limited set of buyers—how will your “AI for BI” product stand out? I've been seeing teams heavily invest in copilots, agents, semantic layers, governance frameworks, and increasingly sophisticated models, yet many still hear the same feedback from sales prospects: “We may just build this ourselves?" Or they don't hear it, but suspect the customer is doing just that.  Whether they actually can DIY the solution is the wrong question. The bigger question is *why they believe they can.* Your product may have a genuine competitive advantage, but your real challenge is that this advantage isn't obvious to buyers. The moat exists, but it is invisible. What makes this relevant is that many capabilities once considered differentiators are rapidly becoming normalized. AI copilots, agentic analytics, governed data, semantic layers, and broad integrations now appear across nearly every platform in the category. As AI accelerates development, sophisticated engineering alone becomes harder to defend as a lasting advantage. So what actually creates a durable moat if the engineering and product seems easy to copy? I explore four areas: proprietary data, trusted relationships, and products that accumulate institutional knowledge remain difficult to replicate. And finally, user experience itself as a strategy. As users increasingly access your intelligence through AI agents rather than dashboards, their experience may become the moat that competitors can't copy. Highlights / Skip to: AI for BI and analytics products is facing a race to commoditization (2:09) Common moats that everyone is using right now and why they fail (3:28) Proprietary data as a moat (9:29) Being embedded in your community as a moat (11:14) Compounding institutional knowledge as a moat (15:22) UX design asa moat even when there is little/no UI to see (18:36) Find the baseline for customer experience to build into later strategies (25:11) Actionable questions to ask your team to move forward on finding your competitive differentiation as a B2B analytics product (28:02)   Links CED: A UX Framework for Designing Analytics Tools That Drive Decision Making

Most leaders think about AI as a tool to analyze data or assist with tasks. But what happens when your AI becomes an autonomous agent, not just providing insights but actively orchestrating complex processes on its own?Today, we are at PegaWorld 2026 at the MGM Grand in Las Vegas, and, we're going to talk about moving AI from a theoretical concept to a practical, value-driving reality. Specifically, we'll explore:- The transition from predictive AI to agentic AI, and what that means for orchestrating complex customer journeys.- The architectural and data foundations required to successfully deploy autonomous AI agents at an enterprise scale.- How this approach enables a new level of proactive, personalized engagement that improves outcomes and drives business value.To help me discuss this topic, I'd like to welcome Richard Rutkowski, Director of Product and Technology at enGen.About Richard RutkowskiRichard Rutkowski is Director of Product and Technology at enGen, where he leads the development of clinical care management solutions designed to improve patient outcomes, streamline administrative processes, and reduce healthcare costs. With a background in computer systems technology and expertise in product strategy, agile methodologies, and technology leadership, Richard works across cross-functional teams to develop and scale innovative solutions that address complex healthcare challenges. enGen is the technology, operations, and services company of Highmark Health, one of the largest integrated health organizations in the United States. The company provides technology, data, and business solutions that help health plans, providers, and care teams modernize operations, improve efficiency, and enhance healthcare experiences. enGen focuses on leveraging emerging technologies, including AI and automation, to simplify complex healthcare processes and drive better outcomes across the healthcare ecosystem.Richard Rutkowski on LinkedIn: https://www.linkedin.com/in/richard-rutkowski-35063410a/---------- Resources ----------enGen: https://goengen.com/Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn more at Pega.comWe're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fDon't miss We Make Future - the International Festival of Innovation in AI, Tech, and Digital Marketing, June 24-26 in Bologna. Learn more: https://aglbrnd.co/r/c80991afff416bb2The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716baCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.comThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

Is the open model GLM-5.2 really Opus 4.8 level?

This week on Trending in Ed, host Mike Palmer is joined by Trending in Ed all-star Beth Rudden, CEO of Bast AI. From her roots digging in the dirt as an archaeologist to managing a $34 billion division as the Chief Data Officer of IBM Managed Services, Beth brings a deeply grounded, technical perspective to the artificial intelligence conversation. In this wide-ranging and insightful conversation, Mike and Beth skip the typical AI hype to explore what it actually takes to build explainable, trustworthy technology. Beth shares how Bast AI acts as an LLM-agnostic explainability layer—using a unique drinking chocolate analogy to demonstrate how they verify AI data rather than letting models hallucinate plausible narratives. They explore the practical application of using small language models (SLMs) for data enrichment, highlighted by Bast AI's meaningful work with Craig Hospital to translate complex neuro-spine outpatient procedures into accessible languages and analogies. KEY INSIGHTS: • Inverting the Chatbot Approach: Why defining what an AI can talk about is far more effective than building restrictive guardrails. • The Myth of "Human in the Loop": How shifting accountability to overworked humans can become a form of liability laundering. • Microservices vs. Agentic Harnesses: Looking at the risks of natural language agentic systems like Claude Code versus discrete, self-healing tasks. • Cognitive Offloading & Math Education: Why future technical skills should prioritize differential equations and the diversity prediction theorem over simple calculation. • Pattern Recognition vs. Choice: Defining true intelligence through the ability to choose wisely, rather than just matching mathematical patterns. They also cross paths with the Cynefin framework, explain how the human brain conserves energy by only holding two paradoxes at once, and unpack the cultural shifts reshaping modern engineering ethics. Stay ahead of the curve in education and technology! Please like and share this episode with your network, and follow the podcast on Apple Podcasts, Spotify, or your favorite player so you never miss an episode like this one. LINKS: Learn more about Bast AI: https://www.bast.ai Subscribe to Beth's Substack: https://bethrudden.substack.com TIMESTAMPS: 00:00 - Introduction and welcoming Beth Rudden back to the show 01:00 - The drinking chocolate analogy for Explainable AI 03:00 - Beth's lightning-round background: Archaeology to Chief Data Officer at IBM 05:00 - Getting "catfished by AI" and verifying facts with databases 07:00 - Mike on Gemini, RAG applications, and checking AI confabulation 09:00 - Enriched data and Small Language Models (SLMs) at Craig Hospital 12:00 - Epistemic security and inverting conversational technology 14:30 - Liability laundering and the illusion of "human in the loop" 15:30 - Agentic harnesses vs. self-healing microservices 20:00 - Understanding as labor and Conrad Wolfram's three-step math process 22:30 - Future human skills: Differential equations and jelly bean statistics 26:30 - Pattern recognition vs. true intelligence as the ability to choose 29:30 - Neurosymbolic systems and subjectivity in data science 34:30 - Shunting energy: The Cynefin framework and holding paradoxes 38:30 - Healthcare AI scribes and doctor burnout 44:30 - Trust architectures and building tech for the Maintenance Era 47:30 - Cultural devastation and the teleological suspension of ethics 49:00 - Final thoughts and wrapping up with Beth Rudden

The e-commerce world didn't get “easy” overnight. Our guest Jason Greenwood has lived every phase of it, from the days when getting a website online was hard, payments were clunky, and technical SEO was the only way to get discovered, to today's world where a storefront can launch fast and customers expect everything to work instantly on a phone. That long view makes his take on digital transformation and the future of commerce feel grounded, not hype-driven.We dig into the biggest platform shifts Jason has seen, then zoom in on the opportunity most people still underestimate: B2B e-commerce for manufacturers and distributors. He explains why relationship selling and sales compensation models slowed adoption, why so many teams still burn time on low-value admin work, and why the B2B digital commerce market remains wide open compared to saturated retail e-commerce. If you care about modernizing operations, improving customer experience, or scaling revenue, this conversation connects the strategy to the messy reality inside real companies.Then we go deep on AI in e-commerce, especially agentic AI that can break work into subtasks, run parallel workflows, and ship real outputs fast. Jason shares how he uses AI as a thought partner and execution partner, the prompts he repeats to find blind spots, and the non-negotiable habit of demanding citations and reviewing deliverables so hallucinations do not sneak into client work. If you're trying to stay relevant as automation accelerates, this is a practical roadmap.Subscribe for more conversations like this, share the episode with an operator who needs it, and leave a review with one AI workflow you're ready to automate next.How to connect with Jason Greenwood?LinkedIn: https://www.linkedin.com/in/jason-greenwood-digital-expert/ Website: https://www.greenwoodconsulting.net/ podcast: https://www.greenwoodconsulting.net/podcastYouTube: https://www.youtube.com/user/jagnz1/videosReady to scale your Amazon business? Click here to book a strategy call. https://calendly.com/firingtheman/amazon Support the show

