Podcasts about agentic

North Korea takes $387 million from Bitget and moves it through THORChain while NEAR's Shield freezes what it can, a Consensys validator hack tests whether staking was ever the risk-free rate, a quant named Benny shows Kalshi's perps volume was cooked, and Apollo warns that AI agents are coming for your checking account. Welcome to The Chopping Block, where crypto insiders Haseeb Qureshi, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This week the three of them record from a self-serve podcast studio in Amsterdam. Bitget loses 387 million dollars to North Korea's Lazarus Group and pays every claim from its user protection fund, but the stolen funds raise a harder question: THORChain lets them through while NEAR's Shield freezes them, so which one is actually decentralized? (Dragonfly is an investor in Bitget and NEAR.) Then a Consensys validator compromise tests staking as the risk-free rate, Robert prices insurance on US Treasuries at 35 basis points, a quant named Benny exposes Kalshi's perps volume, and the crew takes apart Apollo's warning about agentic bank runs, from Robert's one basis point checking account to Tarun's agent filing his insurance claims. Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Show highlights

Matt and Nic are back with another week of news and deals. In this episode:  Are OpenAI and Anthropic reenacting the Fat Protocol Hypothesis Will AI agents cause bank runs optimizing bank balances for yield? If the AI complex bursts does it take down VC? Our tribute to Hester Peirce as she retires from the SEC The SEC and CFTC publish crypto FAQs Vitalik lays out his vision for Ethereum in 2030 Quantum progress is accelerating Illinois delays their crypto transaction tax  Is San Francisco better than it was? 

Scott Sanborn is the CEO of Happen Bank, the company known until this summer as LendingClub. He is the first guest to appear on the show four times, and each visit has caught the company at a turning point. This time it is the rebrand: we talk about why the LendingClub name no longer fit, what six years of running a chartered bank has taught him, and how he is preparing for a world where AI agents shop for financial products on a consumer's behalf.What We CoveredTen years as CEO and why it has never been the same jobWhy the LendingClub name no longer fit the businessThe customer research behind the Happen Bank brandHow they will measure whether the rebrand is workingWhat it took to get a bank charter six years agoShepherds, not sheriffs: building the risk and governance teamLevelUp Savings, LevelUp Checking and DebtIQInnovating on the loan product with their own balance sheetThe balance sheet and marketplace mixThe switch to fair value accountingHow AI is changing operations and discoveryGetting ready for AI agents that shop on consumers' behalfHome improvement lending and home equityKey TakeawaysA brand is a promise, and the old name could not carry it. Customers told the company two things: they did not know it was a bank, and they did not want the word "lending" on a debit card that holds their own money. The rebrand waited until the product suite, and the financial returns, were there to back it up.The charter let them innovate more, not less. With its own balance sheet and a direct line to regulators, the company can test new loan terms and features like TopUp on its own portfolio, then bring investors the results a year later. It holds about 40% of originations on balance sheet.Simple incentives drive engagement. LevelUp Savings pays a 100 basis point rate kicker for depositing $250 a month. It has gathered billions in deposits, 20% of accounts come from borrowers, and borrowers who have paid off their loan hold an average balance of around $19,000 to $20,000.Agentic shopping favors lenders who already compete on value. Most Happen Bank customers already arrive through comparison sites, so Scott sees agents hunting for the best deal as a tailwind. The open questions are legal, such as what happens when an agent signs a loan disclosure.About Scott SanbornScott Sanborn has been CEO of Happen Bank, formerly LendingClub, since 2016, having joined the company in 2010 as Chief Marketing Officer. He led the acquisition of Radius Bank, the first time a fintech bought a chartered bank, and the 2026 rebrand to Happen Bank. Before LendingClub he held senior marketing and revenue roles at eHealth, RedEnvelope and the Home Shopping Network.Connect with Fintech One-on-One:Tweet me @PeterRentonConnect with me on LinkedInFind previous Fintech One-on-One episodes

Beyond the Shelf Live heads to Huntington Beach, where Dave Feinleib catches up with Nate Moran from Snowflake at the Retail Club AI Festival.Nate has gone from using retail technology on the brand side to working with the companies behind it. He shares what that switch has been like—and what caught his attention at the event. Agentic shopping is part of the story, but what about making life easier for the teams running the business? Nate sees plenty of opportunity there, too.Connect with Nate on LinkedInFollow Beyond the Shelf on LinkedInLearn More about It'sRapidGet the It'sRapid Creative Automation PlaybookTake It'sRapid's Creative Workflow Automation with AI surveyEmail us at sales@itsrapid.io to find out how to get your free AI Image AuditTheme music: "Happy" by Mixaud - https://mixaund.bandcamp.comProducer: Jake Musiker

In this episode of the AdTech Heroes podcast, Jon Wallett talks with Ashok Ganapam, President, AdTech and Monetization at MediaMint, about how agentic AI and data science are transforming decision-making in ad tech.They explore what agentic AI really means beyond the hype, how it's reshaping ad operations, engineering, and business intelligence, and what it takes for teams to adopt it successfully.Interested in being a guest? Contact us: adtechheroespodcast.com/contact

Dear Diary… "I use AI a lot to help scout out things or pose challenges and see where solutions are being marketed along those lines." Jeffrey Ostrander runs a nearly $5 billion business in one of the most dynamic supply markets on the planet. His team has left the starting block on agentic AI. What they are still deciding is how far into the race they want to run. That distinction runs through this whole conversation. Jeffrey talks about pilots that stumble, business cases that change daily, and a supply base of machine parts makers who are not sitting in front of a computer. Jeffrey is Head of North America Basin Supply Chain for SLB, the 100 year old company formerly known as Schlumberger. He returned to the same organization he started with 15 years ago, after time in global business services and other functions around the world. In this episode of The Agentic Procurement Diaries podcast, Philip Ideson and Jeffrey discuss: - Why sourcing and supplier performance sit in mirrored category structures, and how that builds a talent pipeline - The use cases already in play, from tail procurement to freight pay assurance and contract scouring - The "work-work balance" and why AI discovery has to be carved into paid time - Where he will not yet take the human out of the loop, and who is legally responsible when an agent makes the call Links: Jeff Ostrander on LinkedIn: https://www.linkedin.com/in/jeffrey-ostrander/ Zycus on LinkedIn: https://www.linkedin.com/company/zycus/  AOP Provider Directory | Zycus: https://artofprocurement.com/provider-directory/zycusinc  Subscribe to the AOP Newsletter: https://resources.artofprocurement.com/art-of-procurement-podcast-subscribe  Subscribe to Art of Procurement on YouTube: https://www.youtube.com/@ArtofProcurement   

Agentic commerce is changing not only where consumers shop, but who may be doing the shopping for them. As AI agents take on more of the discovery, comparison, and purchasing process, brands and retailers need to rethink how products are found and understood by both people and machines. In this episode, Liz Sertl chats with Kristen Rodgers, Director of Brand, Retail, Marketing and Advertising, and Sports Tech at Plug and Play. Kristen explains what agentic commerce means, how shopping has progressed from e-commerce to mobile commerce, social commerce, and now AI-assisted purchasing, and why consumers may be more willing to hand routine purchases over to an agent than emotional purchases that require more consideration. She also explains why brands need machine-readable product information as more consumers use tools such as ChatGPT, Perplexity, Claude, and Gemini for product discovery. The conversation also covers the shift from search engine optimization to generative engine optimization, or GEO, and how longer, more contextual AI prompts give brands new information about what consumers want. Kristen shares how AI storefronts could change product search on brand and retailer websites, why businesses still want to own the purchase and post-purchase experience, and how sports organizations are using technology to support the fan journey before, during, and after an event. She also discusses digital twins and synthetic data as tools for testing how audience segments may respond to marketing, product, and business decisions, along with the AI tools she uses in her own work.   In this episode, you'll learn: How agentic commerce shifts shopping from consumers searching for products themselves to AI agents helping discover, compare, and potentially purchase products on their behalf Why machine-readable product data and generative engine optimization are becoming more relevant as shoppers use AI tools for product discovery and recommendations How AI storefronts, digital twins, and synthetic data can help brands, retailers, and sports organizations better understand customer and fan needs and create more relevant experiences   Things to listen for: (00:00) Introducing Next Level Supply Chain (00:53) Kristen's background and her role at Plug and Play (03:09) How sports tech connects player performance, fan experiences, and stadium technology (04:12) How commerce moved from e-commerce to mobile, social, and agentic commerce (05:45) What agentic commerce is and how AI agents can shop on a consumer's behalf (07:29) The difference between functional and emotional purchases (09:20) Why brands and retailers need machine-readable product information (10:00) The shift from SEO to generative engine optimization (11:58) How AI storefronts could change product search and discovery (16:23) How sports organizations are thinking about the full fan journey (18:52) How digital twins and synthetic data can support audience research and decision-making (21:19) Consumer expectations around data and relevant experiences (22:32) Kristen's favorite technology (24:20) Why Kristen wants to learn more about vibe coding and building her own AI agent     Connect with GS1 US: Our website - www.gs1us.orgGS1 US on LinkedIn Connect with the guest: Kristen Rodgers on LinkedInVisit Plug and Play at https://www.plugandplaytechcenter.com/   

On this episode of Inside Business, we start with Ireland's economic outlook a week out from the Budget 2027 announcement. After years of consistent steady growth and running a surplus, what potential challenges await next year? Are we putting enough into the State's rainy-day funds?And why do developments with the US Federal Reserve have a clear impact on our economy?To discuss all this, host Cliff Taylor was joined in studio by Rossa White, Chief Economist at EY Ireland.In the second half of this episode, we look at agentic AI and why it has been making headlines for all the wrong reasons lately.Data breaches and deceptive behaviour have led to growing calls from AI leaders, including OpenAI CEO Sam Altman and Anthropic's Dario Amodei, for a more cautious approach to AI development and stronger safeguards. But why don't these companies know what their software is up to?And is proper regulation even a possibility at this point?Irish Times business and technology journalist Ciara O'Brien has been following these developments closely and she explained why agentic AI is giving big tech cause for concern.Produced by John Casey with JJ Vernon on sound. Hosted on Acast. See acast.com/privacy for more information.

AB sits down with Cisco's SVP and GM of Splunk, Kamal Hathi, to discuss how the combination of Splunk and Cisco technologies are providing the critical infrastructure for the AI era. From optimizing AI at scale to defending at machine speed to turning machine data into agentic action, this great conversation gives insight into how the combination of Cisco and Splunk technologies are driving the newest innovations in the agentic era.

Share Your ThoughtsMeet your invisible studio staff, the AI systems that could be handling your culling, client communications, and scheduling while you're behind the camera. Most AI tools you already use answer one question and stop. Agentic AI is different; it's built to take a whole string of steps toward a goal, with less of you checking in at every single one. In this episode, I break down what that actually means for a working photographer, using plain terms instead of hype.Here's what you'll get: a definition you can actually use, without the vendor jargon. A concrete corporate event walkthrough showing where an agentic layer could realistically touch your workflow, from culling and file routing to client communication and scheduling, without me pretending any specific tool can run all of it end to end today. And the line that matters most? The difference between automation that assists you and automation that quietly overreaches into decisions that should stay yours. I walk through a real failure-mode illustration, the kind of overreach that happens when a system grades on exposure and focus instead of story, so you know exactly what to watch for.Key points:Agentic AI takes multi-step action toward a goal, not just single-answer responsesThe label shifts fast across vendors, so treat this as a snapshot, not a permanent factThe real question isn't capability, it's oversight: does a task stay reversible if the system gets it wrongWhat overreach actually looks like: a system that makes the right technical call and the wrong storytelling oneA working decision framework: use it, test it, or wait, based on risk and reversibilityAny claim that AI "replaces" a photographer's judgment is opinion until proven otherwiseThis week's challenge: pick the part of your workflow you dread most, run one agentic tool against it, time the result, and keep a human checkpoint before anything reaches a client. One task, one timer, one honest answer.

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

What happens when companies deploy AI agents before fixing the data those agents rely on?In this episode of Riding Unicorns, James and Hector sit down with Toby Mather, Co-Founder of Rig, the AI-native data infrastructure company building the data layer that allows humans and AI agents to work from the same trusted context.Rig started as a "data brain" sitting on top of platforms like Snowflake and BigQuery, making sense of fragmented company data so teams could use tools like Claude and Cursor to build applications, automations and analytics. It has since expanded into an end-to-end data stack covering ingestion, warehousing and context.Toby explains why LLMs alone aren't the answer to enterprise data. While language models are excellent at understanding context, businesses still need deterministic systems like SQL and structured tables when they want accurate answers from their data. Rig's thesis is that AI should make sense of the complexity, but the underlying calculations still need to be grounded in reliable data.The conversation also explores the rush towards autonomous AI agents. Toby argues that many companies are trying to run before they can walk: connecting agents to dozens of fragmented systems without first creating the clean, consistent data infrastructure they need. Get the context right, and the journey from human-in-the-loop to autonomous agents becomes much easier.Topics Covered• Why AI agents need better data infrastructure• Building a "data brain" for humans and AI agents• Why LLMs aren't always good at data reasoning• Why 55-year-old SQL and tables still matter in the AI era• Moving from human-in-the-loop to autonomous agents• How Rig uses Rig to run its own business• Building agentic workflows across CRM and customer success• Toby's lessons from building and selling Lingumi• Why founders should choose enormous markets• Landing major enterprise customers as an early-stage startup• The PULL framework for B2B sales• How to sell enterprise software without becoming a services business• Competing with incumbents like Snowflake and Databricks• Balancing customer feedback with founder-led product intuition• Why agentic customer success could be a major opportunityToby also shares some of the more surprising ways customers are already using Rig, from identifying overpayments hidden across thousands of invoices to building AI-powered customer success systems that identify problems and proactively contact customers.This is a conversation about the infrastructure beneath the AI agent revolution: getting company data into the right shape, giving AI the context it needs and building the foundations required for truly autonomous work.

In this episode, we dive deep into the world of agentic AI and its transformative impact on industrial organizations - thanks to Jana Kirchheim from Microsoft. We share fresh insights from our conversations with industry leaders on how hyperteams—blending humans and AI agents—are changing the rules of leadership, governance, and knowledge management. You'll hear practical examples from companies like Bayer and discover how even mid-sized firms can harness agents for real business value. We discuss the challenges of orchestrating thousands of agents, building effective governance, and capturing critical tacit knowledge before it disappears. Join us as we explore what it takes to be brave, adapt, and thrive in the era of superintelligent industrial AI.

For episode 777 of the BlockHash Podcast, host Brandon Zemp is joined by Kenneth Shek, CEO at Moca Network and Managing Director at Animoca Brands.Kenneth leads the Moca Network, Animoca Brands' identity ecosystem, building decentralized identity infrastructure across a network spanning more than 500 portfolio companies and 700M+ addressable users, and can discuss AI agents and digital identity, the future of online trust, agentic commerce, and why identity will become a foundational layer of the AI-powered internet.

Ist das klassische Kernsystem tot, jetzt wo KI ganze Prozesse selbst bauen kann? In dieser Folge diskutieren wir mit Sven Schlünzen (Managing Director) und Jochen Wehr (Business Unit Lead Client & Partner Management) von adesso insurance solutions, warum Bestandssysteme und Agentic AI kein Widerspruch sind – sondern der neue Standard.Wir sprechen über den "Agentic Layer", der KI-Agenten mit Kernsystemen verbindet, warum Deterministik für BaFin & EU AI Act entscheidend ist, wie ein Schadenprozess heute schon vollautomatisiert abläuft – und warum das bis zu 35 % Effizienzgewinn und 4 Prozentpunkte Combined-Ratio-Verbesserung bringen kann. Plus: Wird der Sachbearbeiter zum Supervisor eigener KI-Agenten?Jetzt reinhören – für alle, die wissen wollen, wie KI die Versicherungsbranche wirklich verändert.Schreibt uns gerne eine Nachricht! Hier geht es zur PTA Stelle "Business Analyse Versicherung (m/w/d)!Jetzt mit dem Code "Monday" 10% auf Deinen Plaud Pro sichern!Folge uns auf unserer LinkedIn Unternehmensseite für weitere spannende Updates.Unsere Website: https://www.insurancemondaypodcast.de/Du möchtest Gast beim Insurance Monday Podcast sein? Schreibe uns unter info@insurancemondaypodcast.de und wir melden uns umgehend bei Dir.Dieser Podcast wird von dean productions produziert.Vielen Dank, dass Du unseren Podcast hörst!

In episode 260 of the 6G Podcast, Anshel Sag recaps Qualcomm's Hawaii summit, where the key theme was agentic computing and announcements included Snapdragon 8 Elite Extreme Gen 6 (plus a non-extreme flagship), Snapdragon Sound Elite Gen 2, Microsoft Surface devices with Snapdragon X2 Plus, and an X105 modem described as Release 19 compatible, alongside partnerships supporting on-device AI amid memory constraints. Mike Danil summarizes an Ookla report on U.S. fiber ISPs during a consolidation “land grab,” citing major deals (Verizon–Frontier, AT&T–Lumen fiber, Zayo acquisition) and highlighting smaller providers to watch: Allo Fiber, Gateway Fiber, Live Oak Fiber, Wire3, Ripple Fiber, Intrepid Fiber, and Easy Fiber. They discuss Google's Project Sun Catcher to test TPUs in space and the growing plausibility of space data centers, then cover 3GPP's Madrid meeting where decisions on 5G-to-6G migration (MRSS spectrum sharing and other deployment options) were deferred to December in Boston. The episode also touches on a new Apple–Qualcomm licensing agreement and Meta's Muse consumer AI agent, including early friction when agents interact with service-provider chat systems. 00:00 Welcome and Introductions 00:35 Qualcomm Summit Highlights 03:17 On Device Versus Cloud AI 06:14 US Fiber Land Grab 09:14 Fiber Competition Trends 11:08 Google TPUs in Space 14:28 3GPP 6G Migration Debate 19:37 Qualcomm Apple Licensing Deal 22:18 Meta Muse AI Agents 28:07 Wrap Up and Farewell

In today's MadTech Daily, we discuss 58% of ad executives expecting agentic buying to scale within a year, Apple and Amazon facing a renewed UK consumer case, and A24, Sony and The New York Times circling Letterboxd.

Performance is getting harder to ignore, and Tomás argues that AI is making the problem urgent in ways most teams are not ready for. He explains why AI-generated code, exploding system surface area, and rising infrastructure costs are creating a perfect storm, and why Perfloop exists to turn performance engineering into a rigorous, automated science.Tomás, the creator of Perfloop, breaks down how the product maps your codebase and telemetry into a living model of your system, then hunts for performance anti-patterns with a verification harness that puts every hypothesis through measured, repeatable experiments. Instead of relying on a freestyle coding agent, Perfloop uses structured discovery, deterministic checks, and adversarial verification to produce results you can actually trust.Chapters:00:00 The performance problem behind Perfloop00:39 Why performance work is a battle03:59 How AI agents raise the stakes08:55 Quality control at the scale of agentic development10:34 How Perfloop maps systems and finds opportunities14:32 Using telemetry to prioritize hot paths18:13 Perfloop's open-source performance wins22:18 How Perfloop measures and verifies improvements25:11 Common performance patterns and bottlenecks28:47 The “apex hunt” for bigger architectural gains30:58 Initiatives and setting high-level performance goals35:21 Connecting code optimizations to customer impact39:59 Why independent verification matters44:36 Choosing the right AI models for each task49:45 What a harness does in Perfloop53:59 The possibility of pre-merge performance reviews57:24 How AI may change the role of performance engineers63:54 Why performance requires measurementImportant links:Patterns: https://app.perfloop.ai/t/oss/patternsPerfloop: https://app.perfloop.ai/t/oss/startFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

In this episode of HFS Unfiltered, David Cushman speaks with EY's Dan Diasio and Thiru Vengadam about what it takes to move from AI experimentation to enterprise-scale agentic operations. Drawing on EY's recognition as a Horizon 3 Market Leader in the HFS Horizons Agentic Services 2026 report, they discussed why the biggest barriers to AI adoption are no longer technology, but business transformation, governance, operating models, and workforce readiness. The conversation explores how organizations can move beyond proof-of-concept projects by embedding AI into core business operations, building trusted agentic systems with strong governance, and adopting outcome-based partnerships. They also discuss the evolution of Services-as-Software™, where AI-enabled services are creating new business value by combining software, human expertise, and continuous innovation.Key takeawaysAI success is a business transformation challenge, not just a technology one.Scaling AI requires rethinking operating models, processes, data, governance, and talent.Agentic AI must be built on trust. Governance, security, auditability, and human oversight are essential for deploying enterprise-scale AI systems.Partnerships are evolving. Organizations need deeper co-development and outcome-based collaborations rather than traditional vendor relationships.Services-as-Software™ is reshaping enterprise services. AI enables organizations to combine software with human expertise to deliver new, higher-value outcomes.The future belongs to enterprises that embed AI into operations, not just experiments.Sustainable value comes from integrating AI into the way work is designed and delivered.Learn more about the 2026 HFS Horizons: Agentic Services report, which assesses how effectively 36 service providers help enterprise clients adopt agentic AI and realize value across three distinct Horizons, here.#AgenticAI #AgenticServices #EnterpriseAI #ServicesAsSoftware #AIOperatingModel #EY #HFSResearch #AIGovernance #DigitalTransformation #FutureOfWork

Erick opens with the good news: Iran's economy is collapsing under U.S. sanctions and a naval blockade of the Strait of Hormuz, with Secretary of Energy Chris Wright, U.N. Ambassador Mike Waltz, and President Trump all detailing the pressure campaign as gas and diesel prices start easing on returning refinery capacity. He also covers SpaceX's […]

Getting started with Claude Code and agentic AI doesn't require a technical background, as Henry Lopez and applied AI specialist Colin Rhoades explain the shift from AI chatbots to AI agents that complete tasks for your small business. Show Notes Page: https://www.thehowofbusiness.com/622-claude-code-agentic-ai/ You don't need a technical background, or to have ever written a line of code, to get started with agentic AI. Henry Lopez is joined again by his son-in-law Colin Rhoades, a corporate AI and data analytics specialist, for a primer on the shift from AI chatbots to AI agents that can actually get work done for your small business. Most business owners have tried ChatGPT, Claude Chat, or Gemini by now, and those tools are genuinely useful.  But there's a newer, less familiar layer: Agentic AI, tools that don't just answer a question but go do the work to implement it. Understanding the difference, and knowing how to take the first step, matters right now, because the businesses that start experimenting are the ones that will get the leverage first. Colin's analogy captures the shift well: chatbot AI is like having a very smart consultant or research assistant at your fingertips, while agentic AI is more like giving that consultant a desk, access to your tools, and an assignment to go do. An AI chat gives you answers. Agentic AI gets things done. The clearest example in the episode is Henry's daughter Makena's business, Final Curtain Finishing, a needlepoint finishing service with a Shopify ecommerce site. Native Shopify isn't built for configured products, so the site needed custom HTML code. Makena has no coding background, but using ChatGPT and then Claude Code, she generated that code herself with plain English instructions. This was work that otherwise would have cost thousands of dollars in outside development. Now that Claude Code is connected directly to her Shopify account through a connector, it can read the site's configuration and make changes on its own based on her instructions. That connection is the real unlock: Agentic AI plugged into or connected to your systems (a CRM, email, a Shopify store, QuickBooks) can do its own lookups and extracts instead of you exporting reports and pasting screenshots into a chat window. Colin saw this firsthand the first week he connected Claude Code to his company's CRM: the manual process of finding a report, exporting it, and cleaning the data disappeared, and he could go straight to deciding what the data meant. But getting started doesn't mean diving in blind. Henry and Colin both stress starting with controlled access and a human in the loop, the same way you'd onboard a new employee, and expanding autonomy only as trust builds. As Colin put it, "the goal isn't AI can do everything, it's having an AI that you can trust to do one defined task well." And getting started is simpler than it sounds: pick one repetitive task you already understand, document it (even just by speaking it into Claude), and teach the AI that one process first. This episode is hosted by Henry Lopez. The How of Business podcast focuses on helping you start, run, grow and exit your small business. The How of Business is a top-rated podcast for small business owners and entrepreneurs. Find the best podcast, small business coaching, resources and trusted service partners for small business owners and entrepreneurs at our website https://TheHowOfBusiness.com

In this episode of The Circuit, Ben Bajarin and Jay Goldberg explore the evolving dynamics of the semiconductor memory market, consumer AI agents, and critical compute infrastructure. The hosts begin by analyzing the aggressive capacity expansions and yield improvements of Chinese memory providers YMTC and CXMT, discussing how their growing output might provide pricing relief for consumer electronics OEMs currently squeezed by massive data center demand. The conversation then pivots to Meta's new "Muse" AI assistant, which the hosts view as a potential catalyst for mainstream AI adoption that could bridge the user skill gap by acting as a proactive personal and enterprise orchestrator. Finally, they unpack Anthropic's $11 billion equity-exchange partnership with Akamai, highlighting its implications for distributed edge inference and the massive, unforeseen surge in CPU demand required to power these continuous "agentic" workloads.

If you have a gaming computer with about 6 gigabytes of dedicated VRAM you can run an open source LLM using Bionic from LM Studio for free and actually get very useful work done. It quickly changes the way you use and how you even think of your computer as a productivity tool. Agentic computing is the next wave of computing.

In this episode, Lex chats with Simon Taylor, who heads up market development at Tempo, the payments-native blockchain built by Stripe as a high-performance settlement layer for stablecoins and tokenized money. Simon is also the founder of Fintech Brain Food, one of the sector's most widely read newsletters. They discuss why there is no Fedwire for the internet, and why the next wave of on-chain volume is coming from enterprise money movers like Deel rather than crypto-native builders. Simon explains why tokenized deposits, stablecoins and TradFi settlement will converge on a single chain, why agentic commerce is still stuck in its WAP-phone era, and how the Machine Payments Protocol is being designed as an IETF-grade standard that can settle across Tempo, Stripe or any card network.NOTABLE DISCUSSION POINTS:The AI productivity gap is an operating-model gap, not a tooling gap. MIT found nine in ten companies get zero productivity gain from AI, while Ramp's own data shows the heaviest users generate 2x higher revenue on 40% less capital. What separates them is four ingredients: AI evals as a cultural default, a shared library of skills (Ramp has 350+), non-engineers shipping production code (12% of Ramp's human-initiated PRs), and treating AI fluency as the primary staff learning curve.Agentic commerce is in its WAP-phone era. Nobody is actually paying for things with agents at any scale - Walmart's ChatGPT checkout converts worse than its dotcom, Target has told customers they are 100% liable for anything an agent buys, and Walmart and Amazon block third-party agents outright as fraud. The real volume is in B2B finance teams automating PDF-invoice-to-payment flows through Ramp and Brex, which is where Machine Payments Protocol and x402 will first find product-market fit.On-chain cash settlement is less than 0.1% done, and Tempo is being positioned as the missing Fedwire for the internet. The pitch is not a new L1 competing on TPS benchmarks - it is a settlement layer designed by payments veterans who understand that payments are all edge cases, with permissionless issuance combined with opt-in receive policies (TIP-20 upgrades on ERC-20, block/allow lists, embedded compliance) that let enterprises finally clear their RFP checklist.TOPICSFintech, Stablecoins, Tokenization, DigitalAssets, Payments, Settlement, RWA, DeFi, TradFi, CapitalMarkets, AgenticCommerce, AgenticPayments, AIAgents, MachinePayments, Ethereum, Canton, Blockchain, Web3, Tempo, Stripe, Anthropic, Ramp, Brex, Deel ABOUT THE FINTECH BLUEPRINT

AI isn't just changing how we use software, it's changing who software is built for.In this episode of Lessons in Product Management, John Fontenot sits down with Kimberly Logan, Head of Product at the Walrus Foundation and former Google leader, to explore the evolution of product leadership and what happens as AI agents increasingly become users of software themselves.Kim shares lessons from her transition from technical program management into product leadership, including the shift from focusing on execution and the “how” to owning the “what” and “why.” They also discuss product-market fit, building better customer feedback loops, prioritizing under resource constraints, and how AI can make strong product managers even more effective.Then the conversation turns toward the emerging infrastructure of an agentic world: persistent AI memory, data ownership, portability between AI systems, verifiability, and the trust problems that arise when agents begin operating across organizational boundaries.What does product management look like when intelligence becomes cheap, but trust becomes increasingly valuable? That's the question at the center of this conversation.Outline:00:00 — Introduction & Kimberly Logan's background 01:29 — From Technical Program Manager to Product Leader 05:15 — Making the transition into Product Management 07:10 — Skills aspiring PMs should develop 09:40 — AI as a force multiplier for Product Managers 10:35 — Is AI a tool or a fundamental technological shift? 12:31 — What happens when AI agents become the users?13:58 — What is Walrus?15:26 — Why your data becomes more valuable in the AI era 17:40 — Portable, programmable & verifiable data18:44 — Solving AI platform risk with portable memory 20:47 — Verifiable AI memory21:50 — Where AI memory is being used today24:44 — Finding real Product-Market Fit 26:18 — How do you prioritize with limited resources? 28:32 — Ruthless prioritization & product trade-offs 30:16 — Where AI goes next 31:45 — The cross-company trust problem for AI agents

If you have a gaming computer with about 6 gigabytes of dedicated VRAM you can run an open source LLM using Bionic from LM Studio for free and actually get very useful work done. It quickly changes the way you use and how you even think of your computer as a productivity tool. Agentic computing is the next wave of computing.

