Podcasts about agentic

Tempo Mainnet is live, but this episode isn't really about just another chain launch. It's about a bigger claim: that AI agents are about to need native money, and that the internet may need a new payment layer to support them. Georgios Konstantopoulos and Brendan Ryan join Bankless to unpack why Tempo launched with agentic payments front and center, what MPP actually is, how it compares to x402, and why they think machine-to-machine commerce could reshape everything from paid APIs to the business model of the web itself. ---

Read more about Capgemini's Digital Cloud Platform → https://cloud.mongodb.com/ecosystem/c...In this episode of the MongoDB Podcast, Apoorva is joined by Vinay Makkaji from Capgemini and Farid Mohammad from MongoDB to discuss how enterprises are powering the next wave of Agentic AI applications. The conversation explores the shift from AI experimentation to real-world deployment, including AI agents, RAG architectures, and large-scale data modernization.They also unpack how the MongoDB–Capgemini partnership enables organizations to build scalable, production-ready AI solutions through unified data management and modern architectures. Tune in to hear practical use cases, industry examples, and where enterprise AI is headed next.Sign-up for a free cluster → https://www.mongodb.com/cloud/atlas/r...Subscribe to MongoDB YouTube→ https://mdb.link/subscribe00:00:00 Introduction to the MongoDB Podcast 00:00:58 Meet the Experts: Vinay Makaji & Fared Muhammad 00:03:09 The Three Phases of genAI Evolution 00:04:47 Shifting from Generative to Agentic AI 00:06:55 Why AI is a System, Not Just a Model 00:10:48 The Power of Technology Partnerships 00:17:11 Case Study: Predictive Maintenance in Oil & Gas 00:20:18 How Agentic Systems Prevent $250k/Hour Downtime 00:24:22 The Future: Mainframe Modernization & Industrial IoT 00:28:28 Key Takeaway: Partnerships Build Outcomes 00:30:22 Final Advice: Data Strategy is the Foundation

Sumeet Arora, Chief Product Officer at Teradata, joins The Tech Trek for a sharp conversation on the shift from human driven SaaS to agentic software. This episode digs into what changes when software stops just supporting human workflows and starts driving outcomes alongside people, why trust and governance matter more as AI systems take on more responsibility, and what serious companies need to do now to prepare.This is a practical discussion about where the market actually is, what gets overhyped, and what leaders should focus on beneath the noise. Sumeet lays out a clear view of the emerging enterprise stack, from knowledge and context to agents, governance, and outcomes. He also explains why the winners may not be the loudest companies in AI, but the ones that get their data, knowledge, and operating model right.In this episode• Why agentic software is a real shift, but still in its early stages• What trust, governance, and explainability need to look like in an AI first enterprise• How software companies should rethink product strategy for agents as well as humans• Why every employee may need to become a manager of AI agents• Why knowledge infrastructure could matter more than the agent layer itselfTimestamped highlights• 00:45 Teradata's role in helping enterprises become autonomous• 02:34 Where we really are in the agentic AI maturity curve• 10:16 How software shifts from workflow centric to outcome centric• 16:17 Why every employee may need an AI workforce• 21:57 The skill gap between enterprise users and agentic adoption• 24:48 Why knowledge, not just agents, will define the winnersStandout line“The fundamental winners will be ones who get the knowledge fabric correct.”Practical takeawayIf you are building for an AI driven future, do not start with agents alone. Start with trusted knowledge, usable context, clear policies, and systems that can explain decisions. The companies that treat agentic AI as a stack, not a feature, will be in a much stronger position.Follow The Tech Trek for more conversations with leaders shaping the future of technology, product, AI, and enterprise transformation.

What does it really take to move from AI hype to something that actually works inside a business? In this episode, I sit down with Shibani Ahuja, SVP of Enterprise IT Strategy at Salesforce, to talk about why so many enterprise AI projects stall long before they deliver real value. While the market is full of noise around agents, copilots, and automation, Shibani makes the case that the real issue is often much simpler and much harder at the same time. Design. She explains why model capability alone will never rescue poor architecture, weak governance, or unclear data ownership. Our conversation goes well beyond the usual agentic AI headlines. Shibani shares what she learned from speaking with hundreds of C-suite leaders over the past year, and why many early enterprise AI conversations were too focused on models instead of ecosystems. We unpack the difference between predictive, generative, and agentic AI, why trusted data means more than having lots of information, and how Salesforce's own internal journey revealed conflicting knowledge, governance gaps, and the importance of determinism in enterprise settings. I also loved Shibani's perspective on the human side of this transformation. We talk about why successful organizations are framing agents as a capacity multiplier rather than a headcount story, how to bring employees along through visible wins and shared learning, and why the best starting point is often a simple, boring use case that removes pain for frontline teams. She also shares her thoughts on the eight design principles for the agentic enterprise, the myths that frustrate her most, and what will separate the leaders from the laggards over the next 18 to 24 months. This is a conversation for anyone feeling pressure to do something with AI, but wanting a clearer view of what meaningful progress actually looks like. Are businesses building the right foundations for an agentic future, or are too many still mistaking experimentation for strategy? Have a listen and let me know your thoughts. Useful Links Connect with Shibani Ahuja Agentic Enterprise Architecture    

AI used to be about prompts, now it's about delegation. Christopher Penn breaks down what agentic AI actually is, why it represents a leap forward for small businesses, and how tools like Claude Cowork are turning strategy into execution. If you've been curious about moving beyond copy-and-paste AI and into systems that actually get work done, this conversation is your starting point. https://www.theagentsofchange.com/616 Need help with your branding, website, or digital marketing? Reach out to me (Rich Brooks!) today at https://www.takeflyte.com/contact

Send a textFirst Aired Apr 23, 2025If you've been following the AI space lately, this episode hits differently the second time around.When Al sat down with Ruchir Puri — Chief Scientist of IBM Research, IBM Fellow, and the architect behind Watson and watsonx — the conversation covered ground that's only gotten more relevant since: the death of prompt engineering, the rise of agentic AI, and why 2025 was always going to be the year agents broke through in the enterprise.Ruchir doesn't deal in hype. He deals in systems — real ones, running at scale, in industries where a hallucinated number has consequences. In this masterclass, he walks through inference scaling, memory in AI systems, and what it actually means to build AI that's useful rather than just impressive.If you're new to the show, this is the episode to start with. If you've heard it before — trust us, it lands differently now.Key moments:12:21 — Why prompt engineering is already fading (and what replaces it)13:39 — Inference scaling: the frontier that's not about training anymore16:26 — Why AI systems that "forget" are failing us17:56 — The full agentic loop: Think, Plan, Act, Execute, Observe, Reflect23:45 — Why enterprise AI agents are no longer a future stateMaking Data Simple is hosted by Al Martin, WW VP Technical Sales, IBM.Ruchir's LinkedinAl's LinkedInExplore IBM's WatsonxWant to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. 