Yaakov Zar is the founder and CEO of Lev, a software platform built to modernize the workflow of commercial real estate professionals. Yaakov started Lev after experiencing firsthand how broken the CRE financing process was, watching a $4 million loan take six months to close. What began as a tech-enabled brokerage has evolved into a purpose-built agentic workflow platform helping lenders, brokers, and investors manage deals, ingest unstructured data, and move faster. Yaakov is based in New York City.(02:26) Bottom Up vs Top Down(04:31) Slack Origin Tangent(05:59) MetaProp Skills Library(09:43) What Is Defensible AI(11:12) MCP & Rapid Change(12:41) Pilots Everywhere & Demo Fatigue(17:34) Same Workflow, Turbocharged(19:34) Real Estate's Move 37 Moment(22:04) Why Winning Is Hard to Define(26:07) Lev Agentic Workflows(29:14) Leapfrogging Past Salesforce(31:43) Data Quality Pushback(33:49) Ingesting Email Into CRM(35:54) Selling Software to CRE(39:06) Overhyped AI and Security Risks(42:50) Collaboration Superpower: Steve Jobs

Twilio (TWLO) CEO Khozema Shipchandler discusses the company's shift beyond messaging into a broader engagement platform built for agentic A.I. He highlights voice A.I. growth and Twilio's ability to deliver ROI for customers like Lyft (LYFT) and IBM (IBM). Shipchandler also outlines Twilio's neutral platform strategy and path to durable profitability.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe 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

Revenue cycle doesn't just need more reporting; it needs smarter systems that can prevent problems before they happen.In this episode of Straight Outta Health IT, Jeff Hatfield, Co-Founder and CEO of Four Points Health, talks about how Agentic AI and intelligent automation are reshaping revenue cycle management for hospitals. He explains why denials, write-offs, payer complexity, and manual rework continue to drain financial resources and create unnecessary administrative burden. Drawing from both personal experience and years of working with hospital leaders, Jeff shares why healthcare needs to move beyond retrospective dashboards and toward real-time action.Jeff introduces the Agentic Claims Integrity System (ACIS), built to help hospitals shift from reactive denial management to proactive denial prevention. Rather than simply flagging problems after the fact, ACIS identifies issues upstream, intervenes before claims are submitted, and helps teams reduce avoidable denials and write-offs. He also explains how closed-loop systems can track payer behavior, validate whether fixes worked, and continuously improve performance over time.He also explores the human side of automation, emphasizing that AI should not replace healthcare teams but give them leverage. By reducing repetitive work, improving productivity, and speeding up reimbursement, intelligent automation can help staff focus on higher-value tasks while strengthening hospital financial performance. Hatfield also highlights the importance of making this technology accessible to rural and community hospitals, so AI does not widen existing gaps in healthcare.Tune in to hear how Agentic AI can help hospitals reduce denials, improve cash flow, ease staff burnout, and build a more sustainable future for healthcare operations!ResourcesConnect with Jeff Hatfield on LinkedIn here.Follow Four Points Health on LinkedIn here and visit the website here.

With 250,000 customers and $1.2B in revenue, Monday.com's CPTO explains why they threw out their roadmap and rebuilt everything around agentic AI.Topics Include:Daniel Lereya joined Monday.com when it had just 30 people and five engineers.He grew the R&D org from five engineers to roughly 900 over a decade.Three years ago Daniel became Monday.com's first ever CPTO.Monday.com initially approached AI by adding small features across the product.They called this early phase "sprinkling AI dust" — helpful but not transformative.A pivotal board meeting made Daniel realise AI hadn't changed Monday's core value.Monday.com decided to rethink its mission from first principles around AI.The new mission: AI agents that actually execute work, not just manage it.AI gives businesses an "infinite workforce" regardless of company size.Agents can now do hyper-personalised work at a scale humans simply cannot.Monday's platform puts agents at the centre, replacing boards and dashboards.Shared context and human-in-the-loop handoffs make their agents uniquely powerful.Monday ran an "AI month" — pausing the entire 900-person builder org to transform.The month rebuilt team mindset and energy, reminding staff of early startup days.Monday also ran an "agentic week" where every department built their own agents.Finance built agents to automatically match incoming payments to customer accounts.Scaling AI adoption internally remains the biggest challenge across businesses today.Monday introduced "effective AI" — balancing capability with cost efficiency.They acquired voice AI startup One AI to add specialised model capabilities.On pricing, Monday shifted to a hybrid seats-plus-AI-credits consumption model.Participants:Daniel Lereya – Chief Product and Technology Officer, Monday.comKamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web ServicesJohan Broman – EMEA ISV Head of Solutions Architecture, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Google released updated guidance for optimizing websites in both traditional and AI-powered search. The message is clear: SEO hasn't changed as much as you think. In this episode, Meredith's Husband walks through the new guidance from Google's and explains what it means for you as a website owner.Get the full article with links discussed in the episode:https://www.meredithshusband.com/blog/google-ai-seo-guideTimestamps [0:00] Introduction [0:42] Why AI bots still use Google for search [3:42] AI plus SEO crash course update [5:56] Walking through Google's new guidance document [6:45] Is SEO still relevant for AI search? [9:00] Creating unique, helpful, people-first content [13:31] Technical structure that supports visibility [15:29] Myth busting: chunking, LLMS.txt, and more [18:22] Agentic search experiences [19:00] Summary: Four Key Points from Google --Submit questions for future episodeshttps://www.meredithshusband.com/podcast

The Internet Report podcast examines lessons from deep space operations that can help developers build more resilient agentic AI systems that are capable of managing intermittent connectivity and stale data.   ———    CHAPTERS  00:54 Making Decisions Autonomously 03:08 How Intermittent Connectivity Impacts Agentic AI 07:11 Existing Protocols for Extreme Environments 12:27 Broader Implications Beyond Extreme Environments 15:17 What Getting It Right Looks Like 17:09 Learning Points for Autonomous Road Vehicles   ———    
  For additional insights, check out The Internet Outage Survival Kit: https://www.thousandeyes.com/resources/the-internet-outage-survival-kit?utm_source=soundcloud&utm_medium=referral&utm_campaign=fy26q4_internetreport_q4fy26ep136_podcast    ———    Want to get in touch?    If you have questions, feedback, or guests you would like to see featured on the show, send us a note at InternetReport@thousandeyes.com. Or follow us on LinkedIn or X.   ———    ABOUT THE INTERNET REPORT  This is The Internet Report, a podcast uncovering what's working and what's breaking on the Internet—and why.     Tune in to hear ThousandEyes' Internet experts dig into some of the most interesting outage events from the past couple weeks, discussing what went awry—was it the Internet, or an application issue?    Plus, learn about the latest trends in ISP outages, cloud network outages, collaboration network outages, and more.    Catch all the episodes on your favorite podcast platform:      - Apple Podcasts: https://podcasts.apple.com/us/podcast/the-internet-report/id1506984526      - Spotify: https://open.spotify.com/show/5ADFvqAtgsbYwk4JiZFqHQ?si=00e9c4b53aff4d08&nd=1&dlsi=eab65c9ea39d4773      - SoundCloud: https://soundcloud.com/ciscopodcastnetwork/sets/the-internet-report      - YouTube: https://www.youtube.com/@theinternetreport_official 

In this session from DX Annual, Christopher Sanson, Product Lead, AI Developer Experience, and Madison Capps, Engineering Manager, Infrastructure at Airbnb, challenge some of the most common assumptions about AI. Is AI primarily about replacing humans? Do organizations need mandates to drive adoption? And are the productivity gains really as small as some studies suggest?Using examples from Airbnb's own AI journey, they share how the company achieved widespread adoption of agentic AI through AirChat, community enablement, and internal tooling rather than top-down mandates. They also discuss the impact AI is having on developer productivity, how non-developers are increasingly using coding tools, and how teams are rethinking product development in an AI-first world.Finally, Madison takes a deeper look at the infrastructure powering Airbnb's AI strategy, including AirChat CLI, the AirChat SDK, and AirChat Remote, along with the company's vision for asynchronous agent workflows and the next generation of AI-powered development.Where to find Christopher Sanson:• LinkedIn: https://www.linkedin.com/in/christophersanson Where to find Madison Capps:• LinkedIn: https://www.linkedin.com/in/madison-capps-66950625In this episode, we cover:(00:00) Intro(01:37) Myth #1: AI is about replacing humans(03:22) Myth #2: You need mandates to drive AI adoption(05:21) AirChat, agentic AI, and Airbnb's adoption strategy(08:07) Myth #3: AI has little impact on productivity(09:33) Airbnb's increase in coding time and PR throughput(14:20) Myth #4: AI coding tools are just for coders(15:39) How non-developers are using coding tools(17:24) Rethinking product development in an AI-first world(20:30) Myth #5: Vibe coding isn't coding(22:16) Unsolved problems in agentic AI tooling and how Airbnb is addressing them(26:30) Airbnb's overall AI philosophy in practice(29:15) Using agentic AI to accelerate code migrations(30:18) AirChat SDK: How Airbnb enables teams to build AI-powered applications(33:17) AirChat Remote and asynchronous agent workflows(36:07) Predictions for what's nextReferenced:• ⁠Airbnb• Steve Jobs's Bicycles for the Mind • Jennifer St Pierre • Justin Reock• AI-generated merged code holds steady at ~30%• Andrej Karpathy's post on X

On today's show Ben and Andrew begin with a hydration break take as the World Cup continues before turning to the latest on Anthropic's export control saga, what the Trump administration may not understand about AI cybersecurity, and what Anthropic still doesn't understand about dealing with the government. From there: Fables differentiation, the dangers of ringfencing frontier AI within U.S. borders, and how open source Chinese AI may affect the marketplace. From there: Why Ben gives Fox the benefit of the doubt after its Roku purchase this week, whether Siri AI will nuke ChatGPT's market, Noam Shazeer joins OpenAI, what e-commerce will and won't be automated, and whether autonomous driving can scale on ICE vehicles.

