Podcasts about agentic

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

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

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

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

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

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

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

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

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

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

Finance Presenter Chua Tian Tian had been under the radar for the past two weeks on her annual vacation across Asia, but she’s not coming home without bringing our listeners a little something – a Special episode of Under the Radar from AI chip darling NVIDIA’s GTC Taipei, which took place in the first week of June. GTC Taipei 2026 brought together developers, researchers and industry leaders to dive into the latest breakthroughs shaping every industry, from AI factories, agentic and reasoning AI, physical AI and robots and even more. Think of a reinvention of the personal computer by Nvidia and Microsoft to allow the running of personal AI agents. In this Special, “On the Go” episode of Under the Radar, Tian Tian gave an overview of the highlights at NVIDIA GTC Taipei.See omnystudio.com/listener for privacy information.

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

GFTN's Pat Patel on building Point Zero Forum, the future of stablecoins and agentic AI, and why coexistence beats winner-takes-all in the next wave of digital money.

Food delivery app Doordash will now allow you to upload pictures of food and have artificial intelligence handle the purchase and delivery of ingredients, among other features. Learn more about your ad choices. Visit podcastchoices.com/adchoices

What happens when customers stop opening banking apps and start managing their finances through AI assistants?In this episode, we sit down with Mathias Fanschek, Head of Digital Transformation and Retail Strategy at Raiffeisen Bank International, to explore how one of Europe's largest banking groups is preparing for a future of headless banking, agentic commerce and AI-powered customer experiences.With 18 million customers across 11 markets and managing over €200 billion in assets, Mathias shares what it really takes to move generative AI from experimentation to production. We had a good discussion about virtual mobile assistants, transforming legacy data infrastructure, and managing executive expectations in a rapidly changing, highly regulated landscape.You'll also hear Mathias' perspective on Revolut's new PRAGMA model, why context is the missing ingredient in today's AI experiences and how banks can remain trusted intermediaries as customers increasingly interact through AI-powered distribution channels.

What if agentic AI makes SRE more important, not less? Bennett Gould explains why autonomous AI systems may create more demand for reliability thinking — not less.Everyone seems to think AI is coming for SRE in a hard way.You might have heard the same story:“AI will write the code.”“Agents will handle incidents.”“Copilots will generate the runbooks.”“Automation will reduce operational load.”Yes, the job question is real. If AI can write code, summarize incidents, query observability tools, generate runbooks, and operate across systems, then engineers are right to ask what happens to the work.But here's the part that gets missed: AI does not just automate reliability work. It creates more objects and surface areas that need to be made reliable.Agentic AI is moving from demos into real workflows. These systems are no longer just answering questions. They are querying tools, pulling context, generating changes, and in some cases taking action around production environments.That makes this a Monday morning problem.Teams are already using LLMs for incidents, documentation, observability, infrastructure, and operational decision-making. Somewhere, a team is one demo away from giving an agent access to tools originally designed for humans.That is exactly why I wanted to have this conversation.Bennett Gould is currently a solution engineer at Neubird.ai. His career in SRE and SRE-adjacent work spans large enterprises, cloud, industrial technology, and startups, including AWS, IBM, Siemens, and a YC startup.I wanted to ask him a simple question: What in the agentic AI is happening to SRE?Here are 3 highlights from our talk:1. Agentic AI increases the reliability surface areaThe obvious fear is that AI reduces the need for reliability engineers. Bennett's view was more nuanced. He was clear that engineers still need to adapt. If people do not reskill, stay current, and learn how these systems are forming, there may absolutely be pressure in the job market. But he also argued that AI could create more demand for reliability skills because production complexity is increasing.More code is going into production.More AI-generated code is going into production.More systems that people do not fully understand are going into production.And now autonomous agents are starting to enter production workflows too.That means more surface area. More automation. More operational uncertainty. More ways for things to go wrong.Bennett compared this to Terraform: Infrastructure as code created enormous efficiency gains. But it also created new ways to make very big mistakes very quickly.Before Terraform, most people could not delete all their production resources with a single command. After Terraform, that became technically possible if the system was designed badly enough.Agentic AI follows a similar pattern. With great automation comes great responsibility.Agents can help engineers move faster, query tools, summarize context, and reduce toil. But they can also amplify weak engineering practices, poor boundaries, bad assumptions, and unclear operational ownership. That is not the end of reliability work. That is reliability work entering a new phase.2. Agents can reduce toil, but context is the ceilingOne of the strongest parts of the conversation was Bennett's explanation of where agents can help in incident response. A lot of SRE work involves moving across tools.You may need to query Prometheus, Dynatrace, logs, traces, cloud consoles, ticketing systems, documentation, runbooks, dashboards, and architecture diagrams.The problem is not always that the engineer lacks judgment.Sometimes the problem is that the information is scattered across too many tools, each with its own query language and interface. Bennett gave a simple example: an engineer might be very good at PromQL and very fast when Prometheus is the source of truth. But if the same engineer has to work in a different observability platform with a different query language, their response time can suffer. That is an obvious place where agents can help.The engineer may not need to know every query language perfectly. They need to know what they are looking for and how to reason about the system. The agent can help translate that intent into the right tool calls, queries, and summaries.That could reduce MTTR. It could reduce toil. It could help engineers move faster during incidents.But Bennett also made the limitation clear: You are only as good as the context you have. This is where he introduced two useful concepts:* Context mining* Context distillationContext mining means proactively finding the information that might be useful in a given operational situation.Context distillation means taking large amounts of information — runbooks, Confluence pages, diagrams, documentation, prior incidents — and reducing it into the minimum useful context an LLM or agent can use.That sounds powerful. But there is a catch. Sometimes the context simply is not there.Many of the largest and most complex organizations still run legacy systems where knowledge lives in people's heads, stale documentation, tribal memory, and unwritten assumptions.There may not be a clean process for turning that into usable context. That matters because agents do not magically understand your system. They work with the context they are given. If the context is missing, outdated, or wrong, the agent's usefulness maxes out early.3. Agentic systems are not just LLM demosA basic LLM workflow is relatively easy to demo:You give it a prompt.You connect a few tools.You add some APIs.You get a useful answer.That is impressive, but it is not the same thing as running an agentic system in a meaningful production environment.Bennett made a useful analogy here: running your own infrastructure versus using a hyperscaler.Cloud providers removed a lot of undifferentiated heavy lifting. Most companies do not want to spend half their time racking servers, managing data centers, and dealing with low-level infrastructure when they are trying to serve customers.Agentic systems create similar questions:* What parts of the work should be handled by the system?* What parts still need engineering discipline?* And what has to exist around the model before it is safe and useful?That surrounding structure is where the real work begins. Bennett called this harness engineering. Once you move beyond an LLM demo, you have to think about memory, learning, tool usage, identity, federation, security, evaluations, and guardrails.That is a very different problem from “the model gave a good answer on my laptop.” SREs know why that distinction matters. “It works on my machine” is not an acceptable reliability strategy.A runbook that recovers a thousand-node database cannot be non-deterministic, undocumented, and dependent on someone's local setup. If it is part of the operational backbone, it needs to be reliable.Agentic AI does not remove that requirement. It makes it more important.Bonus: Agents expose weak engineering practicesAgentic AI not only introduces new problems but it also reveals old ones.* Weak APIs.* Brittle runbooks.* Missing context.* Poor evals.* Unclear tool boundaries.* Operational shortcuts.Systems that were designed assuming careful human use may behave very differently when AI agents start using them. That is why this conversation matters for SRE.Agentic AI is not only a productivity story. It is a reliability story.It forces teams to ask whether their existing practices are strong enough for a world where more actions can be generated, recommended, or executed by autonomous systems.The silver lining for reliability workAgentic AI does not remove the need for reliability thinking. It raises the bar for it. The tools will change. The workflows will change. Some tasks will absolutely be automated or reshaped.But the hardest parts of reliability are still the hard parts:* understanding the system* knowing the trade-offs* building reliable operational processes* making good judgment calls under uncertainty and* owning the outcome when something changes in productionThat is why SRE does not disappear in an agentic AI world.It becomes one of the disciplines that makes the agentic AI world survivable.So if your team is already using AI around incidents, observability, runbooks, infrastructure, or production workflows, the question is not whether the future is coming. The future is already in the workflow.The real question is whether your reliability practices are ready for it. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit read.srepath.com