Martin Raison, Co-founder and CTO of Nabla speaks with Pitt HexAI host Jordan Gass-Pooré about Nabla's central role in architecting the agentic AI era in healthcare. Martin details Nabla's evolution from a specialized ambient scribing tool into a comprehensive "Adaptive Agentic Platform". They discuss the significant challenges involved in making it possible for AI agents to perform complex clinical tasks and how Nabla has been thrust into tackling a labyrinth of structural and data hurdles. These range from the integration of fragmented, unstructured patient charts and hospital guidelines to the complex technicalities of agent discoverability, interoperability, and the establishment of standardized accountability frameworks.The interview highlights a significant shift in Nabla's technical strategy: moving from probabilistic Large Language Models (LLMs) toward world models. Raison explains that while LLMs are effective at generating text, they lack a fundamental understanding of cause-and-effect and the ability to simulate evolving environments. To address this, Nabla has entered an exclusive partnership with Advanced Machine Intelligence (AMI), a research lab co-founded by Yann LeCun. This collaboration provides Nabla with early access to world model technologies that can "imagine" different scenarios and simulate the consequences of actions, providing a more deterministic and auditable path for AI in high-stakes clinical settings.In discussing the technical foundations of computational health, Martin addresses the critical need for inference optimization to manage the millions of model executions required daily at scale. Furthermore, Martin envisions a fundamental shift in the paradigm of AI inference through the adoption of world models. He suggests that these architectures will blur the traditional boundary between training and inference by enabling continuous learning, where the model adjusts and evolves in real-time based on new data and clinician feedback, rather than being limited by the static context windows of current LLMs.Beyond the core technology, Martin and Jordan discuss the critical importance of explainability and interoperability in the "agentic web" of healthcare. They specifically highlight architectural initiatives like MIT's Project NANDA, which focuses on the foundational layers of the agentic web, including critical elements like discoverability and authentication that go beyond the AI layer alone. Martin emphasizes that the sector must move toward standardized "Agent Fact Files" to ensure accountability and ease of governance as organizations begin to manage thousands of agents. He concludes by looking toward a future of "emergent intelligence," where the collaboration between multiple models creates sophisticated patterns that can eventually help clinicians improve their own professional practice over time.

What happens when an AI hater starts building with AI agents? In this episode, we talk with software engineer Steve Klabnik, known for his work on the Rust programming language, about his journey from criticizing AI to experimenting with it firsthand. We explore Steve's programming language Rue, largely built with the help of AI tools like Claude, and discuss what this means for software engineering and the future of coding in an AI-driven world.Featuring:Steve Klabnik – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:The Rust Programming LanguageRustRueDaniel's RSA Meeting link for March 23, 2026Daniel's RSA Meeting link for March 24-25, 2026Upcoming Events: Register for upcoming webinars here!

The Centers for Disease Control and Prevention launched a strategy and guidance for use of artificial intelligence on Thursday, setting a direction for the agency's own work and providing resources for public health officials across the country. Those documents point to a desire to promote adoption of the technology, empower the workforce to use it, and ensure the tools are governed properly. But, more uniquely, the publications encourage the use of “agentic” or “deep research” AI uses — those that can autonomously carry out specific tasks — which CDC is already tapping into. Almost 10% of CDC's roughly 100 AI use cases were agentic tools in 2025, according to the Department of Health and Human Services' recently reported AI use case inventory. Its share of agentic uses makes up roughly a third of such deployments across the department. As a result, the CDC's new strategy includes specific language to leverage that technology to support public health, strengthen research and data management, and improve access to data. And simultaneously, the agency released specific guidance for state, tribal, local and territorial (STLT) public health authorities on the use of AI agents for research based on experiences from its own exploration. The White House is launching a task force aimed at eliminating fraud in federally run programs — a goal that will be pursued largely through beefed-up data-sharing processes. The executive order signed Monday by President Donald Trump is framed through the lens of various fraud cases in Minnesota involving Medicaid, a Department of Agriculture child nutrition program and Small Business Administration loan programs during the COVID-19 pandemic. Investigations into the alleged fraud began under the Biden administration's Department of Justice, but the scandal has since been wielded by the Trump White House to freeze funds and strip away benefits from residents of the Gopher State. Under Trump's new order, the task force will be charged with developing a national strategy to combat fraud in federal benefit programs. The EO calls specifically for new measures to improve eligibility verification processes and create controls to prevent the disbursal of improper payments. The task force will also be required to “promote the facilitation of information and data sharing and coordination between State, local, tribal, and territorial governments and the Federal Government, and benefit-providing agencies and law enforcement agencies,” per the order. Interagency data-sharing would additionally be prioritized as part of an overarching enforcement push aimed at disrupting and dismantling “fraud networks and facilitators,” the EO states. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

Doug Green, Publisher of Technology Reseller News, interviewed Scott Eivers, CEO of Datatonic, about the rapid evolution of AI in telecommunications and why the next phase of innovation depends on building strong data foundations. Datatonic, a leading Google Cloud partner, works with telecom operators and enterprises to modernize their data architectures so they can fully leverage advanced analytics and AI-driven automation. Eivers explained that the telecom industry is entering a new phase where agentic AI—autonomous systems capable of taking action and executing workflows—will play a growing role in operations, customer engagement, and network management. However, he emphasized that AI success depends heavily on the quality and accessibility of underlying data. “AI is only as good as the data it's built on,” Eivers noted, pointing out that many organizations still struggle with fragmented data environments that limit the effectiveness of their AI initiatives. A key focus of Datatonic's work is helping telecom providers unify and modernize their data infrastructure using cloud-native platforms. By bringing together operational, customer, and network data into a consistent architecture, service providers can unlock new capabilities such as predictive analytics, intelligent automation, and real-time decision-making across their organizations. The conversation also explored how AI is moving beyond experimentation into production use cases across the telecom sector. From improving customer service to optimizing network performance and detecting fraud, AI-driven systems are increasingly becoming embedded in core telecom operations. Eivers stressed that companies that invest early in scalable data platforms will be best positioned to deploy these capabilities effectively. Ultimately, the discussion highlighted a broader shift in the industry: AI is no longer just about models and algorithms—it is about data strategy, governance, and operational readiness. As telecom providers pursue digital transformation, the organizations that succeed will be those that treat data as a strategic asset and build the infrastructure needed to support intelligent, automated systems. More information about Datatonic is available at https://datatonic.com/.

In episode 316 of Absolute AppSec, hosts Ken Johnson and Seth Law participate in a crossover with Kurt Hendle and Cameron Walters from the Coffee, Chaos, and ProdSec podcast to discuss the radical transformation of security roles in an AI-driven landscape. The guests share origin stories rooted in gaming and "mischievous" curiosity, which evolved into deep careers in security architecture and engineering. The primary discussion centers on the industry's shift toward an "Agentic Development Lifecycle" (ADLC), where the sheer volume of AI-generated code renders traditional manual review gates obsolete. This acceleration risks a "rubber stamp" culture where developers approve fixes in seconds rather than minutes, potentially leading to a mountain of technical debt. Consequently, the role of security is shifting from manual bug finding to high-level governance and "context infusion," requiring practitioners to manage AI agents that automate complex tasks. Economically, the group highlights how frontier model announcements have caused massive market volatility, wiping billions from traditional security stocks. Ultimately, they conclude that while older "primitive" tools are failing, professionals who lean into AI as a "superpower" for governance and oversight will be essential for navigating this new, non-deterministic reality.

The rise of Agentic agents in military headquarters is a foregone conclusion. Understanding how they perform, where they may hallucinate answers, and their requirement for credible and reliable data sets sit at the heart of their utility. Henrik Sommer, a retired Brigadier General with the Danish military, explains some of the potential, vulnerabilities, weaknesses, and opportunities that AI can provide, including from Systematic's new Wingman AI tool, something already embedded in the Sitaware system. The importance of coders, teachers and trainers of algorithms, and how we prompt AI come out as clear markers in this conversation, as does the core question: how much should we trust AI in the military?

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM   This episode features a conversation with Daniel Cohen‑Dumani on why many organisations feel stuck on AI despite rapid advances. The discussion focuses on agentic AI, the growing gap between consumer and business adoption, and why strategy matters more than experimentation. You will hear practical guidance on narrowing AI efforts to real business problems, building organisational memory for reliable agents, and avoiding paralysis caused by hype and fear. The conversation also challenges traditional systems like CRM and reframes AI as a tool to learn, not shortcut, building sustainable capability inside organisations.