Co-founders Dr. Salman Avestimehr and Dr. Aiden He join the podcast to discuss their new "agentic" company, Teamily AI. They dive into how their platform is disrupting the social landscape by weaving multi-agent AI into group chats, enabling groups, friends, and families to interact with virtual friends, essentially creating a collaborative environment where AI acts as a participant that anticipates needs and remembers the full context of a conversation.This conversation explores the core value proposition of an AI-first social platform—not just making an individual superhuman, but enabling a collective of human and AI agents to do "fascinating things together." The founders detail their technology, which is built on deep expertise in distributed machine learning and multi-agent systems, and their long-term vision to IPO and evolve the very nature of social networks by bridging the gap between human and artificial intelligence.In the news segment, Charlie Fink and Rony Abovitz unpack the week's biggest AI stories: Ben Affleck selling his stealth AI film company, Interpositive, to Netflix; Anthropic's Claude briefly dethroning OpenAI's ChatGPT in the app store; and a deep dive into Jack Dorsey's company Block cutting 4,000 employees. The hosts also discuss the social fallout of AI acceleration, particularly the counter-movement seeking tactile, real-world connection and the economic risk of displacing white-collar data analysts.Key Moments00:03:00 – App Store War: Discussing Anthropic's Claude topping the app charts and why the US Department of Defense will use the best AI system regardless of corporate objection.00:04:00 – Hollywood's AI Play: Netflix acquiring Ben Affleck's AI company, Interpositive, which uses unedited film dailies to train an AI for editing and optimization.00:05:00 – The Mediocrity Threat: Rony Abovitz's take on the risk of AI creating a "very, very long tail of Okay" content, leading to a cultural sameness.00:07:00 – Counter-Culture: Exploring the growing emotional need for "something real" and a massive movement away from purely digital experiences.00:09:00 – The White-Collar Risk: The hosts argue that the white-collar data analyst is the worker "most easy to replace" by AI, contrasting with the high value of blue-collar workers.00:11:00 – The "Oh Wow" Moment: Charlie Fink describes his first experience with Teamily AI, noting the immediate power of real-time, multi-person and multi-agent prompting.00:13:00 – The Science Behind Teamily: Dr. Aiden He, PhD in Machine Learning, explains how Teamily is built upon his previous research in distributed learning and multi-agent systems.00:26:00 – Global Memory: Aiden details Teamily's unique "cross domain, long horizon memory," which allows the AI to combine human-human chat context with human-AI memory for a more natural interaction.The biggest takeaway is the conceptual shift from using AI as a solo productivity tool to using it as a collaborative team member. The path to the next phase of social networking hinges on building platforms where AI is not isolated but is a natural, evolving part of a human community.This episode of The AI XR Podcast is brought to you by Zappar, the folks behind Mattercraft, a leading visual development environment for building immersive 3D web experiences for mobile headsets and desktop. Start building smarter at mattercraft.io. Listen and subscribe to the AI XR Podcast wherever you get your podcasts! Watch the full thing on YouTube https://youtu.be/s78WZJSfGeo. Hosted on Acast. See acast.com/privacy for more information.

AI couldn't cure his mother's stage 4 cancer. It caught three near-fatal errors, found a same-day appointment, and helped her leave on her own terms. When Pratik Desai's mother was diagnosed with stage four duodenal adenocarcinoma — a rare cancer with roughly 3,000 US cases a year — she was nearly discharged without an oncology appointment. Over the next 76 days, Desai used AI at her bedside, from 5am to 10pm, to understand each report, prepare for every appointment, and push a stretched health system to move at the pace her diagnosis demanded. This is a frank account of where AI helped, where it didn't, and the line he refuses to cross. This is a 1:1 interview in The Agentic Patient — a Faces of Digital Health series on how patients and caregivers actually use AI: which tools, which prompts, and which guardrails. GUEST Pratik Desai — New Jersey-based AI practitioner; caregiver and builder of a free, local AI tool for patients HOST Tjaša Zajc — Founder & host, Faces of Digital Health / The Agentic Patient WHAT THE CONVERSATION COVERS - Using AI to interpret a biopsy report and push for a same-day "stat" CT scan - Why AI and the doctors agreed on the care — and clashed on the speed - Finding a same-day oncology appointment through an AI-assisted network search - An error-riddled CT report the AI refused to read — and what it did to trust - Running three Claude "personas" as built-in second and third opinions - A local, open-source AI tool that keeps medical data off the cloud - How to prompt as a patient or caregiver: awareness, knowledge, advocacy — not diagnosis - Where AI failed him: prognosis, and the rule he broke under pressure - Defining quality of life when the outcome is already known CHAPTERS 0:00 How patients use AI — and the guardrails 1:20 Day one: a healthy mother, a diagnosis no one would name 3:34 The first prompt, and pushing for a stat CT scan 7:43 Using AI in the open: agreement on care, friction on speed 9:35 The counterfactual: 76 days with AI at the bedside 12:40 Finding a same-day appointment through a network search 13:40 The CT report the AI refused to read 15:50 When trust erodes: good faith, not competence 18:41 Why switching hospitals wasn't an option 21:54 Defining quality of life: her three goals 28:27 Three Claude personas, and a local private tool 35:12 How to prompt: awareness, knowledge, advocacy — not diagnosis 37:54 Where AI fell short, and the closing asks THE AGENTIC PATIENT SERIES New to the series? Start here → [PASTE PREVIOUS AGENTIC PATIENT EPISODE LINK] All episodes → https://www.facesofdigitalhealth.com/agentic-patient-blog MORE FROM FACES OF DIGITAL HEALTH

Depending on whose view you subscribe to, agentic AI is either the breakthrough banks have been waiting for in operations (and customer service), or the perennial solution in search of a problem. Join our three fintech rockstars as the get to the bottom of what agentic AI means in 2026—and whey the hype pits justification versus a lack of tech realization.

Introduction Carriers have spent decades building underwriting models on structured data - loss history, credit scores, telematics - while ignoring one of the richest signals available: how people actually behave when they fill out an application. ForMotiv was built on the premise that digital body language is predictive, and after nearly a decade of proving it, the company just hit profitability. Woody Klemmer is the co-founder and Head of Growth at ForMotiv, a behavioral analytics platform now embedded across the majority of the top ten U.S. carriers. In this conversation, Josh Hollander and Klemmer dig into the growth paradox carriers can't escape, what agentic AI fraud actually looks like at the application layer, and why the build-versus-buy math on behavioral data almost always favors buying. Guest Bio Woody Klemmer is the Co-Founder and Head of Growth at ForMotiv, a behavioral analytics platform purpose-built for the insurance industry. ForMotiv captures digital body language - hesitations, edit patterns, corrections, and interaction behaviors - from online applications and turns them into real-time signals for conversion, risk, and fraud decisions. Klemmer has spent nearly a decade growing the business from a direct-to-consumer tool to an enterprise-wide behavioral intelligence layer serving the majority of the top ten U.S. carriers. Key Topics The growth paradox — Every tactic carriers use to grow inadvertently lowers the barrier for misrepresentation and fraud. The impact catches up 12 to 24 months later in loss ratios. ForMotiv's thesis is that behavioral intelligence can break this either/or dynamic between growth and risk. Intent is two-dimensional - Conversion likelihood on one axis, risk profile on the other. A high-intent applicant who backed into their garage is a fundamentally different underwriting risk than one who just bought a new car. The Year of the Agent - ForMotiv sold more agent-related solutions than direct solutions for the first time in 2024. Agents know underwriting thresholds and how to game the system. Agent scorecarding and benchmarking tools are now being used for fraud detection, SIU referrals, and new hire training. Enterprise intent - In 2026, ForMotiv embeds across the full policy lifecycle from first quote to claims, providing a unified behavioral thread across systems that have traditionally been siloed. Agentic AI detection is live - ForMotiv can identify when an AI agent is completing an application. Carriers are still deciding what to do with that signal, but the detection capability exists today. First-party data as a model input - Carriers incorporating ForMotiv's behavioral dataset into existing predictive models are seeing measurable jumps in predictive lift from a genuinely novel data source. Notable Quotes "Carriers are faced with what we call a growth paradox - the mechanisms they use to grow inadvertently increase risk. And that usually catches up 12, 18, 24 months later." "We had a carrier say the quiet part out loud: our worry is we're getting the bad business that you're helping protect the other carriers from." "When people ask who our biggest competitors are, I always say bandwidth and budget. We're sunscreen - protective, but not a necessity until we're integrated." "The JavaScript component isn't the value. What we've done over a decade is feed it all back to you in 40 milliseconds." Resources Guest: ForMotiv: https://www.formotiv.com Woody Klemmer: https://www.linkedin.com/in/woodyklemmer/ Host & Organization: Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ Horton International (USA): https://www.horton-usa.com/ Insurtech Leadership Podcast: https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