久違的 TBB 三寶相隔五個月再度合體！大談 WWDC26 感想！兒童控制功能搞到 Daniel PTSD 發作？Anson 覺得中國評測規範矯枉過正！Wallace 質疑NVIDIA RTX Spark 究竟會否成功

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

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

Content's value is in the intelligence it brings, regardless of what system it's found in. But there is a lot of enterprise content across many, many systems.On the Mostly Unstructured Podcast, KeyMark CMO Clay Tuten sits down with Mike Askren, VP of Product at Hyland, on how document management and ECM are becoming an intelligence layer for agentic AI, and the right size and scale problems to tackle with agents.Topics explored: Why has enterprise value moved from storing and securing content to extracting intelligence from it? How content federation connects AI services to content across on-prem, cloud, and hyperscaler systems. What an enterprise context engine does, and why the relationships between documents matter more than the engine itself. Why agentic governance matters so much. Monitoring, coaching, and shutting down agents that hallucinate or run on stale instructions. Why the highest-ROI AI work comes from the processes that are least exciting, but have the highest volume of occurrence. Questions this episode answers: What is the intelligence layer in enterprise content management? How much enterprise data is unstructured, and why does it matter for AI? What is content federation and why is it needed for enterprise AI? What is agent governance and how is it different from data governance? How do you get ROI from AI without replacing your existing systems? Where should a CIO start when moving ECM into an AI intelligence layer? What is intelligent document processing (IDP) and how does it relate to agentic automation? Subscribe for more AI talk on content intelligence, IDP, and agentic AI from the team at KeyMark, or reach out if anything caught your ear.Timestamps:00:00 – From storage to intelligence: the ECM shift01:58 – What "unstructured content" really means03:01 – Mike's role at Hyland and content federation04:11 – The content-fueled agentic enterprise06:45 – Why 70–90% of enterprise data goes untapped08:03 – Agentic governance and context you can trust09:25 – Human-in-the-loop feedback and coaching agents10:22 – The control tower: monitoring and stopping agents12:03 – Agents as digital employees13:45 – Advice for CIOs under pressure15:23 – Start small: the attainable win, not the moonshot18:39 – Where the ROI actually hides19:47 – Practical outcomes: claims, HR, government21:03 – First steps into the intelligence layer24:45 – From IDP to agentic automation to new workflows27:19 – Slow down, ask questions

Recorded on the LHV Bank booth at Money20/20 Europe in Amsterdam, this second episode in our LHV‑partnered series, and our third episode from the event brings together six leaders shaping the future of global payments, embedded finance, and AI‑driven commerce. Russell Goldsmith was joined by: 1/ Daniel Kornitzer, Head of Global Partnerships, Ebanx 2/ Kunal Galav, VP of Pleo Embedded, Pleo 3/ Sophie Condie, Chief Executive Officer, Shieldpay 4/ John O'Beirne, CEO & Executive Director, Square International, Block 5/ James Neville, CEO, Yaspa 6/ Anthony Peculic, Interim CPO, Marqeta A fast‑paced, insight‑rich episode capturing the themes dominating Money20/20 Europe: emerging‑market innovation, embedded finance, agentic AI, and the new trust layers required to power the next generation of global commerce.

Most apartment operators think they know who they're competing against. According to Jonas Bordo, they're probably missing the bigger picture.In the second half of Reid's conversation with the Dwellsy CEO, Jonas explains why renters don't think in traditional comp sets, how AI could soon replace apartment search as we know it, and why the future belongs to open platforms that connect renters, properties, and intelligent agents. It's an eye-opening conversation about technology, consumer behavior, and the forces reshaping housing.Whether you're in multifamily, proptech, marketing, or operations, Jonas offers a fresh perspective on where the industry is headed—and why the biggest changes may arrive much sooner than most people expect.