Bu bölümde MacBook Neo, Mert'in Xcode Agentic Coding deneyimi, Coraline kitabı ve Marathon oyunu üzerine sohbet ettik. Bizi dinlemekten keyif alıyorsanız, kahve ısmarlayarak bizi destekleyebilir ve Telegram grubumuza katılabilirsiniz. :) Yorumlarınızı, sorularınızı ya da sponsorluk tekliflerinizi info@farklidusun.net e-posta adresine iletebilirsiniz. Zaman damgaları: 00:00 - Giriş 05:40 - MacBook Neo 45:10 - Xcode Agentic Coding 1:18:10 - Okuduklarımız, Persian Fire 1:55:30 - İzlediklerimiz 2:04:45 - Oynadıklarımız, Marathon 2:38:33 - Albüm tavsiyesi Bölüm linkleri: Monofor MacBook Neo iPhone 17e Studio Display XDR Apple Finally Made a Repairable MacBook Xcode 26.3 unlocks the power of agentic coding Kitap Kulübü Etkinliği Teknopoli Old Man and the Sea Coraline Small Fry Persian Fire: The First World Empire and the Battle for the West Pirate Enlightenment, or the Real Libertalia The Pitt The Bourne Identity Hijack Coraline Microsoft's next Xbox, Project Helix, won't reach alpha until 2027 Marathon Asia Minor - Between the Flesh and Divine

What happens when you stop thinking about AI as a replacement tool and start thinking about it as a value creation engine? In this episode, Raul shares the paradigm shift he taught his 4-year-old son about money and value creation, rebuts Mark Cuban's argument about AI token costs, and walks through how to find your own net new value as a service founder or consultant.Chapters00:00 - A 4-Year-Old's Take on How Money Works (and Why He's Right)01:30 - The Highest Calling: Why We're Meant to Create, Not Just Execute02:30 - Mark Cuban Is Right About Token Costs. He's Wrong About the Goal.04:00 - What Net New Value Actually Is (and Why You're Stuck Without It)05:00 - The Key Distinction: Efficiency Is Not Creation06:00 - How I Compressed 12 Weeks of Work Into a Month (Without Outsourcing My Thinking)07:00 - The Test: Are You Still in Replacement Mode?08:00 - The Firm of the Future: 70% Agentic, 30% Human, 100% Intentional09:30 - Your Offer Dictates Everything. Start There.11:00 - What I Learned Spending Millions in Direct Response About Upsells12:30 - Proactive Value: Anticipate Your Client's Next Problem Before They See It13:00 - Be a Creator and Inventor. Tinker. Play. Build for Fun.

Samsung's Galaxy S26 Ultra integrates Google Gemini to perform agentic artificial intelligence tasks within apps. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Crypto OG Erik Voorhees joins The Chopping Block crew to dissect the future of agentic payments, the eternal war for privacy, memecoin-fueled AI drama on Moltbook, and why your next DeFi user might just be your OpenClaw agent—plus, a candid look at crypto's core and how AI turns software engineering existential. Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This week, we're joined by none other than Erik Voorhees, legendary crypto pioneer and founder of Venice, for a no-holds-barred discussion on the wild convergence of AI, crypto, and the meme coin casino. Erik unpacks his journey from anti-surveillance crusader to AI entrepreneur, why Venice is all-in on privacy and free speech for LLMs, and how “provable privacy” is a Sisyphean technical challenge. The crew breaks down OpenClaw's agent drama, memecoin carpet-bombing of Moltbook, and Meta muscling in on AI social networks. We debate agentic payments (will your first paying customer soon be a bot?), the true game theory behind state surveillance, and why crypto's greatest killer use case might actually be building tools for robots instead of humans. Plus: existential crises for software engineers, why “AI alignment” is a philosophical dead end, and the childlike glee (or open psychosis) of trading OpenClaw war stories at AI meetups. Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Show highlights

Have you ever contacted customer support with a simple request, only to find yourself trapped in a loop of scripted chatbot responses that never actually solve the problem? It's an experience many of us know all too well.  AI has made customer service more conversational over the last few years, yet there is still a gap between answering a question and actually resolving an issue. That gap is exactly where today's conversation begins. In this episode of Tech Talks Daily, I spoke with Mike Szilagyi, SVP and General Manager of Product Management at Genesys Cloud, about a new chapter in AI-powered customer experience. Genesys has announced what it describes as the industry's first agentic virtual agent built on Large Action Models, or LAMs. While Large Language Models have dominated the conversation around AI for the past few years, they have largely focused on generating responses, retrieving knowledge, or answering questions. What they have struggled with is execution. Mike explained how Large Action Models take the next step. Rather than simply telling a customer how to solve a problem, these systems can plan and execute the steps needed to complete a task. Imagine contacting an airline after a sudden flight cancellation.  Instead of navigating multiple menus or repeating information to a human agent, an agentic virtual assistant could understand your situation, check alternative flights, apply airline policies, and complete the rebooking process across several systems. In other words, the AI moves from conversation to action. We also explored how Genesys approached the design of this technology with enterprise governance in mind. From explainable decision paths and audit logs to guardrails that ensure every automated action can be traced and understood, the goal is to make autonomous AI trustworthy inside complex organizations. Mike also shared insights into Genesys' partnership with Scaled Cognition and how integrating specialized models helps deliver reliable execution in real-world customer service environments. Perhaps most interesting was our discussion about the human role in this evolving contact center landscape. As automation begins to handle routine and multi-step workflows, human agents are free to focus on situations that require empathy, judgment, and expertise. That shift raises interesting questions about how organizations design customer experiences in the years ahead. So how will customers respond when virtual agents move beyond answering questions and begin resolving problems on their behalf? And once one brand delivers that experience, will it quickly become the expectation? Useful Links Connect with Mike Szilagyi Learn more about Genesys Genesys Agentic Virtual Agent Powered by LAMs for Enterprise CX Follow on LinkedIn

Notion isn't designing AI agents that just use tools. Their agents can autonomously build their own integrations, as well as write the code needed to finish a task. Sarah Guo sits down with Notion Co-Founder Simon Last to explore Notion's rapid evolution from a simple writing assistant to a sophisticated platform for custom AI agents. Simon discusses the technical hurdles of indexing disparate data from sources like Slack and Google Drive, as well as the internal shift toward using coding agents to build Notion itself. Plus, Simon elaborates on what he sees as a fundamental transition in productivity: moving from a tool where humans do the work, to one where humans manage a swarm of agents. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @simonlast | @NotionHQ Chapters: 00:00 – Cold Open 00:05 – Simon Last Introduction 00:26 – Genesis of Notion AI 04:10 – Challenge of Semantic Indexing and Retrieval 07:16 – The Six-Month Rewrite Cycle 08:12 – Notion's Coding Agent Era 09:44 – Impact on Team Dynamics 12:49 – Launching Custom Agents 15:39 – Notion as the ‘Switzerland' for Models 17:33 – Designing APIs for Agent Customers 20:09 – Simon's Personal Agentic Workflows 24:48 – Notion: Tool for Work is Now A Tool for Agents 27:28 – How Building Has Changed for Simon 29:00 – Conclusion