By Doug Green “Governance is absolutely necessary. It's no longer optional.” In this episode of the Technology Reseller News podcast, Doug Green speaks with Rajesh Kari, Senior Director of Products and Solutions at Versa Networks, about the emerging security challenges created as agentic AI moves into live network and security operations. Kari says Versa Networks is a leader in SASE, offering a unified platform that brings together networking, security and operations across enterprise infrastructure. As AI becomes more embedded in operations, Versa is focused on a new zero trust challenge: controlling not only users and devices, but also the hidden AI-driven sub-actions that can touch production systems. Kari explains that agentic AI is different from traditional AI because it can take action on behalf of users. Rather than simply answering a prompt or returning information, an agent may break a task into sub-queries, call APIs, use credentials, access systems and make changes inside the infrastructure. Those hidden sub-queries can create risk if organizations cannot see, validate and govern what the agent is doing. “People build agents. They know what the objective of the agents are,” Kari says. “But under the hood, what the agent actually deploys, which APIs it accesses, and what kinds of authorization and authentication it leverages can be unknown.” The podcast explores how this creates new exposure for enterprises, MSPs and channel partners. If an AI agent gains access to credentials or production systems, organizations need constant verification, validation and governance around each action. Kari says agentic AI can also hallucinate or generate unnecessary sub-queries, creating additional security and operational risk. Versa is addressing this through Versa Verbo and its Zero Trust MCP architecture. Verbo is designed to help network practitioners gain visibility, management and analytics through natural language interactions. Instead of searching through hundreds of alerts or dashboards, operators can ask questions about outages, performance issues, configuration changes, security incidents and branch health. The Zero Trust MCP architecture extends that capability by applying governance and access control to AI-driven actions. Kari says this enables AI models and agents to query Versa infrastructure securely, while maintaining controls around authentication, authorization, APIs and operational workflows. For MSPs and channel partners, Kari sees an important opportunity. Many organizations want to deploy AI quickly but do not have the internal capability to build governance infrastructure around it. Partners that develop practices around policy architecture, deployment, ongoing governance and human-in-the-loop approval can help customers adopt agentic AI more safely. Kari says AI operations copilots are becoming standard in SASE and network platforms. Network teams, infrastructure managers and executives increasingly want to use natural language to understand the health of their infrastructure instead of relying only on dashboards. But as those tools become more powerful, governance becomes the deciding factor in adoption. “If the agent has gained access into certain files or visuals which has violated any particular compliance standards, it becomes the responsibility of the organization to prove it,” Kari says. For Versa, the message is clear: agentic AI can simplify operations and accelerate decision-making, but it must be governed from the beginning. Zero trust principles need to be built into every AI agent connection. Learn more at www.versa-networks.com  

We'd love to have your feedback and ideas for future episodes of Retail Unwrapped. Just text us!The weakest link in most data strategies is the human factor; it's the team members who can't agree on measuring what matters. Add to that, communications often break down in the best tech solutions to deploy and how to integrate them to prevent data fragmentation. Join Shelley and Tim Shea, Founder and CEO of Latticework Insights, as they unpack why culture, not code, decides whether a retailer's next analytics dollar will be profitable. Fast facts: Agentic commerce is already filling shopping carts before customers reach a retailer's site, and most brands have no real lever to influence which products an AI agent selects. Plus, organic search visibility is collapsing as AI overviews and sponsored results dominate the page, pushing traditional discovery to page two or three. Listen and learn how to be a better data strategist with analytics that are evaluated with the same rigor as marketing spend, as a return on investment rather than an obligatory expense. Special Guest: Tim Shea, CEO and Founder Latticework Insights For more strategic insights and compelling content, visit TheRobinReport.com, where you can read, watch, and listen to content from Robin Lewis and other retail industry experts, and be sure to follow us on LinkedIn and Twitter.

In this episode of the B2B Marketing Podcast, Kavita Singh sat down with Adam Bertelsen, AI Workforce Transformation Lead, Baringa to unpack how agentic AI is reshaping the way work gets done and what it really means for B2B marketers. Adam shares cross-industry lessons from sectors like law, financial services, media, and government, revealing the patterns in which tasks AI absorbs first and why creative judgment, brand instinct, and relationship-building still sit firmly in the human camp. Together, they explore the five “human-native” capabilities that matter more as AI matures: translation and judgment, accountability and trust, embodied presence, taste and provenance, and relationship-building. Adam and Kavita also dig into why so many organizations are failing to see real productivity gains from AI, how to move from experiments to strategic value, and why the smartest leaders are treating AI as an operating model shift rather than a tool rollout. If you're under pressure to prove ROI from AI without sacrificing distinctiveness, this episode is a must-listen. In addition, B2B Ignite will be taking place on 1 July in London. Listeners to the podcast can save 20% on their ticket to B2B Ignite 2026 – simply enter the discount code PODCAST when prompted at check out.https://events.b2bmarketing.net/b2bignite

The skills problem isn't going anywhere — it's just wearing new clothes. In this episode, I unpack how the lessons we learned decades ago (limiting work in progress, the theory of constraints, test-driven development) are coming roaring back as the fundamentals that will carry you through the agentic shift. The bottleneck has moved, and knowing where it went changes how you should work. A lot of what we're learning about building with agentic tooling isn't new at all — it's a re-emphasis on lessons software engineers learned twenty years ago, just arriving in a new form. In today's episode, I walk through why the fundamentals are becoming more important than ever, why so many of us feel scattered despite having the most powerful tooling we've ever had, and where the real bottleneck in software delivery has quietly moved. My goal isn't to convince you that your job is now babysitting AI — it's to show you which parts of the work are still squarely yours, and how older principles can make you faster and more confident right now. Limiting Work in Progress Is Back: Just because you can spin up fifty agents doesn't mean you should split your focus across fifty things. Orchestrated fan-outs are powerful, but a human juggling agents across hiring, on-call, and a project all at once still pays the same old context-switching tax — and the quality drops while the speed never improves. Work Deeper, Not Wider: Instead of spreading yourself shallowly across more tickets, run multiple sessions on the same domain. Write a competing or adversarial version that critiques your assumptions, develop better documentation, or capture what you're learning as a reusable skill. Depth beats breadth. The Scattered-Engineer Epidemic: Engineers are burning out faster, not slower. We have the capacity to push more through the pipeline, so we're getting handed (or choosing) more than we can carry. Reducing parallelism often holds your delivery speed steady while dropping your cycle time and raising quality. The Theory of Constraints, Revisited: Treat your software development lifecycle as a pipeline with a bottleneck — and if you can't find one, you've optimized one part too far. Writing code used to be the choke point, so we spent enormous energy de-risking work before it ever reached an engineer. The Bottleneck Has Moved: When production gets cheap, it's no longer worth heavily de-risking upstream — which is why engineers are picking up more experimental, proof-of-concept, discovery work, and product folks are prototyping with these tools too. The new constraint isn't writing the code; it's verifying the agent didn't ship something broken. Verification Scales With Your Effort: The more an agent produces, the bigger the pile of PRs, MRs, and outputs waiting on human review. That backlog is the new bottleneck — and skepticism is creeping in because we're not even sure our tests are sufficient to verify what the agent built. Why TDD Fits This Moment: The honest question isn't "Can I trust the agent?" — it's "What verification loop do I need to build so I can trust it more?" Clear requirements feed a clear testing loop: write the failing test, let the agent write the code to turn it green, and you bridge the gap between requirements gathered and requirements met. It's not as simple as "go write a test," but it's a strong fit for where we are right now. Episode Homework: Go dig into the fundamentals — limiting WIP, the theory of constraints, test-driven development. Find the old lesson that still applies to your workflow today, bring it to your team's flow, and email me about what you discover.