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

It's official: Knownwell is now part of 2X, and together we're building the leading human-agentic GTM services company, unifying B2B marketing, sales, and customer success. In this special in-person episode of AI Knowhow, Knownwell CEO David DeWolf and 2X founder Dom Colasante join host Courtney Baker at 2X headquarters to break down the news and what drove the acquisition, including: why software and services are converging into a single category and what humans uniquely own in an agentic world. In this episode: The big news: 2X acquires Knownwell to build the first human-agentic GTM services company The trend permeating the services world: customers buy outcomes, not software or services Go-to-market fragmentation, and why marketing, sales, and customer success must run as one motion The 90/10 retention paradox every revenue leader should know Why all work should have a human in the loop Moving Knownwell's commercial intelligence up the stack into sales and marketing Show Notes: Read today's press release: https://2x.marketing/press-release/2x-acquires-knownwell/ Connect with David DeWolf: https://www.linkedin.com/in/ddewolf/ Connect with Dom Colasante: https://www.linkedin.com/in/domeniccolasante/ Connect with Courtney Baker: https://www.linkedin.com/in/courtbaker/

Join Itai Gafni, Co-Founder and CEO of Huskeys, for an unvarnished evaluation of why web application firewalls (WAF) have remained functionally stuck in the 1990s. While modern application traffic has evolved from human browsers to a complex matrix of APIs, automated microservices, and autonomous AI agents, legacy WAF solutions still rely on brittle, static rule sets. An alumnus of Israel's elite Unit 8200 where he engineered advanced intelligence and cyber platforms, Itai is leading a massive paradigm shift. In this episode, we discover why security teams are terrified of updating their firewall rules—and how introducing an agentic control plane allows enterprises to optimize threat detection without breaking production or driving away legitimate customer revenue.

The finance industry wants to use artificial intelligence agents to get customers to spend more, faster, bigger...But AI agents don't mix easily with the security standards that ensure client safety in payments.For more, listen to the latest episode of Unseen Money from New Money Review, featuring Paul Amery and Timur Yunusov.

Most leaders think they are delivering a great customer experience. Pierre Charchaflian of IBM says they are delivering yesterday's version. The new standard is not fixing problems when customers report them. It is knowing about the problem before the customer does, and solving it before they have to ask. That shift, from reactive to anticipatory, is what separates the brands that customers stay loyal to from those they leave without explanation. The technology to do it exists right now. Most companies are not using it. Pierre has spent 25 years at the intersection of data, technology, and customer experience, and he says this transformation is unlike anything he has seen before. The window to act is open. It will not stay that way. What You Will Learn About Anticipating Customer Needs With AI: What agentic AI actually is in plain language, why it is fundamentally different from prior AI capabilities, and what it means for your CX strategy starting now Why IBM's research found that technology stack limitations, not budget or talent, are the number one barrier preventing CMOs from delivering the customer experience they already know they need to deliver How agentic search engines are becoming a direct threat to brand digital presence, and what leaders need to do before their customers' AI agents start bypassing them entirely Why anticipating a customer's need before they express it is now a measurable competitive advantage, and what separates the companies building that capability from the ones still reacting How AI can read sentiment, detect frustration signals across structured and unstructured data, and trigger a response before a customer decides to leave Why conversion is the metric that tells the truth about whether your customer experience is actually working, and what NPS and CSAT consistently miss Download IBM's Win the Moment report now: https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/customer-intent?utm_id=Stacy-Sherman-AdobeSummit-LinkedIn-IBVCMOStudy-04-16-26 #IBMPartner Have a question or thoughts to share? Leave a voice message: https://www.speakpipe.com/StacySherman Learn more at DoingCXRight.com and subscribe to the newsletter for more actionable strategies.

Anyone can build software with AI now, and millions of people are giving it a try. But when AI can spin up an app in minutes, are security risks slipping through the cracks?

For episode 742 of the BlockHash Podcast, host Brandon Zemp is joined by Chi Zhang, co-founder and CEO of Kite, which is building the base layer for the agentic internet. Her extensive background encompasses AI, big data, and product management.

This episode features Geoffrey Mattson, CEO of SecureAuth, joined by co-host Sarah Cicchetti, Director of Product Management at Semperis.Geoffrey has spent decades building and leading companies at the intersection of AI and cybersecurity, including MistNet.ai, an AI-native threat detection platform acquired by LogRhythm, and Xage Security, where he drove zero trust adoption across the U.S. military, global energy firms, and Fortune 500 enterprises. At SecureAuth, he leads a platform built around continuous, real-time identity authority across workforces, APIs, and AI agents.In this episode, Geoffrey argues that agents combine the speed of automation with the unpredictability of humans, making real-time per-action authorization the only viable control model. He discusses why “friendly fire” from well-meaning employees is the biggest threat vector right now, how MCP vendors are ignoring their own OAuth spec, and what a practical agent rollout with real guardrails actually looks like.This episode reframes authorization as the problem the identity industry has been deferring for years and can no longer avoid.Guest Bio Geoffrey Mattson is a serial entrepreneur and globally recognized cybersecurity and AI executive with decades of experience building market-defining companies and technologies that protect the world's most critical systems.He is currently CEO of SecureAuth, a leader in AI-driven identity and access management with its Continuous Authority, ensuring ongoing verification across workforces, customers, APIs, and AI agents. This is enabled through its Private Authority Platform, which puts authentication and authorization under your control through any deployment model (cloud, on prem, hybrid, air-gapped).Prior to SecureAuth, Mattson served as CEO of Xage Security, where he led the company in Zero Trust for critical environments from energy to agentic AI. Under his leadership, Xage achieved rapid adoption across the U.S. military, global energy firms, and Fortune 500 enterprises.Previously, Geoffrey Mattson was co-founder and CEO of MistNet.ai, an AI-native threat detection platform acquired by LogRhythm. He pioneered decentralized analytics and machine learning approaches for real-time cyber defense, and later served as SVP of Product at LogRhythm, driving global expansion and shaping the next generation of SIEM/SOAR solutions.Earlier, he held senior executive roles at Juniper Networks, overseeing a $2B product portfolio and leading major M&A efforts, and at Huawei Technologies as SVP and CTO for networking and data center platforms. His engineering leadership at Corona Networks, Caspian, and Bay Networks helped build foundational technologies in network and security architecture.Guest Quote “With agents, you have the power and the speed of an automated process with the unpredictability of a human. And in fact, we are seeing their behavior and their psychology makes them even perhaps less predictable than a human.”Time stamps 01:45 Meet Geoffrey Mattson: Serial Entrepreneur and Cybersecurity Executive 02:40 Why Identity Is Having a Moment 08:40 Defining Agent Identity 12:15 Behavioral Guardrails for Agents 14:37 Agent Identity Lifecycle 17:36 Just-in-Time vs. Standing Privilege 18:02 C-Suite Pressure and Friendly Fires 21:00 When Agents Live Off the Land 26:12 MCP, OAuth, and Token Pitfalls 28:04 Threat Models and Rollout Strategy 30:13 LLMs and Policy Authoring 31:23 Conclusion and Final ThoughtsSponsor The HIP Podcast is brought to you by Semperis, the leader in identity-driven cyber resilience for the hybrid enterprise. Trusted by the world's leading businesses, Semperis protects critical Active Directory and Entra ID environments from cyberattacks, ensuring rapid recovery and business continuity when every second counts. Visit semperis.com to learn more.LinksConnect with Geoffrey on LinkedInConnect with Sarah on LinkedInConnect with Sean on LinkedInDon't miss future episodesLearn more about Semperis