If you have a gaming computer with about 6 gigabytes of dedicated VRAM you can run an open source LLM using Bionic from LM Studio for free and actually get very useful work done. It quickly changes the way you use and how you even think of your computer as a productivity tool. Agentic computing is the next wave of computing.

Copilot, assistant, agent — the terms get thrown around interchangeably, but they describe three very different levels of AI autonomy. So where does agentic AI actually belong in the configure-price-quote process, and where should humans stay firmly in control? In this episode, Frank sits down with Sourabh Kukar, Director of Technical Consulting at Salesforce, where he leads a team of enterprise architects working across Revenue Cloud, Agentforce Revenue Management, CPQ, and H&A solutions for large enterprise customers. Sourabh was named Salesforce's FY24 CMT Technical Architect of the Year, holds 23 industry certifications, and is an IEEE Senior Member. Sourabh brings a rare mix of backgrounds to the conversation — starting as a Java developer, spending a decade as an integration architect, then moving deep into the Salesforce platform in 2019. That combination of coding roots, systems breadth, and platform depth shapes how he thinks about which parts of quote-to-cash are ready for real AI autonomy and which still need deterministic guardrails and human sign-off. Frank and Sourabh also dig into how to architect multiple specialized agents so one agent's bad output doesn't become another agent's bad input, why fixing your data and simplifying your processes matters more than the AI layer itself, and what changes for revenue operations teams as quoting and approvals move into conversational tools like Slack. In this conversation we cover:  The real difference between a copilot, an assistant, and an agent — and where Salesforce's Agentforce quoting agent fits Which parts of configure-price-quote are ready for high AI autonomy, and where humans need to stay in the loop How to architect multiple specialized agents so errors don't cascade downstream Why fixing your data and simplifying your processes matters more than the AI layer on top What changes architecturally when quoting and approvals move into Slack A practical framework for choosing phased coexistence over a full CPQ-to-Revenue-Cloud migration If you're a Salesforce CPQ customer evaluating a move to Revenue Cloud, an enterprise architect thinking through agentic AI governance, or a revenue operations leader trying to separate real AI capability from hype, this episode offers grounded, practitioner-level insight from someone building these systems for enterprise customers every day. Learn more: Sourabh Kukar on LinkedIn Don't forget to subscribe on YouTube and your favorite podcast platform.  More CPQ research and resources at https://novuscpq.com

Daniel “Dazza” Greenwood is the founder of CIVICS.com, a boutique provider of professional consultancy services for legal technologies, automated transactions, privacy and data management, and technology strategy. Dazza is also a researcher at MIT Media Lab and Lecturer at MIT Connection Science where he has been advancing the field of computational law and generative AI for law as Executive Director of law.MIT.edu.Our guest serves as lead on the Data Rights Protocol initiative through Consumer Reports Digital Lab. This protocol provides a common open specification for enabling consumers and companies to process the exercise of individual data rights as a consumer-connected digital service.Dazza Greenwood consults to Fortune 100 companies, architecting and building integrated business, legal and technology cross-boundary networks at industry scale. As an attorney, he served as both in-house and special counsel for technology law, representing corporations and governments. He has also testified before the US House, US Senate and other legislatures on electronic transactions law and consults extensively to the public sector.References:* Dazza Greenwood on LinkedIn* Dazza Greenwood's Substack* CIVICS.com* Data Rights Protocol: Standardizing consumers' data rights requests (Consumer Reports)* Uniform Electronic Transactions Act (1999)* Authority Boundaries for AI (Dazza Greenwood, May 2026)* LQAI from LegalQuants on Github (open source platform for law firms)* Thirteen Words Shape Legal AI (Dazza Greenwood, September 2026)* MIT Computational Law Report - Now part of Stanford Law School* HOPE Lab, Hands-On Projects and Experimentation: Learn to work with agents across multiple stages, with clear goals, boundaries, and evidence of what worked.* Interlateral (“Bring your own agent”), run by Dazza Greenwood: A space where people and their AI agents meet, coordinate, and build together over the web.* Jamie Smith: AI Agents, digital identity, wallets and personal data (Masters of Privacy, December 2024). This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mastersofprivacy.com/subscribe

Mark Zuckerberg says Meta's AI agent, Muse, needs to be discreet. The same month, some of the calls it made to businesses were placed by people in a call center. I went through what he told Joanna Stern and Alex Heath about Muse's privacy and security and sorted every claim by tense. What exists today, only Meta has checked. The protection from Meta itself is promised for later this year. My verdict: stay away from this. After the sign-off, the show moves to Saturday mornings.Chapters00:00 - Discreet AI, and calls made by people00:59 - What Muse is, and the agentic web02:33 - Joanna Stern's question03:57 - Present tense: the virtual machine and the ads05:45 - Passwords, Sentinel, Amazon and the Mac app07:05 - Future tense: the locked version and discretion10:10 - Who is asking: an ad company with a privacy record11:40 - From the browser wars to the agent wars14:42 - Two documents, 1993 and 202616:00 - After the episode: moving to SaturdaysKey Numbers500,000+ people tried Muse in its first week, as reported by The Information97.6% of Meta's 2025 revenue came from ads$5 billion: the FTC's 2019 privacy penalty on Facebook87 million people's data reached Cambridge Analytica1993: CERN put the web's code in the public domain"Later this year": when Meta says the version it cannot see inside arrivesKey TakeawaysListen for the tense. What Muse does today is described only by Meta, and nobody outside Meta has published a check of it. The version Meta itself cannot see inside is promised for later.Meta's plan for Muse is a small cut of every transaction. Zuckerberg said the cut will come from the businesses. If you run a store, that is you.The early web worked because it was given away and ran on your own computer. This time the companies want to be in the middle from day one. It is the browser wars again, fought over the agent.What to DoBefore you connect your email, passwords or card to any agent, ask how it works today, in the present tense.If you run a store on Shopify, check Sales channels, then Agentic. Meta's agent and Google's AI may be on by default.Watch the full Joanna Stern interview.The No Hacks newsletter is at nohacks.co/subscribe.Sources & LinksThe interviewsJoanna Stern, New Things with Joanna SternAlex Heath, Sources podcastMeta's own wordsIntroducing MuseMeta's 2025 annual reportThe recordFTC, $5 billion penaltyCERN, 30 years of a free and open webNo Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit

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

Apex Fintech Solutions provides the tools and services that enable hundreds of clients to launch, scale, and support digital investing for tens of millions of end investors. The company provides essential infrastructure and a comprehensive ecosystem of cloud-based products to enable and streamline trading, wealth management, cost basis, tax reporting, and, through its subsidiary Apex Clearing™, custody and clearing. LEARN MORE HERE Checkout Gary's Substack: https://garymarcus.substack.com/ Jim Chanos returns, this time with AI researcher/professor emeritus Gary Marcus. The two join Dan to discuss AI's build-out technology, economics, and risks. Marcus argues modern LLMs lack durable technical moats, remain unreliable and hallucination-prone, and are becoming commoditized, driving token price wars and challenging profitability for OpenAI/Anthropic; he favors neurosymbolic approaches and warns that “agent” systems are causing serious security incidents, saying OpenAI should be temporarily shut down or put into receivership until fixed. Chanos explains his bearish focus on data centers as capital-intensive, low-return “equipment leasing” businesses being marketed like REITs, with hyperscaler incremental returns declining and credit tightening. They compare the AI cycle to late-1990s TMT, discuss NVIDIA's unique position versus its customers, highlight IPO/financing as a potential breaking point, and debate regulation, surveillance “dystopia,” and political risks. —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

SharpLink CEO Joseph Chalom breaks down why Ethereum becomes the settlement layer for the A.I. agent economy after Meta unveiled Muse. We cover agent payments, stablecoins, and what this means for ETH holders.~This Episode is sponsored by Ether.Fi~Join Ether.Fi and Earn cashback on trades of tokenized stocks and more!➜ ether.fi/@paulbarronGuest: Joseph Chalom, CEO at SharplinkSharplink website ➜ https://bit.ly/SharplinkETH00:00 Intro00:10 Sponsor: EtherFi01:00 Meta MUSE01:40 A.I. article02:10 How could Ethereum win vs Meta?04:00 Meta training for the agentic future05:45 Mark Zuckerberg sparks another meme season06:30 If Agents dont need ENS why would they need eth payment rails?09:25 Why wouldn't Meta and others build their own blockchain?11:40 Will anyone trust Meta privacy features?14:00 Explain ERC-800416:15 12 month agent outlook18:45 Chains will be Hubs of expertise?20:25 Middlemen already taken over most of AI workflow?22:45 Qualcomm Snapdragon for A.I. mobile phones23:50 Why has ETH allowed zCash to takeover the privacy narrative?25:25 A.I. Agent Memecoins paired with Tokenized Stocks potential?29:30 TradFi vs degens ecosystem31:00 Is Uniswap the true winner?33:10 Entering Tokenization Flop Season?36:00 Consumer flexibility vs KYC#Meta #AI #Crypto~Meta Muse A.I. Agents Need ETH

Jfrog CEO Shlomi Ben Haim sits down with Mandeep Singh, Bloomberg Intelligence's global head of technology research, ahead of their swampUP 2026 event. The evolving software supply chain, driven by AI-agent deployments, MCP servers, and reusable skills, is emerging as a major trend that could reshape the broader DevOps market. They also discuss the security vulnerabilities with increasing model capabilities and the OpenAI-Hugging cyber incident. 

In today's Cloud Wars Minute, I unpack Workday's move toward agentic contract lifecycle management and greater workflow automation.Highlights00:03 — Workday has announced that its next mission is to bring agentic AI across the entire contract lifecycle, instead of just AI for individual contract-related tasks. The company is launching the Workday Contract Workflow Agent, which is now in early access.00:22 — But before I get into that, I want to share some other findings that kind of support Workday's intentions here. The company recently conducted a survey of nearly 7,000 professionals and found that 89% said their organizations routinely absorbed financial losses from vendor contracts that auto-renew without anybody's knowledge.00:44 — So, to support this and other processes across contract creation, negotiation, execution, management, compliance, and renewal, the company has launched the Workday Contract Workflow Agent, which is one of a series of major enhancements coming to Workday Contract Lifecycle Management, or CLM, and described as the 'beginning of a new era of agentic CLM."01:09 — The overall goal is to automate more of the manual work involved in managing contracts, connect those tasks with broader business workflows, and it really chimes with Workday's wider vision, which is to embed agentic AI into enterprise workflows, rather than treating AI as a separate tool.01:31 — I think that's what makes the company's approach particularly interesting in the enterprise AI space. It's not just about giving employees another AI assistant, but about embedding agents directly into the workflows that run the business. Visit Cloud Wars for more.

Robert Smallwood speaks with cybersecurity and data privacy expert Michael Esola about the growing need for practical AI governance. Michael shares insights from his new book, Governance at the Speed of Autonomy, and introduces the CORE framework—Context, Oversight, Responsibility, and Elasticity—for managing the risks of AI and agentic AI.They discuss shadow AI, data-loss prevention, audit readiness, critical infrastructure risks, and how quantum computing may reshape cybersecurity. The episode also previews Michael's upcoming sessions at the AI Governance World Conference in Las Vegas, where he will explore AI governance, cybersecurity, and data privacy in greater depth.

AI Agents Can Automate More Of Your Business Than Ever Before, But That Does Not Mean Humans Are Out Of The Equation In this episode of The Complete Entrepreneur, Colin C. Campbell, Michael Gilmour, Michele Van Tilborg, and members of the Startup Club community explore what happens when AI agents can begin handling work traditionally performed by employees, consultants, accountants, lawyers, and developers. From automating customer support and bookkeeping to qualifying leads, reviewing contracts, analyzing data, and running workflows around the clock, the conversation looks at how entrepreneurs can use agents to reduce repetitive work and dramatically increase the capabilities of smaller teams. More importantly, they discuss why adopting an agentic mindset is not simply about replacing people. It is about redesigning work, keeping humans involved where judgment and creativity matter, and helping employees move toward higher-value roles that AI cannot easily replicate. What it means for entrepreneurs to develop an agentic mindset How AI agents can automate repetitive business operations around the clock Why accountants, lawyers, consultants, and other service providers need to rethink how they create value How founders can use AI to reduce costs while increasing the capabilities of their teams Why human oversight remains critical when agents handle financial, legal, or operational work How AI can augment strong employees instead of simply replacing them Why time management, project management, and problem-solving will become increasingly valuable human skills How founders can design AI workflows that preserve human judgment, creativity, and accountability

What does a security operations center need when attacks are arriving at a speed and volume that human analysts cannot manage alone? I recorded this episode with Adam Khan, VP of Global Security Operations and AI Security at Barracuda, during the 20th anniversary of the Barracuda Tech Summit in Alpbach, Austria. Adam has spent over 25 years in technology and security. When we last spoke at the event, he used Home Alone and soccer to make complex security topics easier to understand. This year, expectations were high, and he arrived with Formula One. The comparison begins with what spectators see. Attention naturally falls on the car and driver. Behind them sits a much larger operation involving engineers, strategists, mechanics, simulations, telemetry, and rapid decisions. Adam believes modern security works in a similar way. Customers want to run their businesses, while a largely unseen combination of analysts, threat intelligence, automation, and AI works behind them. That operating model has developed into what Barracuda calls the Agentic SOC. AI agents follow the same playbooks analysts use when examining endpoints, malware connections, artifacts, threat intelligence, identity behavior, and other signals. They can complete repeatable investigative work quickly and consistently across volumes that have grown from hundreds of alerts to thousands or millions. Adam says Barracuda now has hundreds of agents with hundreds of individual skills. These agents can support the process from triage and intelligence gathering through correlation and response. When the system has high confidence that an ordinary user account has been compromised, it may disable that account. If the incident involves an administrative account capable of locking down an entire customer environment, a person must confirm the action. This matters because an AI system can misclassify an event or reach a conclusion that requires additional context. Adam describes feedback mechanisms through which people review decisions, identify mistakes, and feed those findings back into the system. Barracuda also records an audit trail of the actions and queries performed by its agents. One of the most surprising details concerns employment. While headlines frequently associate AI with reducing headcount, Adam says his team has doubled since adopting it. Analysts previously occupied with repetitive investigation have moved into threat hunting, model development, prompt engineering, and attack and defense exercises. The team is also attacking its own systems so that its agents can learn from emerging techniques before a genuine incident occurs. The audience saw this operating model during Adam's keynote. Attendees used their phones to launch controlled business email compromise, QR-code phishing, and ransomware scenarios against Barracuda's attack and defense environment. The platform then analyzed and blocked the activity while the audience watched. Adam says approximately 395 attacks were initiated during the demonstration and all were successfully blocked. That result comes from a controlled Barracuda demonstration rather than an independent test, but it gave attendees a rare view of the speed required during an active incident. We also discuss how Barracuda Managed XDR uses behavior and telemetry across email, endpoints, cloud services, identities, networks, and other technology. An employee traveling with a familiar laptop and phone should not create the same response as an unknown device attempting an unusual login. Historical patterns, device identifiers, signatures, and location data can help reduce unnecessary alerts while highlighting activity that deserves attention. For Adam, the purpose of AI is to increase the speed and reach of security experts rather than remove them. People determine strategy, examine high-consequence decisions, test systems, and remain accountable for customer outcomes. Could the Agentic SOC give security teams the speed they need without surrendering the judgment and accountability customers expect? Listen to the episode and share your thoughts.

In this episode, PV Subba Rao, President, NTT DATA, discusses how agentic AI can improve revenue cycle outcomes, unlock cash and margin, reduce administrative burden and create capacity for broader health system transformation.This episode is sponsored by NTT DATA.

Michelle Beyo is the founder and CEO of Finavator, a consultancy that helps banks, fintechs, and corporates step into the future of finance. Her new book, Mastering the Future of Finance, just published this week by Wiley, breaks the industry into nine elements across data, trust, and technology. We talk about why she wrote it, why she believes there should be a human data right, and how she kept the AI chapter current in a market that moves every month.What We CoveredMichelle's path from telco and online shopping to prepaid infrastructure at InCommPiloting one of the first WeChat top-up tests at 7-Eleven in 2017Why she concluded the future of finance was being built in AsiaSurviving crypto winter at a blockchain startupWinning Money20/20 RiseUp and starting Finavator in 2019How Finavator works with banks, fintechs, and corporatesThe masterclass that led to a Wiley book dealThe nine elements of the future of finance across data, trust, and technologyOpen banking, open finance, and open data explainedThe case for a human data rightKeeping the AI chapter relevant as agentic payments took offEnding each chapter with a subject matter expert interviewKey TakeawaysNumber portability is the template for open data. Your phone number was the first piece of data you could take with you when you switched providers. Michelle sees open banking, open finance, and eventually open data as the same right extended to your financial life, and she wants it codified as a human data right at the ISO level, including the right to delete consented data.Trust is the core layer. In Michelle's framework, open data, digital identity, and cybersecurity with AML compliance sit at the center. Get that trust layer right and fintech, BaaS, and embedded finance can accelerate on top of it.Agentic payments are moving faster than the internet ever did. Memory, auditability, liability, and returns are still open questions. Until credential tokenization matures, Michelle suggests giving AI agents prepaid credentials rather than your core credential.Frameworks outlast specifics. Michelle finished writing in May and agentic payments had already moved by publication. The nine elements are built to hold up even as individual examples date.About Michelle BeyoMichelle Beyo is the founder and CEO of Finavator, which she started in 2019 after winning Money20/20 RiseUp. Before that, she spent six years in telco, eight years running online shopping and affiliate marketing programs for major airlines, led sales, marketing, distribution, and innovation for InComm Canada, and worked at a blockchain startup focused on digital identity and consent. She is the author of Mastering the Future of Finance: How Data, Trust, and Technology Are Reshaping the Global Economy (Wiley).Connect with Fintech One-on-One:Tweet me @PeterRentonConnect with me on LinkedInFind previous Fintech One-on-One episodes

Mike & Tommy are joined one last time by Kurt Buhler as they dive into the agentic development of Power BI reports, wrestling with why generating a governed dashboard is so much harder than spinning up a web app or 3D model, and whether that friction is a platform problem, a data problem, or a skills problem.They tackle the biggest misconceptions teams have when pitching agentic BI internally, debate whether dashboards are headed toward becoming ephemeral artifacts, and make their most realistic predictions for what the BI landscape looks like at the edge and in the enterprise core one to two years from now.Also in the news: Fabric Quest and What Does It Mean to Make Data AI Ready?Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Hi, Spring fans! In this episode, I sit down with Michael Carducci - software architect, magician, and knowledge graph expert—for a high-energy conversation about the future of AI. Michael breaks down why semantic data and auditable, deterministic reasoning are becoming essential for building trustworthy AI systems that actually work in production. If you're curious about what's next beyond bigger models and more tokens, this one is packed with big ideas, sharp insights, and a few surprises along the way. #ai #magic #knowledge #graph

Akash Palkhiwala, CFO and COO of Qualcomm (QCOM), talks about the company's Snapdragon Summit and ways new technology is changing the AI trade. New tech Qualcomm is unveiling includes the Snapdragon 8 and Elite Gen 6 smartphone chips just as the company renews its global patent license with Apple (AAPL). Agentic AI will drive a lot of Qualcomm's new tech, with Akash outlining how AI will execute tasks beyond phone screens.

Muse has driven Meta Platforms to a nearly $2 trillion valuation and has captured the market's attention. But how will Meta make money from Muse and who will the other winners in the industry be? Plus, we discuss the competition and whether Amazon sees this as an existential threat. Travis Hoium, Lou Whiteman, and Tyler Crowe discuss:- Muse v Amazon- How Muse Will Make Money- Shopify's Bet- Expedia on Muse- Who Wins an Agentic Future? Companies discussed: Expedia (EXPE), Meta Platforms (META), Alphabet (GOOG). Host: Travis HoiumGuests: Lou Whiteman, Tyler CroweEngineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement.We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode.Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

More tokens = more ROI, right?

Live from the Vusion podcast studio at Groceryshop 2026 in Las Vegas, Ben Miller welcomes Andrew Lederman, VP of Global Digital Commerce at Mondelēz International, to explore how grocery shopping is evolving online and what that means for one of the world's major consumer packaged goods companies. Andrew discusses the global shift toward digital grocery, changing shopping behaviors and the growing expectation for speed across markets. He also looks at the challenge of bringing impulse products into digital environments, how search and discovery are changing and what brands need to do to remain discoverable as algorithms, LLMs and agentic commerce reshape the path to purchase. In this episode: • How digital grocery is evolving across global markets • What's driving consumers toward online grocery shopping • The growing expectation for speed and convenience • How a CPG company approaches impulse products online • How search and digital discovery are changing • Building discoverability across algorithms and LLMs • What agentic commerce could mean for CPG brands • Strategies for converting digital demand

AI hallucinations nearly sparked an international crisis, Google dodged a breakup but faces new rules, and Meta's personal AI agent might be about to run your life. This week's episode ponders what's pragmatic, what's dangerous, and what's coming for everything from privacy to geopolitics. Judge Orders Data Sharing and Other Fixes to Solve Google's Ad Tech Monopoly US judge signals rejection of part of TikTok privacy settlement AI hallucination of Chinese nuclear components almost led to US military attack For the first time, the US military confirms it has deployed weapons in orbit OpenAI Discloses Six New Incidents of 'Concerning' A.I. Behavior Why AI pacing has become a false choice Iran and China Create First-of-Their-Kind Autonomous A.I. Influence Campaigns Hackers Got Inside a Flock Camera. Its Data Shows How the System Really Works Senate Votes to Block Crypto Bill in Major Blow to the Industry The EU Bans Social Media For Under-13s 'Maybe a year': Geoffrey Hinton gives the Senate a deadline on AI ZuckOff Is a Free App That Sees Meta Glasses Before They See You Host: Leo Laporte Guests: Owen Thomas, Jason Hiner, and Dan Patterson Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/twit rayneo.com NetSuite.com/TWIT ZipRecruiter.com/twit claude.ai/technology

AI hallucinations nearly sparked an international crisis, Google dodged a breakup but faces new rules, and Meta's personal AI agent might be about to run your life. This week's episode ponders what's pragmatic, what's dangerous, and what's coming for everything from privacy to geopolitics. Judge Orders Data Sharing and Other Fixes to Solve Google's Ad Tech Monopoly US judge signals rejection of part of TikTok privacy settlement AI hallucination of Chinese nuclear components almost led to US military attack For the first time, the US military confirms it has deployed weapons in orbit OpenAI Discloses Six New Incidents of 'Concerning' A.I. Behavior Why AI pacing has become a false choice Iran and China Create First-of-Their-Kind Autonomous A.I. Influence Campaigns Hackers Got Inside a Flock Camera. Its Data Shows How the System Really Works Senate Votes to Block Crypto Bill in Major Blow to the Industry The EU Bans Social Media For Under-13s 'Maybe a year': Geoffrey Hinton gives the Senate a deadline on AI ZuckOff Is a Free App That Sees Meta Glasses Before They See You Host: Leo Laporte Guests: Owen Thomas, Jason Hiner, and Dan Patterson Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/twit rayneo.com NetSuite.com/TWIT ZipRecruiter.com/twit claude.ai/technology

AI hallucinations nearly sparked an international crisis, Google dodged a breakup but faces new rules, and Meta's personal AI agent might be about to run your life. This week's episode ponders what's pragmatic, what's dangerous, and what's coming for everything from privacy to geopolitics. Judge Orders Data Sharing and Other Fixes to Solve Google's Ad Tech Monopoly US judge signals rejection of part of TikTok privacy settlement AI hallucination of Chinese nuclear components almost led to US military attack For the first time, the US military confirms it has deployed weapons in orbit OpenAI Discloses Six New Incidents of 'Concerning' A.I. Behavior Why AI pacing has become a false choice Iran and China Create First-of-Their-Kind Autonomous A.I. Influence Campaigns Hackers Got Inside a Flock Camera. Its Data Shows How the System Really Works Senate Votes to Block Crypto Bill in Major Blow to the Industry The EU Bans Social Media For Under-13s 'Maybe a year': Geoffrey Hinton gives the Senate a deadline on AI ZuckOff Is a Free App That Sees Meta Glasses Before They See You Host: Leo Laporte Guests: Owen Thomas, Jason Hiner, and Dan Patterson Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/twit rayneo.com NetSuite.com/TWIT ZipRecruiter.com/twit claude.ai/technology

An incredible opportunity to sit down with the co-founder and CEO of Shopware. What a story, creating the company when they were 16rs old or so, figuring out how to solve complicated problems and has been shepherding with his brother into a major global platform. Such a great conversation about how the product is always first and focus is the key to their success. Always Off Brand is always a Laugh & Learn!   SHOPTOBERFEST episodes are brought you by SHOPWARE! For the best ecommerce platform in B2B, there is no other choice to make complex hard customized merchant needs simplified! Go to https://www.shopware.com/en/ Open Source.. Open Commerce, Agentic by design. Huge thank you to everyone at Shopware for making this possible.     FEEDSPOT TOP 10 Retail Podcast! https://podcast.feedspot.com/retail_podcasts/?feedid=5770554&_src=f2_featured_email   CO-HOST for these shows! BRENT PETERSON who has hosted and produced TALK COMMERCE for many years. We collaborate on these shows and it is a great mashup!  Linkedin: https://www.linkedin.com/in/brentwpeterson/ Website: https://contentcucumber.com/ Podcast: https://talk-commerce.com/ Apple: https://podcasts.apple.com/us/podcast/talk-commerce/id1561204656   GUEST Sebastian Hamenn  LinkedIn: https://www.linkedin.com/in/sebastianhamann/ Shopware: https://www.shopware.com/en/ QUICKFIRE Info:   Website: https://www.quickfirenow.com/ Email the Show: info@quickfirenow.com  Talk to us on Social: Facebook: https://www.facebook.com/quickfireproductions Instagram: https://www.instagram.com/quickfire__/ TikTok: https://www.tiktok.com/@quickfiremarketing LinkedIn : https://www.linkedin.com/company/quickfire-productions-llc/about/ Sports podcast Scott has been doing since 2017, Scott & Tim Sports Show part of Somethin About Nothin:  https://podcasts.apple.com/us/podcast/somethin-about-nothin/id1306950451 HOSTS: Summer Jubelirer has been in digital commerce and marketing for over 17 years. After spending many years working for digital and ecommerce agencies working with multi-million dollar brands and running teams of Account Managers, she is now the Amazon Manager at OLLY PBC.   LinkedIn https://www.linkedin.com/in/summerjubelirer/   Scott Ohsman has been working with brands for over 30 years in retail, online and has launched over 200 brands on Amazon. Mr. Ohsman has been managing brands on Amazon for 19yrs. Owning his own sales and marketing agency in the Pacific NW, is now VP of Digital Commerce for Quickfire LLC. Producer and Co-Host for the top 5 retail podcast, Always Off Brand. He also produces the Brain Driven Brands Podcast featuring leading Consumer Behaviorist Sarah Levinger. Scott has been a featured speaker at national trade shows and has developed distribution strategies for many top brands. LinkedIn https://www.linkedin.com/in/scott-ohsman-861196a6/   Hayley Brucker has been working in retail and with Amazon for years. Hayley has extensive experience in digital advertising, both seller and vendor central on Amazon. Hayley lives in North Carolina.  LinkedIn -https://www.linkedin.com/in/hayley-brucker-1945bb229/   Huge thanks to Cytrus our show theme music "Office Party" available wherever you get your music. Check them out here: Facebook https://www.facebook.com/cytrusmusic Instagram https://www.instagram.com/cytrusmusic/ Twitter https://twitter.com/cytrusmusic SPOTIFY: https://open.spotify.com/artist/6VrNLN6Thj1iUMsiL4Yt5q?si=MeRsjqYfQiafl0f021kHwg APPLE MUSIC https://music.apple.com/us/artist/cytrus/1462321449   "Always Off Brand" is part of the Quickfire Podcast Network and produced by Quickfire LLC.