In this episode of the Kubernetes Bytes podcast, Bhavin talks to Rob Zuber, CTO at CircleCI about all things Software Delivery. The discussion starts by talking about the evolution of Software Delivery over the last decade, but then dives into how Vibe coding impacts CI pipelines. Rob also shares his insights about running an AI-first engineering organization at CircleCI. Listen to learn more! Check out our website at https://kubernetesbytes.com/ Show Notes: https://www.linkedin.com/in/robzuber/ https://circleci.com/ https://circleci.com/blog/

Daniel and JB kick off what they call their most capital-intensive episode yet on ADSN. The conversation opens with SpaceX's blockbuster IPO — stock surging past $200 a share, the company now worth more than Microsoft, and the staggering stat that Elon Musk's net worth jumped by "a full Warren Buffett" in a single day. From there they unpack the $60 billion Cursor acquisition, Fox's $20 billion Roku deal, Substack's official ads launch, and Mercury's new agentic banking platform.The episode covers a wide sweep of what's moving in tech and media right now: why frontier AI labs are about to go on an acquisition spree, how Fox is running Meta's family-of-apps playbook for television, why Sam Altman says "always make an API" saved OpenAI, and the emerging argument that tech companies will start looking more like hedge funds — tiny teams, massive AI leverage, and profit per employee through the roof. If you want to understand where the money is flowing and why, this is the episode.Thank you to our sponsors:AdQuick – Making OOH advertising as easy to plan, buy, and measure as digital. ⁠⁠adquick.com⁠⁠⁠⁠Thrad.ai⁠⁠ — Building the advertising infrastructure for AI. ⁠⁠thrad.ai⁠​beehiiv — The all-in-one platform for newsletters, websites, and every tool you need to grow and earn. ⁠⁠⁠beehiiv.com⁠⁠​The Farm — Fraction commercial legal with an in-house approach to outside counsel. ⁠thefarmllp.com ⁠STAY CONNECTEDJames on Twitter & LinkedIn – /jamesborowDaniel on LinkedIn, Instagram, TikTok – /danieldrugerSubscribe & leave a ⭐⭐⭐⭐⭐ review on Spotify & Apple Podcasts.

In this second special collaboration with Sumsub's What the Fraud? podcast, we close out our Money20/20 Europe series with our 8th episode from the show - a deep exploration of how AI, digital identity and agentic commerce are reshaping trust across global financial services. From neobanks rethinking what “trust by design” really means, to product leaders tackling fragmentation, to regulators navigating cross‑border complexity, this episode brings together five voices defining the next era of intelligent, secure and human‑centred finance. Tom Taraniuk, Head of Partnerships at Sumsub took on hosting duties and was joined by: 1/ Mette Gade, CPO, Lunar 2/ Breno Oliveira, Chief Product Officer, payabl. 3/ Bankole Falade, Chief Legal, Regulatory Affairs & Public Policy Officer, Flutterwave 4/ Conny Ploth, Vice President, Global AI Transformation, Santander 5/ Antoine Dauchy, Product Leader, FLOA

We're told AI will revolutionize marketing, but many leaders are finding it just creates more content chaos and operational risk. Is the answer more AI, or a fundamentally different approach to how AI is managed?Today we are at PegaWorld 2026 at the MGM Grand in Las Vegas, and, we're going to talk about:- The shift from generative AI for content creation to agentic AI for end-to-end campaign execution.- How to orchestrate multiple AI agents to move from a marketing brief to a live, personalized campaign in minutes, not weeks.- Implementing the governance and human oversight necessary to scale AI-driven marketing responsibly and avoid the risks of uncontrolled automation.To help me discuss this topic, I'd like to welcome Tara DeZao, Director of Product Marketing, AdTech and MarTech at Pega. About Tara DeZao Tara DeZao, Director of Product Marketing, AdTech and MarTech at Pega, is passionate about helping clients deliver better, more empathetic customer experiences backed by artificial intelligence. Over the last decade, she has cultivated a successful career in the marketing departments of both startups and Fortune 500 enterprise technology companies. She is a subject matter expert on all things marketing and has authored articles that have appeared in AdExchanger, VentureBeat, MarTech Series and more. Tara received her bachelor's degree from the University of California, Berkeley and an MBA from the University of Massachusetts, Amherst. Tara DeZao on LinkedIn: https://www.linkedin.com/in/taradezao/ ---------- Resources ---------- : https://www.pega.com Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn more at Pega.com We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fDon't miss We Make Future - the International Festival of Innovation in AI, Tech, and Digital Marketing, June 24-26 in Bologna. Learn more: https://aglbrnd.co/r/c80991afff416bb2The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

What does it take to move from AI experimentation to real business impact? Recording during Google Cloud Summit London 2026 at Tobacco Dock, I had the opportunity to speak with Maureen Costello, Vice President for UKI and Sub-Saharan Africa at Google Cloud, about one of the biggest shifts currently taking place across technology and business. After years of discussion around generative AI, the focus is now turning toward agentic AI and how organizations can put these capabilities to work in practical, measurable ways. Maureen offered a fascinating view from the front line of AI adoption, sharing how businesses across financial services, retail, government, and other sectors are beginning to move beyond pilots and proof-of-concept projects. We discussed how AI is helping organizations improve customer experiences, increase productivity, strengthen decision-making, and create new opportunities for growth. From helping banks tackle financial crime and deliver smarter customer services to supporting government departments in modernizing public services, the conversation is filled with examples that bring the technology to life. We also explored why the UK is so well positioned for the next chapter of AI adoption. With world-class research, exceptional talent, and ambitious investment across both the public and private sectors, Maureen believes the UK has a genuine opportunity to remain at the forefront of AI innovation. She also explained why skills development, data readiness, security, governance, and trust will play such an important role as organizations begin introducing AI agents into everyday workflows. What I particularly enjoyed was discussing the human side of this transition. As AI becomes embedded into business operations, how should leaders prepare their teams? What separates organizations that achieve meaningful outcomes from those that struggle to move beyond the early excitement? And how can businesses strike the right balance between innovation, responsibility, and long-term value? Whether you're following the announcements from Google Cloud Summit London, building your own AI strategy, or simply trying to understand where this technology is heading next, this conversation offers valuable insight into one of the most talked-about topics in business today. What role do you think agentic AI will play inside your organization over the next 12 months, and are businesses finally moving from curiosity to meaningful adoption?

As enterprises move agentic AI from controlled pilots into production customer-facing workflows, the gaps in data continuity, governance, and human-agent coordination become the deciding factors in whether AI scales or stalls. In this episode, Shri Nandan, VP of AI Experiences at Comcast, examines why customer experience has become the real stress-test for enterprise AI — and what it takes to scale with customer trust intact. The conversation covers the three data foundations required for context continuity in production, practical principles for human-AI orchestration, and why cross-team governance — a single North Star across CX, IT, and operations — is what separates the organizations that scale from those that fragment. This episode is sponsored by NiCE. Learn how to structure landing pages for higher conversion and how to use self-qualification systems to prioritize high-intent leads. Download our free PDF report, "B2B AI Lead Generation Guide," at emerj.com/aig1

For episode 300 of The Product Podcast, Carlos Gonzalez de Villaumbrosia sits down with Ajit Varma, Head of Firefox at Mozilla, the nonprofit behind the original challenger browser that pioneered browser tabs, pop-up blockers, and browser extensions. With 210 million active users and $826 million in annual revenue, Firefox is the only major independent, open-source browser still standing against Google Chrome's 68% share, Apple Safari's 17%, and a new wave of agentic browsers. Before Mozilla, Ajit spent six years at Meta leading monetization of WhatsApp and overseeing its business messaging platform. He has also held product roles at Google, Uber, and Square.What you'll learn:Why LLMs are making browsers more strategically important, and what that means for product teams building in an agentic worldWhy "trust us" is no longer enough, and how open source changes the standard for privacy in AI products- How to compete against trillion-dollar incumbents without abandoning your missionKey takeaways:Privacy claims without open-source inspectability are unverifiable, "trust us" is no longer a sufficient product strategy in the AI eraCompeting against trillion-dollar companies is possible when mission clarity defines what you refuse to optimize forThe agent-driven internet will either democratize access or concentrate it, product choices made today will determine whichSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