Recorded in partnership with LHV Bank on their booth at Money20/20 Europe in Amsterdam, this episode explores the technologies, regulatory shifts and business models reshaping financial services across the continent. Russell Goldsmith is joined by six industry leaders: 1/ Macs Dickinson, Director of Engineering, LHV Bank 2/ Paul Scholten, Chief Executive Officer, Buckaroo 3/ Eline Blomme, Chief Product and Marketing Officer, Acquired 4/ Scott Dawson, Director & CEO, DECTA UK 5/ Chris Corbett, Product Lead, Plaid 6/ Alexander de Ràfols, Head of Europe Product, Affirm Together, they share practical, real‑world insights from the rise of stablecoins and instant cross‑border payments to the impact of agentic AI, rebundling, and the next wave of open finance innovation. A fast‑moving, insight‑packed episode capturing the themes dominating Money20/20 Europe, from rewired infrastructure to the new competitive dynamics between banks, fintechs and platforms.

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

In this episode of Data Driven, we're diving into the rapidly evolving world of agentic AI—where autonomous AI agents collaborate, communicate, and occasionally collide. Our guest, Vlad Luzin, co-founder and CTO of Band, joins us to explore the technical challenges and real-world implications of building collaboration layers for agents that act like distributed, non-deterministic microservices. We'll unpack the myths and realities surrounding orchestration, governance, and security, and discuss how enterprises can operationalize these agent ecosystems safely. Tune in as we share lessons learned, amusing engineering mishaps, and get a glimpse of what the future holds as agents become everyday colleagues in the digital enterprise.LinksVlad's LinkedIn Profile -https://www.linkedin.com/in/luzin/Watch this episode on YouTube -https://youtu.be/MZztFagEX_EBand Website -https://www.band.ai/Band Docs -https://docs.band.ai/Time Stamps00:00 Explaining orchestration in tech03:42 Understanding models and harnesses09:38 Misconceptions about A2A communication10:41 Understanding multi-agent systems16:18 Observability for distributed systems18:54 Agent communication and collaboration24:28 Unauthorized agent interactions25:49 Remote agent collaboration ideas28:54 How foundational AI models communicate33:20 Agent communication protocols overview35:39 Discussing tech standards and AI velocity40:53 Learning to Work with AI Agents42:41 Using Band AI tools

In episode 666 of the New Media Show, hosted by 2017 Podcast Hall of Famer Rob Greenlee, Rob talks with Greg Wasserman, Head of Relationships at RSS.com and host of Podcast Network Insights, for a deep conversation about one of the biggest questions facing podcasting, video, creator media, and digital networks right now: Podcast networks were originally built for an audio-first industry, but audiences have already moved the definition of a podcast beyond audio. Today, a podcast can be a YouTube show, a Spotify video, an Apple video podcast, a livestream, a short clip, a newsletter, a community, or part of a larger creator-led media brand. Greg brings a unique perspective from his work at RSS.com and from interviewing the leaders behind podcast networks, collectives, production companies, and niche media groups on Podcast Network Insights. He explains that podcast networks are no longer one simple model. Some are media-sales businesses. Some are community-driven groups. Some operate more like production companies, collectives, or full creator networks. Rob and Greg explore how the network model is shifting as video, live streaming, AI, Apple Podcasts, HLS video, YouTube, Netflix, Spotify, FAST channels, private communities, and creator monetization reshape what podcasting can become. The conversation also asks whether independent podcasters should join networks, what creators need to understand before making that decision, and why the future may depend less on downloads alone and more on trust, audience relationships, collaboration, niche value, and direct monetization. 00:00 Welcome to New Media Show #666 00:32 Are podcast networks becoming creator networks? 01:00 How audiences have already redefined podcasting 02:00 Introducing Greg Wasserman from RSS.com 03:00 Why Greg created Podcast Network Insights 04:00 How different podcast networks define community 05:00 Monetization, growth, and the changing role of networks 06:00 Internal network community vs audience community 07:00 Private communities, subscriptions, and audience relationships 08:00 Nova Podcast Network and media-company network models 09:00 Cross-promotion and collaboration inside networks 10:00 Are creators returning to collaboration? 11:00 Podcast networks as media companies 13:00 Owned-and-operated shows vs independent rev-share shows 15:00 Why ad revenue is not the only network business model 16:00 Marketing Podcast Network and niche value 17:00 Jay Shetty, Netflix, and platform exclusivity 18:00 Is Netflix becoming a podcast network? 19:00 Collectives, media companies, and different network definitions 20:00 What is a podcast network today? 21:00 Production companies and network partnerships 23:00 How creators should decide whether to join a network 24:00 Understanding your “why” before joining a network 25:00 iHeart, ad inventory, and the volume-based network model 26:00 Why sponsor status can distract from real monetization 27:00 Does network branding still matter? 28:00 Pineapple Street, GZM, Disney, and network identity 30:00 MCNs, YouTube networks, and the return of multi-channel networks 31:00 Silicon Valley, new media networks, and digital-native media 34:00 Traditional media adopts podcasting, video, and companion content 35:00 Apple Podcasts HLS video as a future distribution channel 36:00 Why video attracts higher media dollars 37:00 Know, like, and trust as a creator value 38:00 Will Apple Podcasts HLS video matter? 39:00 Free platforms, hidden costs, and creator control 41:00 Future ad dashboards across Spotify, Apple, YouTube, and Twitch 42:00 Platform exclusivity, Jay Shetty, Joe Rogan, and audience loss 44:00 Creator hustle and why networks cannot do all the work 46:00 Subscription fatigue and fragmented media access 47:00 More than 20 ways creators can make money 48:00 Lean creator teams, production help, and content scale 49:00 How podcast networks are using AI 50:00 AI-generated voices, sleep content, and audience behavior 52:00 AI for ads, scripts, show notes, social, and workflows 53:00 AI podcast networks and automated show creation 54:00 Agentic workflows and creator production systems 56:00 AI-generated content, humanity, and audience trust 57:00 Algorithms, AI interfaces, and future discovery 58:00 Platform algorithm changes and creator risk 59:00 Human connection, live events, and AI video podcasts 01:00:00 Why human storytelling still matters 01:01:00 Could creators build AI clones of themselves? 01:02:00 Avatars, HeyGen, Gemini, and disclosure 01:03:00 Human-hosted content labels and AI transparency 01:04:00 Video-first creators and separate audio/video feeds 01:05:00 Why The New Media Show still uses separate audio and video feeds 01:06:00 Audio-first creators, social media, and growth challenges 01:07:00 Different networks play different games 01:08:00 The future of compelling audio experiences 01:09:00 Spatial audio, AI audio, and interactive media 01:10:00 Personalized audience experiences and liquid content 01:11:00 Can audiences be moved from YouTube to Netflix? 01:12:00 Bundling, subscriptions, and platform experiments 01:15:00 Algorithms vs human curation 01:16:00 Netflix, FAST channels, and new distribution models 01:17:00 The technology challenge behind FAST channels 01:23:00 Greg's Tesla and the future of in-car video podcast listening 01:24:00 RSS.com, Podcasting 2.0, and AI labeling standards 01:25:00 Closing thoughts and where podcasting is heading Guest and Host Links Guest: Greg Wasserman Head of Relationships at RSS.com and host of Podcast Network Insights RSS.com: https://rss.com Greg Wasserman at RSS.com: https://rss.com/blog/greg-wasserman/ Podcast Network Insights: https://rss.com/podcasts/podcast-network-insights/ Greg Wasserman on LinkedIn: https://www.linkedin.com/in/gregwasserman Host: Rob Greenlee New Media Show: https://newmediashow.com Rob Greenlee: https://robgreenlee.com Podcast Hall of Fame: https://podcasthall.com Rob Greenlee on LinkedIn: https://www.linkedin.com/in/robgreenlee Rob Greenlee Booking: https://calendly.com/robgreenlee About the Host/Author: Rob Greenlee is a 2017 Podcast Hall of Fame inductee and Chair, a global new-media leader who bridges podcasting's human roots and its AI-driven future. As founder of Trust Factor Lab and host of the “New Media Show” and “Spoken Human”, Rob helps creators start, grow, monetize, and future-proof their content. He's held leadership roles at Microsoft, Spreaker, Libsyn, StreamYard, and PodcastOne, and serves as Chairperson of the Podcast Hall of Fame. Learn more at RobGreenlee.com and join the Trust Factor Lab Creator/Podcast Services. Personal/AI Disclosure Note: I used AI tools to help organize and edit this episode and generate show notes. I have made hand edits; the views, clarifications, responsibility, and industry perspective are mine and my guest's. I have been working in podcasting and platform adoption for more than two decades, and this article reflects my own position.The post Are Podcast Networks becoming Creator Networks? | Greg Wasserman #666 first appeared on New Media Show.