Artificial intelligence is rapidly transforming the consumer financial services industry. From underwriting and fraud detection to customer engagement and collections, financial institutions are increasingly deploying advanced AI tools to automate processes, personalize services, and improve operational efficiency. We are releasing today, on our Consumer Finance Monitor Podcast show, a discussion of what may be the next major technological shift for the industry: Agentic AI in Consumer Financial Services — AI systems capable of acting autonomously, making decisions, and interacting directly with consumers. The discussion featured Professor Oren Bar-Gill of New York University School of Law, along with Ballard Spahr partners Joseph Schuster and Adam Maarec.  The discussion was hosted by Alan Kaplinsky, the founder and practice group leader for 25 years of the Consumer Financial Services Group and now Senior Counsel. The panel examined how agentic AI differs from earlier forms of automation, the benefits it offers financial institutions and consumers, and the significant legal and regulatory risks it may create. Below are the key takeaways from the discussion. What Is Agentic AI? Agentic AI refers to AI systems that can independently take actions on behalf of users or organizations. Unlike traditional automation, which performs predefined tasks, or generative AI, which primarily produces content, agentic AI systems can: ·                 Make autonomous decisions ·                 Interact directly with consumers ·                 Initiate actions such as transactions or communications ·                 Learn from prior interactions In financial services, these systems may soon conduct customer service interactions, initiate collections calls, execute payments, or manage purchasing tasks for consumers. While these capabilities promise major efficiencies, they also raise complex legal questions regarding accountability, fairness, and consumer protection. Understanding AI-Driven Consumer Harm Professor Bar-Gill framed the discussion by examining potential consumer harms associated with AI-powered decision-making. Drawing on his recent book with Cass Sunstein, Algorithmic Harm: Protecting People in the Age of Artificial Intelligence, he explained that the impact of AI depends largely on the type of market in which it operates.  The book is available on Amazon here. Sophisticated vs. Unsophisticated Markets Bar-Gill distinguishes between: ·                 Sophisticated markets, where consumers are generally able to make informed decisions ·                 Unsophisticated markets, where consumers are more likely to misunderstand complex products In sophisticated markets, AI-driven personalization, such as individualized pricing, can increase efficiency and expand access to products by offering lower prices to consumers with lower willingness to pay. In contrast, in markets involving complex financial products, such as credit cards, mortgages, or insurance, AI-powered personalization may harm consumers who misjudge product costs or benefits. For example, if a consumer mistakenly overestimates the value of a financial product, an AI system may set the price just below that mistaken valuation, leading the consumer to pay more than the product is actually worth. Algorithmic Price Discrimination One area of growing concern is AI-enabled price discrimination, where algorithms tailor prices to each consumer's willingness to pay. Examples cited during the discussion included: ·                 Airlines experimenting with AI-based pricing strategies ·                 Online retail platforms offering individualized prices for identical products ·                 Insurance companies using algorithms to optimize premiums While pricing based on individual risk, such as in insurance underwriting, is widely accepted, pricing based on willingness to pay raises significant consumer protection concerns. As these practices expand, they are likely to attract increased attention from regulators and lawmakers, particularly at the state level. AI Use Cases in Consumer Finance The panel also highlighted several areas where AI is already being deployed across the consumer financial services lifecycle. Marketing and Customer Acquisition Financial institutions are using AI to analyze large data sets and create highly personalized marketing campaigns. Large language models can generate customized messaging tailored to specific demographic groups or individual consumers. While this personalization improves targeting and engagement, it also creates compliance challenges related to: ·                 Misleading advertising ·                 Disclosure requirements ·                 Potential discriminatory targeting Underwriting and Credit Decisions AI-driven underwriting tools allow lenders to analyze alternative data, such as cash-flow information, to assess creditworthiness. These tools may expand access to credit for consumers who previously lacked traditional credit histories. However, they also raise fair lending concerns under laws such as the Equal Credit Opportunity Act and its implementing regulation, Regulation B. Because many AI models operate as "black boxes," institutions may struggle to explain how decisions are made, an issue that can complicate discrimination analyses and regulatory oversight. Fraud Detection AI is particularly powerful in fraud detection, where pattern recognition is essential. Advanced models can analyze transaction behavior in real time to identify suspicious activity while minimizing unnecessary transaction declines. These tools also allow financial institutions to communicate with customers instantly, confirming transactions or investigating suspicious activity through automated interactions. Servicing and Collections Agentic AI may soon conduct both inbound and outbound customer interactions, including: ·                 Customer service conversations ·                 Dispute resolution ·                 Collections calls In some cases, AI-driven voice systems can conduct conversations that are indistinguishable from human interactions. While this technology may improve efficiency and reduce costs, it raises legal concerns about consumer deception, harassment, and compliance with debt collection laws. Core Legal Risks Despite the novelty of the technology, many of the key legal risks arise from existing laws, not new AI-specific statutes. Liability for AI Actions As Joseph Schuster emphasized, AI is a tool, not a liability shield. Institutions remain responsible for the actions of AI systems just as they would for the actions of employees or third-party vendors. Traditional legal doctrines, including agency law, vicarious liability, and unfair or deceptive acts or practices, continue to apply. UDAP Risks AI systems interacting with consumers may create risks under federal and state UDAP laws if they: ·                 Provide inaccurate information ("hallucinations") ·                 Fail to deliver required disclosures ·                 Exhibit overconfidence in uncertain responses ·                 Engage in manipulative behavioral targeting. Fair Lending and Discrimination AI models can unintentionally produce discriminatory outcomes, even when protected characteristics are not used as inputs. As Professor Bar-Gill noted, future litigation may increasingly focus on disparate impact analysis, which examines whether outcomes disproportionately affect protected classes regardless of the model's internal logic. Governance and Risk Management Given these risks, institutions are increasingly adopting governance frameworks for AI deployment. Common practices include: ·                 AI governance committees with cross-functional participation ·                 Model inventories and risk-tiering systems ·                 Vendor due diligence for AI providers ·                 Data mapping and validation processes ·                 Continuous monitoring of AI outputs. Financial regulators are already asking supervised institutions detailed questions about how AI is being used. Institutions that implement structured governance processes are better positioned to respond to these inquiries. The Rise of Agentic Commerce One emerging application of agentic AI involves autonomous purchasing. For example, a consumer might instruct an AI assistant to plan and purchase supplies for a birthday party. The AI would then select vendors, place orders, and initiate payments using the consumer's stored payment credentials. But what happens if AI makes a mistake, such as ordering supplies for 1,000 guests instead of 10? Such scenarios raise difficult questions involving: ·                 consumer authorization ·                 merchant liability ·                 payment network rules ·                 dispute resolution These issues are only beginning to receive attention from regulators and industry participants. Key Takeaways for Financial Institutions The panel concluded with several recommendations for institutions exploring AI deployment. First, distinguish beneficial uses from harmful ones. AI can deliver significant consumer benefits, but firms must remain vigilant about potential misuse or unintended harm. Second, prioritize governance. Robust policies, oversight structures, and risk management processes are essential. Third, remember that existing laws still apply. AI systems must comply with the same consumer protection, fair lending, and disclosure requirements that govern traditional processes. Finally, institutions must recognize that failing to adopt AI also carries risks. As fraudsters increasingly deploy advanced technology, financial institutions may need AI tools simply to keep pace. As AI technology continues to evolve, the legal framework governing its use in financial services will also develop. For now, however, the most important lesson is that innovation must proceed hand-in-hand with careful legal and compliance oversight. Consumer Finance Monitor is hosted by Alan Kaplinsky, Senior Counsel at Ballard Spahr, and the founder and former chair of the firm's Consumer Financial Services Group. We encourage listeners to subscribe to the podcast on their preferred platform for weekly insights into developments in the consumer finance industry.

Gautam Vasudev, SVP of Product Management for Agentforce Service at Salesforce, spoke with Doug Green, Publisher of Technology Reseller News, during the Enterprise Connect conference about Salesforce's vision for agentic AI and its role in transforming customer service operations. Vasudev explained that Agentforce Service represents Salesforce's next step in bringing autonomous AI agents into the contact center and customer experience environment. These AI-powered agents are designed to handle routine service requests, assist human agents in real time, and orchestrate workflows across enterprise systems. “Agentic AI allows organizations to move beyond simple automation and into systems that can actually reason through customer issues and take action,” Vasudev said. The goal is to improve both efficiency and customer satisfaction by enabling AI agents to resolve common service requests quickly while allowing human agents to focus on more complex interactions. By integrating AI directly into the Salesforce platform, Agentforce Service can connect customer data, workflows, and communications across the enterprise. Vasudev noted that enterprises are increasingly looking for AI solutions that go beyond chatbots and scripted automation. Agentic AI systems are designed to understand context, interact with multiple systems, and assist human workers in delivering more personalized customer experiences. As industry leaders gathered at Enterprise Connect to explore the future of enterprise communications and AI-powered collaboration, Salesforce highlighted how agentic AI platforms like Agentforce Service could redefine how organizations manage customer engagement and service delivery. Learn more about Salesforce: https://www.salesforce.com/