פרק מספר 516 של רברס עם פלטפורמה - קרבורטור מספר 41. הפעם רן ואורי מארחים את נתי לשיחה על נקודת המפגש המרתקת שבין קוד פתוח לקידוד מבוסס סוכנים (Agentic Coding). דיברנו על העתיד הדיסטופי והאופטימי של מפתחי קוד פתוח, איך משווקים מוצרים ל-Agents, ולמה שורת הפקודה (CLI) חוזרת אלינו בענק. [01:04] העתיד המדומיין של AI (סיפורו של OpenClaw) נתי משתף סיפור משעשע על ניסיון לחקור את "OpenClaw". הזיות (Hallucinations) של מודלים: Claude מאשר את העובדות, בעוד ש-Gemini מנתח שמדובר בהמצאה עתידית (פברואר 2026). הבנה שמודלי שפה (LLMs) הם מנועים הסתברותיים ולא מנועי חיפוש עובדתיים. [05:58] החזון הדיסטופי: האם AI יהרוג את הקוד הפתוח? בעיית ההעתקה: בעבר קוד הוגן על ידי רישיונות (כמו AGPL), היום קל לבקש מהמודל לשכתב קוד משפה אחת לאחרת (למשל מ-NodeJS ל-Rust) בעלויות אפסיות. קריסת מודלים עסקיים: עלויות התמיכה והאופרציה (Operation) יורדות כי ה-Agent מתקן תקלות לבד, מה שחותך את ההכנסות של חברות כמו Red Hat. עומס על ה-Maintainers: קוד מג'ונרט על ידי Agents נראה מעולה ומתועד היטב, אבל לא תמיד נכון ארכיטקטונית או לוגית. גישות התמודדות: חלק דורשים לקבל את ה-Prompt (הכוונה) ולא את הקוד עצמו, בעוד שאחרים (כמו יוצר שפת Zig) אוסרים לחלוטין גישה של AI לפרויקט. [15:15] החזון האופטימי: שיווק לסוכנים (GEO) מעבר מ-SEO ל-GEO (Generative Engine Optimization): סוכני AI הם הלקוחות החדשים. איך Agent בוחר כלים? לפי איכות הקוד, הפופולריות שלו ב-GitHub, ובעיקר לפי התיעוד. קוד פתוח הופך לכלי שיווקי קריטי (Open Core) כדי שהסוכנים יוכלו למצוא, להבין ולהמליץ על המוצר. מודלים היברידיים ו-Freemium: מוצרים (כמו Postits) מציעים גישה ללא חומת תשלום (Paywall) בשלבים הראשונים, מה שמאפשר ל-Agents לעבוד איתם בקלות דרך API (Headless SaaS), ואפילו לבצע רכישות בעצמם בהמשך דרך Stripe. [30:29] שובו של ה-CLI ומגבלות ה-MCP הדיבייט סביב MCP (Model Context Protocol): הפרוטוקול כבד, "זולל" טוקנים (Token hungry) עבור הקונטקסט, ודורש תחזוקה של שרתים נוספים. למה Agents כל כך אוהבים CLI (שורת פקודה)? גישה ישירה לאקוסיסטם המקומי והרשאות (כמו Kubernetes או סביבות ענן) בלי לחשוף מפתחות לשירות חיצוני. יכולת לבצע מניפולציות מורכבות בצד הלקוח (Chaining, Grep, Sed) מבלי לשנות קוד ב-Backend, מה שהופך את המודלים לאנשי DevOps מעולים. [36:17] רישיונות קוד פתוח וה"נשמה" של המוצר האתגר באכיפת רישיונות (כמו GPL) בעולם שבו קשה להוכיח על איזה קוד המודל התאמן ואם בוצעה העתקה. הבדל חשוב בטרמינולוגיה: מודלים של "Open Weights" לעומת מודלים שה-Training Data שלהם באמת פתוח. תוכנה כיצירת אומנות מול קומודיטי (Commodity): האם קוד מג'ונרט יכול להחליף את החזון וה"נשמה" (Soul) של מפתחים בולטים? ההשוואה לעולם המוזיקה מדגישה שמשתמשים הולכים אחרי האומן והחזון, לא רק אחרי הקוד היבש. [50:25] רגולציה ומודלי Open Weights אורי מעלה נקודה מעניינת על החסימה של מודל Fable 5 / Mytos 5 (של Anthropic) למשתמשים מחוץ לארה"ב על ידי הממשל האמריקאי. ההשפעה של רגולציה: ה"תקרת זכוכית" הזו עלולה לפגוע בחברות המסחריות האמריקאיות בטווח הקצר, ודווקא לדחוף קדימה מודלים פתוחים (Open Weights) סיניים או אירופאים שאינם כפופים לאותן מגבלות. האזנה נעימה!

In this first of two special episodes recorded in partnership with Sumsub's What the Fraud? podcast, and our seventh recorded at Money20/20 Europe, we explore the rapidly shifting landscape of AI‑driven fraud, digital trust, global onboarding and cross‑border financial access. From foundation models powering entire payment stacks to the rise of agentic commerce and the operational realities of scaling internationally, this episode brings together four leaders working at the front line of financial crime prevention and global payments innovation. Tom Taraniuk, Head of Partnerships at Sumsub took on hosting duties and was joined by: 1/ Georgios Kolovos, Payments & FinTech Leader, NVIDIA 2/ Joe Wilson, Chief Evangelist, bunq 3/ Rik Goslinga, Vice President, Account Management, EMEA, Adyen 4/ Ivan Zhiznevsky, Founder & Chief Executive Officer, 3S Money

How Shameem Shah Is Helping Businesses Win With Agentic AI | XpentorShameem Shah | Founder & Tech Advisor, Xpentor (Bud Lake, NJ)LinkedIn: Xpentor (search E-X-P-E-N-T-O-R)Website: www.xpentor.comConnect & Inquire: via LinkedIn or the Xpentor website"AI is just refrigeration for us. Now, are you going to create your own Coca-Cola?" — Shameem ShahWhat separates a real, scalable AI build from something you slapped together on a no-code tool? On this episode of Diversified Game, Kellen Coleman sits down with Shameem Shah, founder of Xpentor, a software and technology consulting firm out of New Jersey serving insurance, higher education, NGOs, and government since 2008.Shameem breaks down the shift from generative AI to agentic AI, why most no-code builds fail to scale without the right data model and architectural foundation, and how his team uses AI to crush compliance and speed-to-market in the insurance industry.We get into his internal tool Cognax, real use cases from medical colleges to underwriting, why an MVP at $2,000 to $5,000 beats a blind $100,000 commitment, and his big-picture take on where AI is taking all of us.No surface-level hype. Real architecture, real problems, real solutions.Learn the mindset and moves that lead to real results. Please visit my website to get more information: http://diversifiedgame.com/

Mike Michelini and Christian Garcia go deep on AI-powered data systems, custom-built e-commerce tools, and the emerging agentic commerce standard and what it all means for Amazon sellers.

There's great momentum in moving to greater levels of agentic automation, but there are critical areas where deeper consideration is required in how it's applied. In capital markets, trust is a foundational element on which transactions are built and Krisha Vinjamuri, Head of Technology, Enterprise Solutions at S&P Global Market Intelligence, joins host Eric Hanselman to talk about how this can be achieved and the important aspects of successful implementations. One of the useful things in capital markets, is that there are open standards on which to base data ontologies. It's not exciting, but it's the basis of a semantic foundation that can not only ensure that there is depth in data definitions, but can also reduce errors generated by agents. The larger question that looms beyond the construction of foundational architecture, is how the operational envelope that bounds agentic action will be established. This has to be built from policy definitions that take those actions into account. There is great promise and much work that needs to be done. More S&P Global Content: Compute sovereignty: The strategic importance of digital infrastructure AI won't solve its own energy problem – and that might be fine AI in action: unleashing agentic potential AI infrastructure results in 2025 top expectations, forecast upgraded For S&P Global subscribers: FinOps in the age of agentic AI AI Infrastructure Market Monitor & Forecast Service providers race to meet surging enterprise demand for AI infrastructure In 2026, the telecom network becomes code Credits: Host/Author: Eric Hanselman Guest: Krishna Vinjamuri Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith, Dylan Scheible

Tether's USDT has been delisted by major crypto exchanges (including Binance, Coinbase, Kraken, and Crypto.com) specifically for users in the European Economic Area. This occurred because Tether chose not to pursue registration under the EU's Markets in Crypto-Assets (MiCA) regulation. Meanwhile, WalletConnect is empowering the stablecoin ecosystem for millions of merchant around the world. ~This episode is sponsored by Tangem~ Tangem ➜ https://bit.ly/TangemPBN Use Code: "PBN" for Additional Discounts! GUEST: Jess Houlgrave - CEO WalletConnect Follow Wallet Connect on X ➜ https://x.com/WalletConnect 00:10 Sponsor Tangem 01:10 WalletConnect growth: Ingenico rollout progress 03:00 When Verifone or PAX? 05:00 Is Toast Toast? 07:30 Tether Delisted 09:45 Would WalletConnect take over non-compliant use cases of Tether? 11:00 Innovation in the EU 12:45 Saving USDT Utility? 14:15 Business model 17:00 Merchant fees 19:00 Tap-to-pay 21:20 Private transactions impossible? 23:30 CLARITY odds 25:40 WalletConnect fail? 26:15 User-friendy? 26:45 Transaction fees 27:00 Stablecoin threat 29:00 Credit card rewards 29:45 Stablecoin growth vs self-custody growth 30:40 $WCT utility 31:30 Agentic payments 32:30 Netflix login soon? #Crypto #XRP #Ethereum ~Tether Mass Delistings? + Stablecoin Catalysts Coming!