Jennifer St Pierre is Senior Vice President of Developer Experience and Transformation at Dell Technologies, where she leads the strategy for how Dell's Infrastructure Solutions Group builds, operates, and evolves software.In this session from DX Annual, Jen argues that the biggest challenge in adopting agentic AI is not the technology itself, but the people transition behind it. Drawing on lessons from earlier shifts like Agile, DevOps, and cloud adoption, she explains why organizations that treat AI as a simple tooling rollout may get compliance, but not commitment.Jen outlines five leadership imperatives for navigating the transition: building a shared understanding of why change is happening, defining a clear future state, clarifying how roles will evolve, creating psychological safety for experimentation, and aligning metrics and organizational structures with new ways of working. Throughout the talk, she emphasizes that while AI may generate code, humans remain responsible for direction, judgment, and meaning.Where to find Jennifer St Pierre: • LinkedIn: https://www.linkedin.com/in/jennifer-st-pierre-4935a81In this episode, we cover:(00:00) Intro(00:13) Why every major technology shift is ultimately a people transition(05:00) AI-generated code and the evolving role of software engineers(07:43) The importance of developing a shared understanding(12:00) Defining a clear future state and how engineering roles will evolve(19:12) How psychological safety enables experimentation and honest feedback(22:41) Why metrics and organizational structure must evolve for the age of AI(25:40) Why leaders must drive AI transformation intentionallyReferenced:• Measuring developer productivity with the DX Core 4• Understand team effectiveness 

Jack Chambers-Ward hosts a solo episode to recap the biggest SEO news from May 2026, including Google IO, AI traffic reporting in GA4 and the May 2026 core update.Links to news storieshttps://blog.google/products-and-platforms/products/search/explore-web-generative-ai-search/https://www.linkedin.com/feed/update/urn:li:activity:7458539598885867520/https://developers.google.com/search/docs/fundamentals/ai-optimization-guidehttps://support.google.com/analytics/answer/9164320?hl=en#05132026https://blog.google/products-and-platforms/products/search/search-io-2026/https://blog.google/products-and-platforms/products/shopping/google-shopping-cart/https://status.search.google.com/incidents/wdAXJk6LRRihEjpzEeWEhttps://www.sistrix.com/blog/may-2026-core-update-visibility-analysis-and-data-updates/Time stamps00:00 Intro03:11 Subscriptions and Trusted News10:25 Reddit in Google Business Profiles14:12 Google's guide for AI search optimisation29:07 GA4 AI Assistant Tracking33:08 Google I/O recap33:57 Search Box Reimagined37:42 Agentic search and UI40:28 Personal Intelligence42:57 Google's Universal Cart45:17 May 2026 core update46:58 Wrap up

In this episode of The Business of Open Source, I spoke with Manik Surtani, one of the co-founders of the Agentic AI Foundation and the CTO at the foundation. This is part of the series I'm working on about open source and AI, which started last week with a conversation with Glauber Costa about how AI killed a bug bounty program. Manik talks about how the foundation came into existence, why it's important to have a foundation that's specific to agentic AI and what it means, in terms of everyday activities, to be the CTO of an open source foundation. Given how fast everything is moving in the AI space, and specifically around what open source actually means, how we define what is and is not open source, where we can get data and who is able to have data that is open enough to be considered open source. And if we want to mitigate the environmental impact of AI, is the solution really to insist on fewer cat videos? However, if you like this show and want more content about the intersection of open source, AI and bottom lines, you should consider sponsoring! Reach out if you're interested. 