Are we moving too fast in the world of agentic commerce — a new paradigm in online shopping where AI agents act on behalf of consumers, facilitating transactions and product discovery? Unlike traditional e-commerce, where consumers interact directly with platforms, agentic commerce leverages advanced technologies to streamline the purchasing process.In this episode of One Vision — FinTech Fuse, we dive deep into the rapidly shifting landscape of agentic commerce and the alphabet soup. With the technology landscape changing at an unprecedented pace, we explore the challenges and opportunities that arise in the new world.Joining us in the discussion are industry experts, Dr. Efi Pylarinou and Jas Shah, who offer their insights on the rise of different protocols like ACP and UCP, identity verification, and the importance of a level-playing field in the future of commerce.What's your take on this fast-paced evolution? Let's keep the conversation going!#FinTech #AI #AgenticCommerce #AIAgents00:00 Welcome and Setup: The Agentic Commerce Alphabet Soup02:53 The Reality: Are We Moving Too Fast?07:35 Who Writes The Rules? 10:03 Which Protocol Will Win?16:20 Staying Visible: Banks Brand in Bot Era21:04 Trust Data and Curation25:44 The Economics and Gatekeepers33:57 Predictions: Who Will Emerge as The Likely Winner41:56 What Banks Should Do NextHot take: The real battle is about protocols, not models.Hot take: The future belongs to those who can optimize for AI.Keywords AI, agentic AI, commerce protocols, fintech, banking, digital transformation, identity, trust, UCP, ACPMore about our guests 

Amazon is fighting Perplexity over the startup's shopping agents, showing the legacy tech companies may not be as comfortable with AI innovation as we may think. We also discuss Meta's AI strategy and why Oracle is growing and taking a big risk in its buildout. Travis Hoium, Lou Whiteman, and Rachel Warren discuss: - Amazon goes after Perplexity's agents - Meta's scattered AI strategy - Oracle earnings Companies discussed: Amazon (AMZN), Google (GOOG, GOOGL), Meta Platforms (META), Oracle (ORCL). Host: Travis Hoium Guests: Lou Whiteman, Rachel Warren Engineer: 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

Tillman Holloway is the Founder & CEO of Arch Public. In this conversation, we discuss the rise of AI-driven investing and how autonomous agents could reshape portfolio management. We also cover Bitcoin market catalysts, investor behavior during volatility, and how institutions are positioning across crypto and emerging financial products.=======================Join Arch Public this Thursday @ 2pm Et for an exclusive webinar with Anthony, where we will share professional strategies for optimizing your portfolio to outperform current bear market conditions. This session is designed to provide actionable insights into risk management and long-term wealth preservation. Resister here to secure your spot: https://us06web.zoom.us/webinar/register/WN_DVHBA2Z3QgS5X0l203-78A=======================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan (https://figuremarkets.co/pomp), 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 ~8.5% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp =======================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp=======================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 - Intro1:03 - Is AI disruption crashing markets?3:28 - What should AI actually automate in business?6:43 - How investors are navigating volatility11:43 - “Agentic investing” — letting AI manage your money16:46 - Hedge funds, algorithms & high-frequency trading21:41 - Crypto derivatives, perps & new financial instruments23:18 - How Arch Public works & consumer investing trends29:45 - What catalyst sends bitcoin back to all-time highs?34:33 - Institutional adoption & Wall Street conviction

In Part 2 of my conversation with Brooke Gramer, we shift from voice and branding into something even bigger — the future of search and AI-driven commerce.What happens when AI starts shopping for your customers?We explore agentic commerce, GPT updates, model selection, and where AI should never replace human judgment. We also talk about the guardrails business owners need as AI becomes more embedded in workflows.If you sell online — especially on Shopify — this episode will stretch your thinking.Because the future of SEO isn't just rankings. It's recommendations.✨ Key Takeaways:Use AI After You've Learned the Skill — Not Instead of ItAI should accelerate mastery, not replace it.Always Keep a Human in the LoopFrom legal citations to ecommerce workflows, oversight matters.Agentic Commerce Is Emerging — Not Fully AutonomousAI agents still require permission checkpoints and clarification.Model Settings MatterDeep research mode, updated models, and custom GPT guardrails change output quality dramatically.Voice Search Is Coming Faster Than You ThinkThe future of search may be conversational and voice-first.

Every vendor in the industry is slapping the word "agentic" on their roadmap. But, what is agentic AI, really? And should IT leaders care?In this episode, we bring together three voices with very different answers: a skeptic who says it's rebranded orchestration, a strategist who says the reasoning layer is genuinely new, and a founder betting his company on it. Together, they cut through the noise and answer the question every IT leader is quietly asking: what should I actually do about agentic AI in 2026?Key takeaways:Why 80% of AI projects fail — and it has nothing to do with the technologyThe difference between "embedded agents" you're already using and custom agents you probably don't need yet"Start with your decisions, not your technology" — a practical framework for mid-market teamsHow to move AI from "pet project" to operationalized infrastructureFeaturing: Sean Larkin, Principal Architect at Softchoice, a World Wide Technology company | Scott Trump, Founder & CEO of Treva AI (former AWS, Google Cloud, Oracle) | Skip Vanderburg, Founder of Prioriti AI#AgenticAI #MidMarketIT #AIStrategy #TheCatalyst #Softchoice #ITLeadershipThe Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

Amy and Alex discuss how AI is moving beyond generating text to executing real tasks and workflows. In this episode, we unpack the rise of agentic AI, what it means for state governments and how technology leaders can prepare for this next phase of AI innovation. Find the report here: https://www.nascio.org/resource-center/resources/beyond-generation-the-rise-of-agentic-ai-in-state-government/

In today's Cloud Wars Minute, I look at ServiceNow's new Autonomous Workforce and what it means for the future of the digital workforce. Highlights 00:03 — As companies become more familiar with the scope and capabilities of agentic AI, they're seeking more efficient ways to integrate these features into their workflows. And in line with this trend, ServiceNow has launched the Autonomous Workforce: teams of AI specialists that will enhance teams with domain-specific AI knowledge. 00:29 — So how does the Autonomous Workforce operate in practice? Well, the AI specialists deployed by the system have defined roles and work alongside human team members. ServiceNow explains that this shift represents a move away from AI agents that complete individual tasks to teams of AI specialists that take on specific roles. 00:57 — These specialists execute entire workflows from start to finish autonomously. Teams can onboard pre-skilled AI specialists with just a few clicks. These specialists are familiar with their roles, permissions, and, crucially, the historical enterprise context. Companies can scale the scope of the specialists on demand to match spikes in activity. 01:20 — The first out-of-the-box specialist is theLevel 1 Service Desk AI Specialist which can autonomously diagnose and resolve typical IT support requests like password resets or network troubleshooting. Proof of concept for this new system lies with ServiceNow, where the Autonomous Workforce is already handling over 90% of employee IT requests. 02:01 — What's truly remarkable is the redefinition of the work of the digital workforce. Having a context-aware, independent worker for specific tasks is a really outstanding achievement and development. It embodies the futuristic vision of a robotic worker and, in reality, is somewhat more streamlined than many of the widely dispersed agentic systems that I've come across today. Visit Cloud Wars for more.

What is up fraud fighters, and welcome to Fraud Forward!AI is accelerating fraud, 100 percent. But the bigger risk, the thing that should keep every fraud leader up at night, is what happens when fraud teams stop thinking strategically because the queue never ends.In Part 2 of Fraud Forward, I'm back with Ted Josephson, VP of Bank Fraud & Credit Strategy at Synchrony Financial, and we are getting into fraud leadership at the enterprise level, where strategy, AI, automation, and culture collide.Because let me just assure you, fraud prevention at scale requires more than tools. It requires fraud leadership strategies, fraud team leadership that protects time for long-term planning, and strategic fraud solutions that can separate normal fraud noise from the signals of a true fraud shift.Then we get direct about AI. Where it's delivering real value today, where the industry is still overhyping “AI” that is not actually learning, and why certain decisions, especially first-party fraud, should never be fully automated without human accountability and empathy.And fraud fighters, we close with what Ted thinks is being underestimated right now, and it's big. Agentic commerce creating a new accountability and disputes nightmare, plus the rise of casual “friendly fraud” as a cultural norm. Because fraud prevention evolution is not just a technology program, it is bank fraud leadership and credit risk leadership in action. This is fraud prevention innovation, and it demands strategic fraud decisions.What you'll hear in this episode:How enterprise fraud teams protect time for long-term strategy when fraud never stopsWhy planning cannot be an extra, it has to be scheduled like any other critical operating functionHow to tell the difference between normal fraud noise and the signals of a systemic weaknessWhat separates a short-term spike from a true fraud shiftWhere AI is delivering real value today, including consistent case narratives and operational efficiencyWhere the industry is still overhyping “AI” that is not actually learningWhy certain decisions, especially first-party fraud, should never be fully automated without human accountability and empathyWhy agentic commerce could create a new accountability and disputes nightmareHow casual “friendly fraud” is becoming normalized, and why that cultural shift mattersHow banking fraud strategy and credit strategy leadership collide in enterprise fraud teamsYou should listen to this episode if you:Lead fraud solutions leadership efforts and you feel like the urgent is crowding out the importantRun fraud prevention at scale and need a better framework to separate noise from true fraud shiftsAre building fraud leadership development for your team and want practical, real-world strategyManage enterprise fraud teams and need strategic fraud insights you can apply immediatelyOwn bank fraud leadership responsibilities and want to pressure test your strategic fraud solutionsAre navigating credit risk leadership decisions alongside fraud risk and disputesAre worried about agentic commerce, dispute accountability, and what comes nextAre watching “friendly fraud” become a cultural norm and need fraud leadership strategies to respondIf you liked this episode, be sure to subscribe and review the podcast on iTunes, Spotify, YouTube, or wherever you listen to podcasts. It really helps with getting the word out.

This week, Paul and Jess give their very amateur Oscar's predictions for the top awards. Next, they discuss the release of AI Agents who are intended to streamline, iterate, and accelerate the creative process, and wonder if their success will increase the volume of projects or just reduce job opportunities, or both. Next, they discuss how the prospect of using AI to generate content based on proven IP libraries may be driving the surge in deal making, and whether its sustainable. Learn more about your ad choices. Visit megaphone.fm/adchoices

Contact centers have long been built on fragmented systems — CRM for customer data, separate platforms for calls and messaging, and AI layered on top. But that model is starting to change. In this episode of The Modern Customer Podcast, in partnership with Salesforce, Blake Morgan speaks with Gautam Vasudev, SVP of Agentforce Contact Center at Salesforce, about the rise of the agentic contact center — and how companies are beginning to unify AI agents, customer channels, and CRM data on one platform. #ad One key idea: when AI agents and human agents share the same context, customers no longer have to repeat their problem multiple times they're transferred. The conversation explores: Why contact centers have remained fragmented How AI and human agents can work together What shared customer context means for CX leaders This episode is sponsored by Salesforce. Learn more about Agentforce Contact Center.  Blake Morgan was called "The Queen of CX" by Meta. She is a customer experience futurist and author of three books on customer experience. Follow Blake Morgan on LinkedIn For regular updates on customer experience, sign up for her weekly newsletter here. Learn more at www.blakemichellemorgan.com 

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.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Treasury is emerging as one of the fastest-moving functions in enterprise AI adoption. In this episode, host Owen McDonald sits down with Leo Gil, Bottomline's treasury technology expert, to explore how AI is helping treasurers move beyond manual, back-office work and into more strategic decision-making roles. Packed with practical insights for treasury and finance leaders, discover how AI is already reshaping treasury today and what's coming next.

In this follow-up to our last episode on AI in the tech industry, Host Angie Dickson, President of the Inogen Alliance and EVP of Antea Group USA, sits down with Karl Huntzicker, Global VP of Health and Safety at Salesforce, to look ahead at the future of AI in EHS. Karl shares how the move from bots to agents marks the beginning of what he calls the “agentic era,” where digital tools are not just answering questions but taking action, conducting investigations, and helping EHS professionals focus where it matters most. The discussion highlights opportunities for augmentation, the evolving idea of a digital workforce, and the hope that AI will finally allow EHS leaders to achieve long-standing goals. --------- Guest Quote: “I really want to look back in five years and say we built agents that made sense, that helped our employees, that provided care to our employees, and that moved the health and safety program forward.” – Karl --------- Time Stamps 00:32 Bots vs. Agents – What's the Difference? 04:00 From Incident Investigations to the Agentic Era 07:13 Augmenting EHS Teams Without Losing Focus on People 10:22 The Digital Workforce: Opportunities and Challenges 13:00 Becoming “Bionic” – Augmentation and Superpowers 14:13 Hopes for the Next Five Years in EHS --------- Sponsor copy Rethinking EHS is brought to you by the Inogen Alliance. Inogen Alliance is a global network of 70+ companies providing environment, health, safety and sustainability services working together to provide one point of contact to guide multinational organizations to meet their global commitments locally. Visit http://www.inogenalliance.com/ to learn more.  --------- Links  Inogenalliance.com/resources Inogenalliance.com/podcast  Angie on LinkedIn: https://www.linkedin.com/in/angeliquedickson/  Karl on LinkedIn: https://www.linkedin.com/in/karlhuntzicker/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Virtuals introduces the ERC-8183 Agentic Commerce Standard. The EF increases its bug bounty program reward to $1 million. LI.​FI introduces an API for Agentic Commerce. And BitMine holds 4.5 million ETH. Read more: https://ethdaily.io/899 Are you running a treasury? You need liquidity but don't want to sell ETH? Get the lowest fixed rates to borrow against ETH and LSTs on Liquity V2 on liquity.org  Disclaimer: Content is for informational purposes only, not endorsement or investment advice. The accuracy of information is not guaranteed.

Finland & Estonia Travelogue Hospital Tech CES 2026: ViewSonic Foldable and 4K/5K Monitors VS Code for Agentic Editing with Codex — by Eddie Tonkoi Support the Show CCATP #830 — Adam Engst on How Siri Could Become the Mac's New Help System Transcript of NC_2026_03_08 Join the Conversation: allison@podfeet.com podfeet.com/slack Support the Show: Patreon Donation Apple Pay or Credit Card one-time donation PayPal one-time donation Podfeet Podcasts Mugs at Zazzle NosillaCast 20th Anniversary Shirts Referral Links: Setapp - 1 month free for you and me PETLIBRO - 30% off for you and me Parallels Toolbox - 3 months free for you and me Learn through MacSparky Field Guides - 15% off for you and me Backblaze - One free month for me and you Eufy - $40 for me if you spend $200. Sadly nothing in it for you. PIA VPN - One month added to Paid Accounts for both of us CleanShot X - Earns me $25%, sorry nothing in it for you but my gratitude

In this episode of Crazy Wisdom, Stewart Alsop sits down with Andre Oliveira, founder of Splash N Color, a bootstrapped 3D printing e-commerce business selling consumer goods on Amazon. The two cover a lot of ground — from how Andre went from running 40 FDM printers out of South Florida to offshoring manufacturing to China, to how he's using Claude Code to automate inventory management and generate supplier RFQs across 200+ SKUs. The conversation stretches into bigger territory too: the San Francisco AI scene, the rise of AI agents and what they mean for the future of the internet, whether local on-device AI will eventually replace cloud-based tools, and why building physical products will stay hard long after software becomes easy. It's a candid, wide-ranging conversation between two self-taught builders figuring things out in real time. Follow Andre on X: @AndreBaach.Timestamps00:00 — Andre introduces Splash N Color, his Amazon-based 3D printing e-commerce business and explains the grind of running 40 FDM machines in South Florida.05:00 — The conversation shifts to Claude Code and how Andre built an inventory automation system to manage sales velocity and RFQs across 200+ SKUs.10:00 — Stewart and Andre compare notes on Opus 4.6, debate Codex vs Claude, and Andre breaks down the new Agent Teams feature in Claude Code.15:00 — Discussion turns to the San Francisco AI scene, the viral OpenClaw launch event that drew 700 people, and what's capturing the city's imagination right now.20:00 — The pair wrestle with data privacy, the illusion of it since 2000, and whether full transparency of personal data might actually serve people better.25:00 — Stewart pitches his vision of local on-device AI replacing cloud tools entirely, and they debate the 10–15 year timeline for mainstream societal adoption.30:00 — Andre traces his origin story: a high school dropout from Brazil who spotted a 3D printing opportunity on Facebook Marketplace and got lucky timing with COVID.35:00 — They explore whether AI-generated 3D models and DfAM will automate physical manufacturing, and why proprietary specs keep the space stubbornly hard.Key InsightsLifestyle businesses deserve more respect. Andre spent months feeling inadequate scrolling through Twitter watching founders announce funding rounds, before realizing his cash-flowing, location-independent business was already the goal. The social media version of entrepreneurial success warped his perception of what he actually had built.Claude Code is becoming an operating system. Stewart describes running Claude Code as having a second OS on top of MacOS — one that makes the underlying machine legible in ways it never was before. Both guests use it not just for coding but as a primary interface for understanding and operating their businesses.Agent Teams changes how work gets done. Andre explains that Claude's new multi-agent feature lets you assign a team lead and specialized roles that communicate with each other in parallel, essentially running an autonomous task force inside your terminal — a meaningful leap beyond single-instance prompting.Physical manufacturing will stay hard. Even as AI-generated 3D models improve, tolerances of 0.5 millimeters can mean the difference between a product working or not. Design for manufacturing is a separate discipline from design itself, and proprietary specs mean open source models rarely hit commercial quality.The internet is heading toward agents. Both guests agree that AI agents will increasingly handle tasks humans currently do manually online — booking services, making payments, coordinating logistics — with the human internet potentially becoming secondary to a machine-to-machine layer.Iteration is the real value of 3D printing. Andre pushes back on 3D printing as a business unto itself, framing it instead as a prototyping tool. The true value is rapid iteration on housing, tolerances, and fit — not the printer, but the speed of the feedback loop it enables.Technology compounds in layers. Andre closes with a tech-tree analogy: each generation normalizes the tools of the previous one and builds the next layer on top. Agentic coding today is what the internet was in the 90s — the foundation for something we can't yet fully see.

In this episode of Confessions of Supply Chain Executives, host Chris Walton sits down with Omar Akilah, SVP of Product at Infios, and Aadil Kazmi, Head of AI Product Development at Infios, to tackle one of the biggest questions facing retail leaders today: Are retailers actually ready for agentic AI? While AI dominated the conversation at NRF, the reality inside many retail organizations is far more complicated. Many companies are still struggling with fragmented systems, unclear strategies, and uncertainty about where AI should even be applied. Omar and Aadil break down what agentic AI really means for commerce, how it differs from traditional generative AI, and why the biggest opportunity may not be flashy customer experiences but rather the operational backbone of retail: supply chain execution. From autonomous order monitoring to real-time visibility across the entire order lifecycle, they explore how agentic AI could fundamentally reshape how retailers manage fulfillment, delivery promises, and operational decision making. The conversation also challenges common assumptions about AI readiness, including why retailers may not need perfect data infrastructure to begin adopting agentic AI and what leaders should actually focus on in the next 30 days if they want to stay competitive. Key topics covered: • What agentic AI actually means for retail operations • Why most retailers are unprepared for the next wave of AI • The difference between generative AI and agentic AI • Why supply chain execution is a prime use case for AI agents • How autonomous order visibility can transform customer experience • Why retailers may not need a perfect data lake to begin adopting AI • The three ways retailers can approach AI adoption • How to avoid getting stuck in “AI pilot purgatory” • The first practical AI use cases retailers should implement

Customer service leaders face rising pressure to resolve more interactions faster, while maintaining high-quality experiences — and many legacy systems and processes can't keep up. In this episode, Craig Walker, CEO of Dialpad, joins Daniel Faggella, Emerj CEO and Head of Research, to break down how AI can augment human agents to handle routine requests like order status and password resets, freeing teams to focus on complex issues. He shares actionable strategies for enterprise leaders, from cleaning knowledge bases and analyzing ticket patterns to running controlled pilots and scaling AI agents across the organization. Craig also explains how AI can coach agents in real time and surface insights for managers, creating a continuously improving support system that drives measurable ROI. This episode is sponsored by Dialpad. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1 Want to share your AI adoption story with executive peers? Click emerj.com/expert for more information and to be a potential future guest on the 'AI in Business' podcast!

Are we moving too fast in the world of agentic commerce — a new paradigm in online shopping where AI agents act on behalf of consumers, facilitating transactions and product discovery? Unlike traditional e-commerce, where consumers interact directly with platforms, agentic commerce leverages advanced technologies to streamline the purchasing process.In this episode of One Vision — FinTech Fuse, we dive deep into the rapidly shifting landscape of agentic commerce and the alphabet soup. With the technology landscape changing at an unprecedented pace, we explore the challenges and opportunities that arise in the new world.Joining us in the discussion are industry experts, Dr. Efi Pylarinou and Jas Shah, who offer their insights on the rise of different protocols like ACP and UCP, identity verification, and the importance of a level-playing field in the future of commerce.What's your take on this fast-paced evolution? Let's keep the conversation going!#FinTech #AI #AgenticCommerce #AIAgents00:00 Welcome and Setup: The Agentic Commerce Alphabet Soup02:53 The Reality: Are We Moving Too Fast?07:35 Who Writes The Rules? 10:03 Which Protocol Will Win?16:20 Staying Visible: Banks Brand in Bot Era21:04 Trust Data and Curation25:44 The Economics and Gatekeepers33:57 Predictions: Who Will Emerge as The Likely Winner41:56 What Banks Should Do NextHot take: The real battle is about protocols, not models.Hot take: The future belongs to those who can optimize for AI.Keywords AI, agentic AI, commerce protocols, fintech, banking, digital transformation, identity, trust, UCP, ACPMore about our guests

In this episode of The Block Runner Podcast, hosts William and I-man dive into the transformative wave of agentic AI and its societal impact. They explore how AI is reshaping daily activities, influencing markets like crypto, and creating a new inflection point for personal and professional productivity. The episode covers the impending changes predicted for 2028, the exponential growth of AI, and how individuals and businesses can leverage these advancements to stay ahead. William and I-man also discuss the importance of applying first principles thinking and building scalable AI solutions to thrive in this new era. Watch the full episode on YouTube: https://www.youtube.com/@TheBlockRunner Subscribe to our newsletter at TheBlockRunner.com

In less than five years, launching a third-party marketplace has gone from a questionable move to a strategic imperative for many major retailers. Recorded live at NRF 2026, this episode of Retail Remix digs into that shift with Scott Eckert, CEO of the Americas at marketplace operator Mirakl.Scott explains why retailers are embracing curated marketplaces as an offensive growth strategy — no longer just as a defensive reaction to Amazon — and how brands like Ulta Beauty, Best Buy and Lowe's are expanding assortment without diluting brand identity.The conversation also dives into how AI answer engines are reshaping product discovery, and why clean, machine-readable catalog data may soon matter more than traditional SEO. Plus, Scott shares Mirakl's growing role in retail media and the company's vision of becoming an orchestration layer across emerging AI-driven commerce channels.Key TakeawaysHow the proving power of Amazon and, perhaps more importantly, Walmart has completely shifted retailers' attitude toward online marketplaces;Why retail media and marketplace strategies increasingly go hand in hand;The important role marketplaces will play in the world of AI commerce, when done right;Why product data must be optimized differently for different AI platforms like OpenAI, Google, and Anthropic; andThe essential quality of a truly disruptive product or service. Related LinksLearn how Mirakl powers enterprise marketplaces and retail mediaRelated reading: Mirakl CEO: Marketplaces are ‘Arming the Rebellion' of Traditional Retail Against Big TechRelated reading:Best Buy's New Third-Party Marketplace is Now LiveExplore more NRF26 coverage and retail insights from Retail TouchPointsSubscribe so you don't miss more episodes of Retail Remix from the show floor of NRF26

We're focusing on an emerging branch of artificial intelligence called agentic AI – that is, an AI tool that can, essentially, act like a booking agent, all the way up to making a reservation on the traveler’s behalf. It acts like an agent – but is it a threat to human travel advisors? And what does agentic AI mean for the OTA model, supplier customer service and travelers themselves? On this episode, McKinsey and Co.’s Vik Krishnan and Travel Weekly aviation editor Robert Silk talk with host Rebecca Tobin about the latest developments in agentic AI and travel and where the technology could lead us. Episode sponsor This episode is sponsored by AmaWaterways https://www.amawaterways.com Winter series: This episode is part of our annual Winter Series, where we feature some of our favorite recent Folo by Travel Weekly discussions. This episode was originally published Nov. 24 and has been edited for length and clarity. Related links Agentic AI turns searches into sales https://www.travelweekly.com/Travel-News/Travel-Technology/Agentic-AI-turns-searches-to-sales Hotel and flight bookings are coming to Google's AI Mode https://www.travelweekly.com/Travel-News/Travel-Technology/Hotel-and-flight-bookings-coming-to-Google-AI-ModeSee omnystudio.com/listener for privacy information.

Marty sits down with Bitcoin developer Matt Corallo to discuss why the emergence of AI coding tools and agentic payments represents the most critical and time-sensitive opportunity in Bitcoin's history to become the dominant payment rail of the internet. Matt on X: https://x.com/TheBlueMatt STACK SATS hat: https://tftcmerch.io/ Our newsletter: https://www.tftc.io/bitcoin-brief/ TFTC Elite (Ad-free & Discord): https://www.tftc.io/#/portal/signup/ Discord: https://discord.gg/VJ2dABShBz Opportunity Cost Extension: https://www.opportunitycost.app/ Shoutout to our sponsors: Bitkey https://bitkey.world/ OPNEXT https://tinyurl.com/tftc2026 Unchained https://unchained.com/tftc/ SLNT https://slnt.com/tftc Salt of the Earth: https://drinksote.com/tftc Join the TFTC Movement: Main YT Channel https://www.youtube.com/c/TFTC21/videos Clips YT Channel https://www.youtube.com/channel/UCUQcW3jxfQfEUS8kqR5pJtQ Website https://tftc.io/ Newsletter tftc.io/bitcoin-brief/ Twitter https://twitter.com/tftc21 Instagram https://www.instagram.com/tftc.io/ Nostr https://primal.net/tftc Follow Marty Bent: Twitter https://twitter.com/martybent Nostr https://primal.net/martybent Newsletter https://tftc.io/martys-bent/ Podcast https://www.tftc.io/tag/podcasts/

Marty sits down with Bitcoin developer Matt Corallo to discuss why the emergence of AI coding tools and agentic payments represents the most critical and time-sensitive opportunity in Bitcoin's history to become the dominant payment rail of the internet. Matt on X: https://x.com/TheBlueMatt STACK SATS hat: https://tftcmerch.io/ Our newsletter: https://www.tftc.io/bitcoin-brief/ TFTC Elite (Ad-free & Discord): https://www.tftc.io/#/portal/signup/ Discord: https://discord.gg/VJ2dABShBz Opportunity Cost Extension: https://www.opportunitycost.app/ Shoutout to our sponsors: Bitkey https://bitkey.world/ OPNEXT https://tinyurl.com/tftc2026 Unchained https://unchained.com/tftc/ SLNT https://slnt.com/tftc Salt of the Earth: https://drinksote.com/tftc Join the TFTC Movement: Main YT Channel https://www.youtube.com/c/TFTC21/videos Clips YT Channel https://www.youtube.com/channel/UCUQcW3jxfQfEUS8kqR5pJtQ Website https://tftc.io/ Newsletter tftc.io/bitcoin-brief/ Twitter https://twitter.com/tftc21 Instagram https://www.instagram.com/tftc.io/ Nostr https://primal.net/tftc Follow Marty Bent: Twitter https://twitter.com/martybent Nostr https://primal.net/martybent Newsletter https://tftc.io/martys-bent/ Podcast https://www.tftc.io/tag/podcasts/

How do brands scale AI governance without slowing down innovation? In this episode, Yael Kochman sits down with NRF leaders Christian Beckner and Caroline Reppert to discuss the industry's shift toward responsible, high-ROI AI adoption. While this conversation was recorded just before the NRF Big Show, the insights remain the definitive roadmap for the year ahead. They dive into why the most successful retailers are prioritizing internal productivity tools and "Agentic" commerce guardrails before rolling out customer-facing AI. Key Topics Covered: - The Governance Shift: Why the CEO and Board are now leading the AI policy conversation - Internal First: How coding and productivity tools are providing the first real wins for ROI - Empowering Employees: Using AI chatbots to support store associates and improve the customer experience - The 2025 Benchmark: Insights from the now-published Retail AI Trends report The report mentioned in this episode is now live! Get the full benchmark data on how your peers are investing in AI today.

Today's guest is Carey Smith, Former President and CIO of XcelerateHealth and Chief Technology Innovation Officer (CTIO) of Blue Cross and Blue Shield of Minnesota. XcelerateHealth is a health-tech startup and business unit of Blue Cross and Blue Shield of Minnesota, focused on AI-driven digital products to transform healthcare insurance experiences. Carey joins Emerj's Nick Gertsch to discuss how leaders can structure talent and workforce AI so decisions are consistent, reviewable, and aligned with organizational controls. Smith also shares practical steps for tightening decision rights, improving data readiness, and designing workflows where AI accelerates hiring and mobility without increasing risk. This episode is sponsored by Eightfold AI. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner Want to share your AI adoption story with executive peers? Click emerj.com/expert for more information and to be a potential future guest on the 'AI in Business' podcast!

Quick Howto: ZIP Files Inside RTF https://isc.sans.edu/diary/Quick+Howto+ZIP+Files+Inside+RTF/32696/#comments Keeping the Internet fast and secure: introducing Merkle Tree Certificates https://blog.cloudflare.com/bootstrap-mtc/ Taming Agentic Browsers: Vulnerability in Chrome Allowed Extensions to Hijack New Gemini Panel https://unit42.paloaltonetworks.com/gemini-live-in-chrome-hijacking/

Consumers aren't lacking for choice. Instead, they're usually drowning in a sea of options, and it's up to brands to find ways to go beyond simply removing friction and bring back the joy in shopping. Adding AI, and agentic AI into the mix can unlock new opportunities, but also brings with it new challenges. We're going to talk a little about all of it.We are recording here at eTail Palm Springs, and hearing from leading brands and the platforms and companies they rely on to innovate in retail. To help me discuss these topics, I'd like to welcome back to the show Noah Zamansky, VP Product, Tech, & Design, Client Experience at Stitch Fix About Noah Zamansky Noah Zamansky serves as the Vice President of Product and Client Experience at Stitch Fix, where he leads cross-functional teams spanning Product, Design, Engineering, Algorithms, and Platform Development. A seasoned leader, Noah has a proven track record of shaping product vision and strategy, designing exceptional user experiences, and spearheading the launch of new business ventures. Before joining Stitch Fix, Noah held the role of Senior Director of Product Management at eBay, overseeing Fashion and Vertical Experiences. Noah Zamansky on LinkedIn: https://www.linkedin.com/in/nzamansky/ Resources Stitch Fix: https://www.stitchfix.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://aglbrnd.co/r/d15ec37a537c0d74 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

While Anthropic and the Pentagon fought, OpenAI swooped in to secure a big deal. But at what cost? And while it seemed like the entire AI news world was wrapped up in the Anthropic-Trump-OpenAI drama, the rest of big tech went nuts. Microsoft teased something agentic, Claude actually shipped it, and Perplexity dropped probably its most important product to date. This week's theme apparently: drama and agents. We'll get you caught up on all of the AI News That Matters.