Agentic AI for Law Firms 3: The cost of split testing vs. taste>> Get the newest LFG episodes delivered to your inbox when you Sign Up for our Newsletter.>> Get the new book beyondintakebook.comResource Links:Fast track your marketing efforts while avoiding common marketing mistakes in our new trainingEstate planning attorney? Stop guessing how to get results from online ads and grow your firm with our client-generating Seminar 3.0 Hosted on Acast. See acast.com/privacy for more information.

In this episode of The Broadband Bunch, host Pete Pizzutillo sits down with Rob Lawrence, Technology Strategist at Microsoft, to separate the reality of agentic AI from the growing hype surrounding autonomous systems. As organizations race to experiment with AI agents, Rob argues that the biggest challenges aren't the models themselves—they're the operating environments, governance frameworks, data quality, accountability structures, and organizational readiness required to deploy them successfully. Pete and Rob discuss why many AI pilots succeed while production deployments struggle, the return of disciplines like project portfolio management and process engineering, and why data governance may be the most important prerequisite for successful AI adoption. Rob also talks about the role of identity and permissions, the risks of poorly governed agents acting on flawed data, and why organizations need better observability into AI-driven workflows. Along the way, he shares advice for CIOs, CTOs, and broadband operators looking to move beyond experimentation and build a responsible foundation for agentic AI.

Agentic storefronts attract divided opinions. From early adopters convinced they're an innovative way to service online customers who need a deeper level of assistance, akin to an in-store sales assistant, to cynics who see this as a distraction from fixing your main website.That's why we invited Jojo Regan, co-founder at Manors Golf, to join us and explain how & why they've launched an agentic storefront to complement the main website. As a self-confessed early adopter of technology, Jojo offers an interesting perspective on the role agentic storefronts can play within an ecommerce strategy.In Jojo's opinion, some brands are missing a huge opportunity by sticking to static, traditional ecommerce experiences. We explore how leveraging AI-driven, conversation-based storefronts can transform customer engagement and boost sales.His vision is for a golf apparel brand that lets customers chat, discover and personalise their shopping journey in real-time, without the limitations of static pages. Jojo explains how Manners Golf is pioneering this shift by integrating an agentic storefront powered by large language models (LLMs). He discusses the strategic thinking behind enhancing traditional online stores with dynamic, interactive experiences that mimic walking into a physical shop, where personalised recommendations and discovery happen naturally.Tune in for the following:The way early adoption of innovative tech like agentic storefronts keeps Manors ahead of the curve in ecommerce.The impact of conversational experiences on key metric, such as a 54% reduction in return rate.The future of AI-enabled shopping: personalisedand highly engaging environments that anticipate consumer expectations.Why early investment in these technologies positions brands as industry leaders in the coming AI-driven retail landscape.How Manors Golf employs a team with creative and technical expertise to produce viral content that drives a top-of-funnel strategy without heavy paid marketing.It's still very early days for agentic storefronts, so real-world case studies will help you build your understanding of what is possible, and what is relevant.

The drama around Anthropic's Fable 5 model clogged our collective attention spans.

Join us as Dave walks through what it actually takes to build custom AI agents from scratch - not theory, but real projects he has shipped for his family, his work, and his community. Dave shares how he used Kiro and Claude to solve real problems: normalizing flood-damaged library inventory data, automating AWS well-architected review collateral, building a room-cleaning task agent for his 12-year-old, planning family menus with Apple Calendar integration, and post-processing live concert recordings. You will learn how agents reason and take action, when to reach for a Kiro power versus a simpler automation, how MCP servers connect agents to real-world tools, and practical strategies for keeping agents accurate without burning through tokens. Timestamps 0:00 Welcome & Introduction 7:57 Dave's Background and How He Got Started with Agents 13:00 The Library Flood Story - First Real-World Agent Use Case 16:00 AWS Well-Architected Review Automation 17:09 What Are Kiro Powers and MCP Servers? 22:13 Kiro Pricing and Bedrock Integration 28:13 Live Demo - Room Cleaning Agent with AWS Rekognition 41:24 Family Meal Planning and Apple Calendar Integration 44:27 Automating Live Concert Recording Post-Processing 52:31 Getting Started - Dave's Recommendations for Beginners How to find Dave: https://www.linkedin.com/in/dave-stauffacher/ Links from the show: https://kiro.dev/

In this episode of The Geek in Review, we welcome Greg Dickason, Chief Technology Officer at LexisNexis, for a wide-ranging conversation on agentic legal AI, Lexis+ AI Protégé, and the movement from AI chat toward AI work. Dickason frames the shift through a simple contrast: earlier legal AI answered questions, while agentic workflows take on multi-step assignments, conduct research, create drafts, verify citations, and move legal professionals closer to finished work product. For law firms and legal departments trying to understand where AI goes next, this episode places agentic AI squarely inside legal workflow, legal research, drafting, and risk management.A major theme of the conversation is trust. Dickason explains how Shepard's Verify extends the familiar Shepard's signal beyond traditional research screens and into uploaded work product. Rather than asking lawyers to rely on AI-generated text without a verification layer, LexisNexis is building citation checking into the workflow, giving lawyers a path to confirm whether cited authority exists, whether authority is still good law, and how later courts treated the cited case. For lawyers worried about hallucinated citations, AI-generated briefs, and unreliable authority, this verification layer becomes part of the product architecture, rather than an afterthought.The discussion also explores the relationship between LexisNexis and Anthropic, along with the rise of legal AI skills. Dickason describes a market where model choice, orchestration, and legal skills increasingly matter as separate layers. Anthropic, OpenAI, Google, and other model providers offer impressive foundations, yet legal work needs more than general-purpose intelligence. Large law workflows require legal content, expert reasoning, matter-specific playbooks, and firm-defined processes. Dickason notes the ability to upload firm playbooks as skills, giving firms a path to bring their own way of working into Protégé.Security receives equal billing with accuracy. As firms place client documents into AI vaults and connect work product to legal AI platforms, Dickason explains bring your own key, or BYOK, through a practical office-and-locked-cabinet analogy. The point is control: client content sits encrypted, access depends on the user's key, and access stops when the key is withdrawn. He also discusses legal chunking, indexing, vector stores, retrieval-augmented generation, and knowledge graphs as part of building AI systems suited for legal documents, rather than generic file handling.The episode closes with a broader view of legal AI's impact on junior associates, legal training, and access to law. Dickason does not predict the end of junior lawyers. Instead, he sees AI helping junior lawyers become senior faster through mock trials, mock depositions, and richer training environments. He also warns of risks from agent volume, security vulnerabilities, and legal systems struggling to keep pace with AI-enabled industries. The message is pragmatic and optimistic: agentic legal AI will change legal work, yet the winners will be those who combine trusted content, secure systems, verification, workflow design, and human judgment.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

Artificial intelligence agents are beginning to make their presence felt in online payments. At present, they typically discover options for purchase and present users with buy options. However, many are already looking towards a future where AI agents have wallets and the ability to pay for small items with stablecoins. This could also create the opportunity for machine-to-machine micropayments. Chad Harper, head of the Coinbase Institute, joins Lewis McLellan, head of content at OMFIF's Digital Monetary Institute, to discuss the rails that will facilitate agentic payments, particularly x402, Coinbase's payments protocol.

In just twelve months, the conversation around Agentic AI in insurance has changed dramatically.  What began as curiosity about autonomous AI agents has evolved into a much more practical discussion about implementation, governance, economics and competitive advantage.  In this special solo episode, InsTech's Zoja Wojcik reflects on the developments that have shaped the market since InsTech's first Agentic AI event in November 2025. Drawing on conversations with insurers, brokers, MGAs, technology providers and industry leaders, she explores how the industry has moved beyond experimentation and towards a more challenging question: where does the commercial value actually come from?  Along the way, you'll hear insights from Simon Torrance, Erdal Atakan, Gina Gill, Elena Maran, Max Richter and Ian Thompson, alongside examples of how organisations including CFC, McGill & Partners, AIG, Duck Creek and hyperexponential are bringing Agentic AI into real insurance operations.  Whether you're still trying to understand what Agentic AI means for insurance or already evaluating deployment opportunities, this episode offers a practical snapshot of where the market stands today and the questions leaders should be asking next.  Want to continue the conversation? Join us in London on July 7 for 'The age of Agentic AI: from strategy to commercial value'. In this episode:  00:00 - What is Agentic AI and why has it become one of insurance's most discussed technologies?  03:15 - Looking back at the industry's first major Agentic AI event in November 2025  05:45 - Simon Torrance on why Agentic AI should be viewed as a new workforce, not simply another software tool  06:20 - Early deployment examples from across the insurance market:  CFC's Lane Assist   McGill & Partners and Salesforce Agentforce   AIG's AI-driven underwriting initiatives   Federato's agentic underwriting platform   hyperexponential and Banyan Risk   Duck Creek's insurance-native Agentic AI platform   08:15 - Why moving from pilot projects to production remains difficult  10:00 - The defining question of 2026: proving commercial value and ROI  12:15 - Intelligence Capital, competitive advantage and why buying AI tools may only create parity  13:30 - Orchestration, governance and maintaining trust in agentic systems  15:00 - Workforce transformation and practical lessons for insurance leaders  16:00 - What questions should insurance organisations be asking next?  Key takeaways:  The industry conversation has shifted from experimentation towards implementation and measurable business outcomes.   Many of the biggest barriers to adoption are organisational rather than technical.   Boards increasingly expect clear economic justification for AI investment.   Competitive advantage may come less from AI models themselves and more from institutional knowledge and decision-making expertise.   Governance frameworks must evolve alongside increasingly autonomous systems.   Organisations that focus on specific business problems are more likely to succeed than those pursuing AI for its own sake.   Featured contributors:  Simon Torrance, AI Risk   Erdal Atakan, Inigo   Gina Gill, Apollo   Elena Maran, Alethesis AI   Max Richter, Mea platform   Ian Thompson, IMT Advisory  Further reading:  For listeners looking to explore the themes discussed in this episode:  Agentic AI & insurance  Podcast episode: Where is the industry today? – a view from the C-suite (A rare C-suite perspective on Agentic AI: what it is, how it's being deployed and why senior leaders are walking a tightrope between bold innovation and operational risk.)  CFC launches Lane Assist, a live agentic underwriting pilot  McGill & Partners becomes first London Market broker to deploy Agentic AI  McGill + AIG collaboration using AI-driven underwriting  Duck Creek launches insurance-native Agentic AI Platform  Federato RiskOps and Agentic underwriting platform  MGA Banyan Risk deploys hx's full agentic underwriting suite  Strategy & commercial value  Simon Torrance's work on Intelligence Capital   AI Risk research on Agentic AI and enterprise transformation   InsTech & ServiceNow New York event: The future of insurance will be orchestrated, not built  Governance & Responsible AI  Article: The New Frontier: Managing and insuring generative and agentic AI risks with Edinburgh Futures Institute  Podcast episode: Creating a new kind of assurance & insurance framework for AI-related risks (This episode unpacks one of the most ambitious research initiatives currently shaping the future of AI risk in insurance.) 

What if the future of marketing isn't about creating better campaigns, but about designing intelligent agents that render campaigns obsolete?Agility requires not just adapting to new technologies, but fundamentally re-architecting our operating models to harness their potential. Today, we're going to talk about the move from personalization to agentic experiences and what that means for enterprise marketing.We'll cover:- How “agentic experiences” are moving beyond simple personalization to fundamentally change the economics of customer acquisition and retention.- The shift in talent and technology required, moving from managing campaigns to orchestrating AI agents across the customer journey.- The practical first steps for building an “agentic foundation” within a complex enterprise environment, focusing on governance and core systems.To help me discuss this topic, I'd like to welcome Kathleen Managing Director of Marketing and Anuj Mathur, Managing Director of CX Transformation at BrillioAbout Kathleen Ulrich Kathleen Ulrich is Managing Director of Marketing at Brillio, where she leads the company's global marketing strategy and brand growth. She oversees brand, content, digital marketing, social media, corporate communications, analyst and media relations, research, and insights. Known for her multifaceted leadership, she brings together cross-functional teams around a unified vision, driving measurable impact across a rapidly evolving marketplace. Kathleen Ulrich on LinkedIn: https://www.linkedin.com/in/kulri/ ---------- Resources ---------- Brillio: https://www.brillio.com This episode is brought to you by Brillio. Founded in 2014 as a full-service digital transformation services and consulting firm, we apply our expertise in customer experience transformation, data analytics, artificial intelligence (AI), platform and product engineering, cloud infrastructure, and security to help customers quickly innovate for growth, create digital products, build service platforms, and drive smarter, data-driven performance. We strive to provide not only what the customers want, but also what they need. To us, success means leading our customers to better outcomes, and aligning our priorities so that we win when they win. We ensure that every individual is fully invested in the success of our customers. We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fDon't miss We Make Future - the International Festival of Innovation in AI, Tech, and Digital Marketing, June 24-26 in Bologna. Learn more: https://aglbrnd.co/r/c80991afff416bb2The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

Anthropic's new Claude Fable 5 is both the best model in the world and potentially one of the most dangerous.

Welcome to a special blockbuster compilation edition of The Edge of Show, broadcasting live from the ground at Consensus Miami! In this episode we sit down with four massive market leaders who are shifting emerging tech away from pure retail speculation and directly toward institutional-grade utility, RWA tokenization, and physical AI infrastructure.Join us with Evan Auyang, President of Animoca Brands, to discuss their historic fintech milestone: securing a rare regulated stablecoin license from the Hong Kong Monetary Authority alongside HSBC. Then we travel with Lin Dai, CEO of BookIt.com to show us details on how their system quietly processed $1.3 billion in travel volume using stablecoin backends without exposing regular consumers to crypto friction.Next Adam Levine, CEO of Fireblocks Financial Services, breaks down on why Wall Street "suits" are taking over the ecosystem and how AI wallets will soon pay for things autonomously. And finally we finish the episode with Till Wendler, CEO and Co-Founder of Peak, who successfully reveals they have tokenized an entire automated robotic vertical farm in Hong Kong. The future on finance is here at the Edge of show, don't miss this episode. Support us through our Sponsors! ☕ Want to make content like ours? Sign up with Castmagic to make your creative process easy: https://bit.ly/CastmagicReferral Work smarter, grow faster. Automate your SEO, get AI insights, and manage all your clients in one place with Helm. Start today 50% off your first month at helmseo.com

What happens when your AI ambitions collide with the reality of your infrastructure? Across boardrooms everywhere, agentic AI has quickly moved from experimental projects to strategic priority. The excitement is easy to understand. Business leaders see opportunities to automate workflows, improve decision-making, and increase productivity. Yet behind the headlines and product announcements sits a less visible challenge that many organizations are only beginning to understand. In this episode of Tech Talks Daily, I speak with Abby Strong, Chief Market Officer and Chief Customer Officer at Cribl, about the growing gap between AI ambition and operational readiness. Drawing on new research conducted with Harvard Business Review Analytic Services, Abby shares why so many organizations are struggling to move AI initiatives from pilot projects into production environments. The findings paint a fascinating picture. While almost every business leader surveyed views agentic AI as strategically important, only a small percentage believe they currently have both the strategy and infrastructure required to support it. At the heart of the challenge is data. As AI agents interact with systems, applications, and services, telemetry volumes are increasing at rates that many organizations never anticipated. In some cases, data volumes have doubled or tripled, creating unexpected infrastructure costs and operational complexity. Abby explains why telemetry, observability, and data management have become central to AI success. We discuss why AI systems are only as effective as the quality, accessibility, and context of the data available to them. She also shares real-world examples of how organizations are wrestling with growing infrastructure demands, rising costs, governance requirements, and the challenge of proving meaningful return on investment. Our conversation also examines the growing importance of visibility into AI activity. As enterprises deploy large language models and AI agents across their environments, security and observability teams are facing entirely new questions around monitoring, governance, compliance, and cost control. How do you establish a baseline when the technology itself is evolving so quickly? How do you maintain trust when AI systems generate vast numbers of automated queries and interactions? Abby offers a balanced perspective on what comes next. Rather than replacing existing systems overnight, many organizations are adding AI capabilities onto current workflows while gradually rethinking how work gets done. The result is a period of transition where businesses must support today's operations while preparing for a future that looks very different. If you're trying to understand why infrastructure readiness may become one of the biggest factors in AI success, this conversation provides valuable context. Are organizations focusing too much on AI models and not enough on the data foundations that support them? And what happens when the cost of AI adoption extends far beyond the AI tools themselves?