Agentic AI is being misread as a series of separate battles - e.g. Snowflake vs. Databricks, copilots vs. agents, model makers vs. app vendors, etc. We think the real story is that the biggest opportunity in software is converging around who owns the new intelligent client and the AI back end that makes it useful. The new client is the agent-based system of engagement - Snowflake's CoWork & CoCo, Databricks Genie, Microsoft Copilot, Google Gemini Enterprise, ChatGPT/Codex, Claude/Cowork and others. But that client cannot deliver business outcomes without a new back end - what we call a System of Intelligence - that represents a model of the enterprise in terms of its business rules and tacit knowledge. You can't build one without the other. We frame this premise using Clay Christensen's integrated innovation and Jensen's extreme co-design as applied to enterprise software.That is why Snowflake is the focal point for this Breaking Analysis, but not the whole story. Snowflake is not just competing with Databricks anymore. It is now in the same strategic arena as Microsoft, Google, OpenAI, Anthropic, Salesforce, SAP, ServiceNow, Celonis and others - all trying to define where business users, builders and agents get work done, and where the enterprise context that powers that work gets built.

✅ New autonomous agents. ✅ Canva designs made for you. ✅ Codex upgrades to make your business move. If you had your head down in spreadsheets this week, you missed some MAJOR AI upgrades that are available now. We track what's hot and what's not and break it all down on Fridays with our Friday Features. Autonomous Copilot agents, new Codex tools, Github CoPilot app and 7 more AI updates you should be using — An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI Codex Role-Specific Plugins LaunchMicrosoft Build Conference AI Feature ReleasesChatGPT Memory and Business Account UpgradesMicrosoft Flash Image Model for PowerPointCanva Integrated with ChatGPT and CodexGitHub Copilot Standalone Desktop App PreviewMicrosoft Autopilot Always-On Work AgentsOpenAI Models Now Available on AWS BedrockCodex Sites: AI-Built Internal Web AppsTimestamps:00:00 OpenAI's big money moves03:47 Explaining role-specific plugins09:02 Microsoft's new image model release11:09 Microsoft's AI strategy and Canva update14:23 Canva integration with ChatGPT16:56 GitHub Copilot's new canvas feature20:46 AI token subscription changes24:42 AWS adds OpenAI models to Bedrock28:25 Introducing OpenAI's CodeX Sites Feature32:07 Launch of OpenAI's New Plug-in34:16 Overview of podcast structureKeywords: Autonomous copilot agents, Codex tools, GitHub Copilot app, OpenAI Codex, ChatGPT business accounts, OpenAI enterprise, Microsoft Build conference, Microsoft always-on agents, AWS AI updates, Canva plugin, ChatGPT memory upgrade, Windows Codex integration, Microsoft Flash model, Enterprise apps integration, Role-specific plugins, Sales data analytics, Product design AI, Creative production AI, Investment banking plugin, Public equity investing, Data analytics plugin, Workspace admins, App permissions, Role-aware work agent, Financial research automation, Microsoft image generation model, PowerPoint AI integration, OneDrive AI features, Visual design creation, Canva app for ChatGPT, Canva MCP server, Agentic context carry, Full screen design preview, GitHub Copilot desktop app, GitHub Copilot Canvas, Agent-native command center, Parallel agent work tree, Code app interface, Model options in GitHub, Token usage limits, Subscription token subsidizing, Anthropic token efficiency, Amazon Bedrock, GPT-4, GPT-4.5, Small language models, Token reckoning, Security governance, Inference engine, Code app sidebar, Codex Sites, Internal dashboards, Project trackers, Interactive web apps, Shareable AI apps, Enterprise data connectors, ChatGPT Canvas, Automated workflow, Workplace authentication, Creative briefs repository.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

Mazen and Robin welcome Gant Laborde of Infinite Red to discuss AI Triforce, a practical framework for AI-powered software teams. They explore agentic coding, governance, testing, code quality, and emerging engineering roles that help teams move faster with AI while maintaining scalability, reliability, and long-term maintainability.   Show Notes AI Triforce announcement   Connect With Us! Gant Laborde: @gantlaborde Robin Heinze: @robinheinze Mazen Chami: @mazenchami React Native Radio: @ReactNativeRdio   This episode is brought to you by Infinite Red! Infinite Red is a premier mobile app consultancy, especially focused on Expo and React Native, located fully remote in the US. We're a team of 30 with highly experienced mobile app developers and have been doing this for over a decade. We are also one of the first development teams to adopt agentic coding in a way that keeps high quality standards and aren't afraid to do things the old school way if we need to. If you're looking for mobile app or React Native or Expo expertise for your next project, hit us up at infinite.red/radio.

Plenty of companies have bolted AI onto how they already work and called it transformation. Far fewer have rebuilt the business around it. In this episode of The Trending Communicator, host Dan Nestle talks with Brian McHale, CEO and owner of Brandience, who bought a struggling traditional ad agency back in 2008 and spent the better part of two decades quietly rebuilding it around AI. His shop now runs eight AI agents for every human employee, cut prospect research from 45 minutes to under 10, and was among the first agencies in the country to earn AI ethics certification. And he did all of it from Cincinnati, not Silicon Valley—which might be exactly why it works. This isn't a story about swapping people for machines. Brian's approach is AI Forward, not AI First: humans stay at the center, and AI makes them better at what they already do. He and Dan get into the unglamorous reality of transformation that actually works—why ambiguity is the biggest source of AI mistakes, how guardrails free people to experiment rather than fence them in, why a leader's job has moved upstream in the content process, and what it means to know when to call a timeout. As Brian puts it, judgment only comes with experience. They also dig into agents and playbooks (and why a playbook is really just a workflow with an agent for each step), the internal bonus program that tied every employee to an AI project and delivered the best ROI Brandience has seen on anything, and the client conversations nobody saw coming—not "please use more AI," but "can I actually own this?" It's a grounded, refreshingly hype-free look at what rebuilding a business around AI looks like from the inside. Listen in and hear about... How "AI Forward, not AI First" keeps humans at the center of the work Why transparency and ethics certification became guardrails, not just signals The shift that moves a leader's role upstream in the content process Building playbooks out of single-step agents—and where to start Why experienced people know when to step in (and when to call a timeout) Notable Quotes from Brian McHale On keeping humans central: "Humans are at the center of everything we're doing still." "The first word that comes to mind for me is just transparency. Because using AI or not using AI either way is just fine." "If you don't know when to say when or when to call a timeout, which frankly really only comes with experience, then you're kind of crossing your fingers and hoping that the tool does what you want it to do." "My goal in life is not to have Brandiance be me sitting there with 50 agents. That sounds terrible." Resources and Links Dan Nestle Lilypath | Website The Trending Communicator | Website Communications Trends from Trending Communicators | Dan Nestle's Substack Dan Nestle | LinkedIn Brian McHale Brandience | Website Go Beyond | Podcast Brian McHale | LinkedIn Timestamps 0:00:00 Host's skepticism on "transformation" and intro to Brian McHale0:06:00 Brandiance's transformation: AI-forward, industry focus, balancing tech and people0:12:00 Navigating regulations, ethics, and AI adoption in healthcare and marketing0:18:00 Ethics in AI: transparency, authenticity, and employee guardrails0:24:00 Leadership responsibility: upstream involvement and AI policy guardrails0:30:00 AI operator training, evolving skills, and workplace adoption challenges0:36:00 Playbooks and agents: Brandiance's approach to AI workflows0:42:00 Agentic tools, Claude Cowork, and collaborative design system workflows0:48:00 Client expectations, ownership, and business implications of AI in agency work0:54:00 Governance challenges, AI engagement incentives, and employee-driven innovation1:00:00 Staffing, layoffs, overreaction to AI, and the value of experience in the AI era1:06:00 Closing remarks, where to find Brian McHale, show wrap-up (Notes co-created by Human Dan, Claude, and Castmagic) Learn more about your ad choices. Visit megaphone.fm/adchoices

Windows Central's Daniel Rubino breaks down predictions for Apple's (AAPL) WWDC 2026 announcement next week. He says people may not fully trust the new agentic AI upgrade tied to Apple Intelligence due to privacy and security concerns, but believes people will eventually be able to make the transition. Daniel discusses the risks and open questions Apple is facing.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

In today's Cloud Wars Minute, I discuss how Workday's Extend platform is helping developers build faster while maintaining governance and trust. Highlights 00:03 — Earlier this week, Workday held its DevCon conference in Las Vegas. It was the biggest DevCon that Workday has ever had. They had 8,000 attendees, and of course, these days, the star of the show was new agentic capabilities that, in this case, Workday is pumping into its Workday Extend platform. 00:53 — This Developer Agent is being added to a number of new capabilities within the Extend platform, and I listened to this whole roundtable discussion, and a number of things jumped out. I just want to share some of the reactions with you because they give a sense of what's going on here among developers in the early stages of the AI revolution. 01:58 — One person called it a real game-changer, this Developer Agent, and she said, "What used to take me days, I can now do in about one hour." Another person said that, with Workday ensuring that all the guardrails around security, trust, and governance are there, "I can build now without losing any sleep every night." 03:08 — This person said actually hiring for software engineers here in the AI era is way up. I think what came across in this roundtable that Workday held at DevCon was the optimism that these folks showed. We're not only surviving the changes brought by AI, we're going to have chances to do more than we ever have before. 04:12 — Here they see that now the work, the time, the effort, the energy, the brain muscle that they are putting into their work is going to result in better output, more impact on the business, more capability, because the technology through these agents is both taking care of lower-level work and ensuring governance, trust, and security are wired in. Check out this press release outlining the major introductions at DevCon. Visit Cloud Wars for more.

Brad Wetherall: AI Search, Agentic AI, and How Corporations Must Adapt to Digital Discovery In this episode of Scouting for Growth, Sabine VanderLinden is joined by Brad Wetherall, former Director of Operations at Google and current COO of Esquire Digital, to unpack the transformative impact of AI on search engines and digital visibility.  The conversation explores how search is moving beyond traditional search engine optimization (SEO) to an era where AI agents, neural networks, and zero-click searches are redefining how brands are discovered, trusted, and chosen online.  Brad Wetherall outlines the emergence of "agentic AI" and the rise of the "frontier firm," where human expertise and AI collaborate to generate both authority and visibility in this new digital ecosystem. This episode offers actionable strategies for corporations, regulated industries, and innovators aiming to future-proof their digital presence and leverage the next chapter of AI-led search.   KEY TAKEAWAYS The traditional SEO playbook is now outdated. The critical question is no longer “How do I rank number one on Google?” but “What does AI say about my company?”  AI-generated summaries and answer engines sit at the top of results, often preventing users from ever clicking on links. To succeed, businesses—especially in highly regulated industries—must ensure their information is not just human-readable but also machine-readable, authoritative, and genuinely original. Websites should be built with both humans and AI in mind, making content easily digestible for AI agents. Content creation has become an interplay of art and science: AI values unique human perspective, expertise, and experience—simply generating generic, regurgitated answers will not suffice and may even have negative consequences, as Google's recent algorithm updates penalize unoriginal, AI-generated spam. Building trust, authority, and relevance is now an ongoing process. It's essential to invest in structured content, active reputation management, robust Google Business profiles, and credible third-party validation through PR. AI agents are becoming the intermediaries of trust, filtering which brands and content make it into these AI overviews. Organizations must become agent bosses, orchestrating both human and machine intelligence, and focusing on verifiable outcomes, not just website traffic. The early adopters who build their authority and distinct voice now will lead in this new landscape and avoid the scramble of playing catch-up.   BEST MOMENTS "The question is no longer how do I rank, but rather, what does AI say about my company?" — Sabine VanderLinden "AI is fundamentally changing the rules of digital discovery. We're seeing a once-in-a-generation shift equivalent to the disruption caused by the Internet itself." — Brad Wetherall "There is no easy button. There's no shortcut. It's not just about buying backlinks anymore—AI search requires a different blueprint." — Brad Wetherall "AI wants to know who you are. The authoritativeness and trust in your company or as an individual now matter more than ever." — Brad Wetherall "Clicks were always a flawed metric. Now, what matters is how many customers you get—not just traffic but outcome." — Brad Wetherall "The companies that do this well—who invest in website optimization, unique content, reputation, and public relations—will win the race. It's hard work, but it's how you'll stand out in an AI-driven world." — Brad Wetherall   ABOUT THE GUEST Brad Wetherall is the Chief Operating Officer at Esquire Digital and the best-selling author of AI and the Future of Search. He spent over a decade at Google, leading operations and shaping products like Google Business Profile, Google Shopping, Google Wallet, and Google Domains—helping over 100 million businesses to be discovered online.  Now at Esquire Digital, Brad applies his deep expertise to help companies adapt to the ever-evolving landscape of AI-driven search and digital visibility. His work focuses on demystifying the complex world of AI search and equipping organizations with the tools and strategies they need to remain competitive and authoritative as the digital economy transforms.   ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

For episode 740 of the BlockHash Podcast, host Brandon Zemp is joined by Kenny Wood, CEO of Sleepagotchi, a next-generation AI health data platform that started with sleep and is rapidly expanding into the broader wellness economy.The company just closed a $6.5M raise backed by Sfermion, Inception, 6th Man, and 1kx and launched its first personalised AI Sleep Coach on 19 May. Before joining Sleepagotchi, Kenny was CTO at Moonlander, a next-generation game creation studio successfully acquired by Alpha 3D. His career began in AAA games, shipping chart-topping franchises including Transformers (#1 in the UK console charts), Formula 1, and World Rally Championship. A builder and technologist with rare breadth, spanning AAA studios, R&D labs, defence simulation, and applied AI, Kenny brings a perspective on behaviour change and AI-driven systems that most founders in the wellness space simply don't have. 

Chris Hall — the Ecom Cowboy, former All-American offensive lineman at UT Austin, and the guy who scaled Bruce Bolt to one of Shopify's fastest-growing stores as a team of one — is as entertaining as he is tactical. But underneath the hat and the accent is a marketer who has been thinking hard about what separates the people who survive this AI moment from the ones who don't. His take: the button-pushers are already gone. The marketers who build and manage agents — and who also make bold analog bets — are the ones who get more valuable every quarter.Inside the episode:Why the "team of one" marketer is actually more viable than ever — and the Claude-powered workflow Chris used to handle ads, email, SMS, reporting, and organic social simultaneously at Bruce BoltHow BattleBox turned Whatnot into their #2 revenue channel (surpassing Amazon) — with net-new customers, not cannibalized .com sales — and why most DTC brands are still completely asleep on itThe AI stack Chris is actually using: Claude for strategy and execution, Wideframe for agentic video editing, Kive for AI product imagery so clean that seven-figure brands are running it as their entire Instagram feedWhy "get sweaty on camera" is one of the highest-leverage moves a marketer can make right now — and the skill it builds that AI literally cannot replicateThe two anti-AI bets Chris thinks every brand and operator needs to make in 2026 — and why they work because of AI, not in spite of it—Sponsored by OMG Commerce - go to https://www.omgcommerce.com/contact and request your FREE strategy session today!—‍Chapters:[0:00] Welcome & Introducing the Ecom Cowboy[1:53] Origin of the Ecom Cowboy Brand & Name[2:17] Chris Hall's Football Career at UT & Blocking Von Miller[4:43] From the NFL to Nonprofits to E-Commerce[6:45] Inside Bruce Bolt: One of Shopify's Fastest Growing Stores[9:07] The Future of Marketing Jobs in an AI World[14:26] What Marketers Must Do to Stay Relevant in 2026[17:32] Getting Claude-Pilled: Building Your Agentic Workforce[21:44] Running an Entire Marketing Team with AI Agents[27:34] Chris Hall's Full AI Stack (Wideframe, Higgsfield & More)[31:36] AI Productivity Hacks: Daily Reports, WhisperFlow & Skills[36:40] The Anti-AI Bet: Live Streaming & IRL Activations[39:11] Why Every Brand Should Be on Whatnot Right Now[47:29] Wrapping Up & How to Find Chris Hall Daily—Connect With Brett: LinkedIn: https://www.linkedin.com/in/thebrettcurry/ YouTube: https://www.youtube.com/channel/UCQmbMwBW8LYDfFAqNqlgTGw Website: https://www.omgcommerce.com/ Request a Free Strategy Session: https://www.omgcommerce.com/contactRelevant Links: Chris' LinkedIn: /chrislukehallPast guests on eCommerce Evolution include Ezra Firestone, Steve Chou, Drew Sanocki, Jacques Spitzer, Jeremy Horowitz, Ryan Moran, Sean Frank, Andrew Youderian, Ryan McKenzie, Joseph Wilkins, Cody Wittick, Miki Agrawal, Justin Brooke, Nish Samantray, Kurt Elster, John Parkes, Chris Mercer, Rabah Rahil, Bear Handlon, JC Hite, Frederick Vallaeys, Preston Rutherford, Anthony Mink, Bill D'Allessandro, Stephane Colleu, Jeff Oxford, Bryan Porter and more

The CFTC reclassified perps as futures. Katherine and Jessi parse what the ruling actually permits and what it means for Hyperliquid. Plus: if your AI agent gets scammed, who pays? Thanks to our sponsor! Explore crypto careers that could change your future at https://crypto.fidelitycareers.com The CFTC approved a perpetual Bitcoin futures contract for KalshiEX, and crypto Twitter immediately got it wrong. Katherine Kirkpatrick Bos untangles what actually changed, why the switch from swap to futures classification matters for retail access, and what the ruling leaves wide open on leverage and decentralized exchanges. Jessi Brooks and Katherine explore the fact that AI agents can now place orders, not just give advice. They revisit their paper "The Agents at the Gate" and make clear why Robinhood's move to let agents charge your Gold Card raises liability questions that existing consumer protection law was never built to answer. In the strangest segment, they also dug into a New York lawsuit where an anonymous plaintiff is claiming legal ownership of nearly 40,000 dormant crypto wallets. Jessi explains why the lost-property theory will probably fail — and why even a partial win could force centralized exchanges into an impossible spot. Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Katherine Kirkpatrick Bos⁠⁠⁠⁠⁠⁠, General Counsel at StarkWare. Previously held senior legal roles across DeFi and centralized exchanges. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jessi Brooks⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, General Counsel at Ribbit Capital⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

No matter your role, experience or industry, we all (mostly) waste hours a week doing the same thing: manually creating slides. 

More tokens = more ROI, right?

A.M. Edition for June 1. Nvidia unveils a next generation lineup of laptops and desktops designed to run AI agents. Plus, SoftBank leapfrogs Toyota to become Japan's most valuable company on news it will invest more than $50 billion in data centers in France. And Colombia lurches right, as voters back a presidential candidate pledging a major drugs crackdown. WSJ South America bureau chief Juan Forero says a potential win by firebrand Abelardo de la Espriella in a runoff later this month could hand President Trump another close ally in Latin America. Luke Vargas hosts. Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices