Podcasts about agentic

Brian Peterson, Cofounder and CTO of Dialpad, joined Doug Green, Publisher of Technology Reseller News, for a podcast conversation ahead of the upcoming Enterprise Connect 2026 and HIMSS 2026 events to discuss how enterprises are moving beyond AI experimentation and beginning to deploy agentic AI at scale. Peterson explained that many organizations have spent the past year exploring AI pilots but are now facing the harder challenge of operationalizing those experiments in production environments. “The real question now isn't whether AI works—it's how you deploy it safely, measure its impact, and scale it across the organization,” he said. Dialpad's approach focuses on helping enterprises identify high-value use cases, build AI agents around those workflows, and validate outcomes before deployment. A key advantage for Dialpad is its access to large volumes of real conversational data from voice, messaging, and contact center interactions. By analyzing these interactions, the platform can identify friction points in customer experience and operational workflows. Those insights then guide the creation of AI agents designed to resolve specific tasks—such as assisting contact center agents, automating routine processes, or surfacing real-time insights during live conversations. Peterson also emphasized the importance of governance and measurement when deploying AI agents. Organizations must ensure that AI systems are transparent, measurable, and aligned with business objectives. By validating performance before production rollout, enterprises can reduce risk while demonstrating clear ROI—an important step in transitioning from experimental pilots to enterprise-wide adoption. As the industry prepares for major discussions at Enterprise Connect and HIMSS, Peterson believes the next phase of enterprise AI will be defined by practical deployment rather than experimentation. Organizations that can effectively turn conversational data into actionable AI workflows will be best positioned to unlock the real value of agentic AI. Visit https://www.dialpad.com/

“Transparency has to be built into the structure so that you know where the decision is made, what authorizations are given, and have an audit trail visible so you can always see what is going on.” –Ross Dawson About Ross Dawson Ross Dawson is a futurist, keynote speaker, strategy advisor, author, and host of Amplifying Cognition podcast. He is Chairman of the Advanced Human Technologies group of companies and Founder of Humans + AI startup Informivity. He has delivered keynote speeches and strategy workshops in 33 countries and is the bestselling author of 5 books, most recently Thriving on Overload. LinkedIn Profile: Ross Dawson What you will learn How human-AI teams outperform human-only teams in productivity and efficiency The crucial role of understanding AI strengths and limitations when designing collaborative workflows Ways AI collaboration can lead to output homogenization and strategies to preserve human creativity Key principles of intelligent delegation within multi-agent AI systems, including dynamic assessment and trust Understanding accountability, transparency, and auditability in decision-making with autonomous AI agents How user intent and ‘machine fluency’ impact the effectiveness of AI agents in economic and organizational contexts The emergence of an ‘agentic economy’ and its implications for fairness, capability gaps, and representation Counterintuitive findings on AI-mediated negotiation, particularly advantages for women, and what it reveals about AI-human interaction Episode Resources Transcript Ross Dawson: This episode is a little bit different. Instead of doing an interview with somebody remarkable, as usual, today I’m going to just share a bit of an update and then share insights from three recent research papers that dig into something which I think is exceptionally important, which is how humans work with AI agentic systems. And we’ll look at a few different layers of that, from how small humans plus agent teams work through to how we can delegate decisions to AI through to some of the broader implications. But first, a bit of an update. 2026 seems to be moving exceptionally fast. It’s a very interesting time to be alive, and I think it’s pretty even hard to see what the end of this year is going to look like. So for me, I am doing my client work as usual. So I’ve got keynotes around the world on usually various things related to AI, the future of AI, humans plus AI, and so on. A few industry-specific ones in financial services and so on. And also doing some work as an advisor on AI transformation programs, so helping organizations and their leaders to frame the pathways, drawing on my AI roadmap framework in how it is you look at the phases, mapping those out, working out the issues, and being able to guide and coach the leaders to do that effectively. But the rest of my time is focused on three ventures, and I’ll share some more about these later on. But these are fairly evidently tied to my core interests. Fractious is our AI for strategy app. So this was really building a way in which we can capture the detailed nuance of the strategic thinking of leaders of the organization, to disambiguate it, to clarify it, and enable that to then be built into strategic options, strategic hypotheses, and to be able to evolve effectively. So that’ll be in beta soon. Please reach out if you’re interested in being part of the beta program, and that’ll go to market. So that’s deeply involved in that. We also have our Thought Weaver software, rebuilding previous software which had already built on AI-augmented thinking workflows. So again, that’ll be going to beta. That’s more an individual tool that will be going into beta in the next weeks. So again, go to Thought Weaver. Actually, don’t—the website isn’t updated yet—but I’ll let you know when it’s out, or keep posted for updates on that. And also building an enterprise course on humans plus AI teaming. It’s my fundamental belief that we’ve kind of been through the phase of augmentation of individuals, and we still need to work hard at doing that better. But the next phase for organizations is to focus on teams. How do you work with teams where we have both human members and AI Agentic members? And it creates a whole different series of dynamics and new skills and capabilities. It really calls for how to participate in the humans plus AI team and how to lead humans plus AI teams. And that is again going into the first few test organizations in the next month or so. So again, just let me know. So today what we’re going to look at is this theme: teams of humans working with AI agents. So not individual AI as in chat, but where we have a lot of agents with various degrees of autonomy, but also agentic systems where these agents are interacting with each other as well as with humans. So there are three papers which I want to just talk about, just give you a quick overview, and please go and check out the papers in more detail if you’re interested. There’ll be links in the show notes. First is Collaborating with AI Agents: A Field Experiment on Teamwork, Productivity and Performance, by Harang Ju at Johns Hopkins and Sinan Aral at MIT. So this, there was an experiment which had over 2,300 participants who were working on creating advertisements. And they had a whole array of humans plus AI, human-human teams, human-AI teams, sort of quite small or just in duos and so on, working on being able to create those which were then assessed in terms of quality and how they worked. So a few particularly interesting findings from that. So individually, just having a human-AI team essentially enhanced performance significantly compared to just human-only teams. And so they were able to move faster and to complete more of their tasks, and the quality was strong. But there’s a phrase which is commonly used around the jagged frontier of capability of AI, and it was quite clear that there were some domains where AI does very well and others where it didn’t. And so this comes to the part where, in terms of the design of the tasks, the design of the human-AI systems, and also the understanding by the human users of what AI is good at or not, is fundamental in being able to do that. And so in some cases, if AI was used in some domains such as image quality, they actually decreased quality. So we need to understand where and how both to apply AI in this jagged frontier and design the systems around that. This changes the role of the humans, of course. Humans then tend to delegate more. And there’s one of the things which they tested for, which is how do you behave differently if you know your teammate is an AI as opposed to not knowing whether a human or AI. And it changes. So they become more task-oriented. They are less using the social cues to interact, and they are essentially becoming more efficient. But some of these social cues which are valuable in the human-human collaboration started to disappear. And this automation process meant that there was not, in the end, as much creative diversity. Now I’ve often pointed to the role of AI in creativity tasks. It depends fundamentally on the architecture—where does the AI sit in terms of initial ideas which are then sorted by filtered by humans and then are involved, or where it sits in that process. But in this particular structure, they found that humans plus AI teams started to create more and more similar-type outputs. So this homogenization of outputs in these human-AI teams was very notable and significant. And so this again creates a design factor for how it is that we build human-AI systems which actually do not lead to homogeneous output. And we’re making sure that we are ensuring that the human diversity is maintained. Often that can be done by being able to have human outputs first without AI then blunting or narrowing the breadth of the creative outputs of humans. Second paper I’d like to point to is called Intelligent AI Delegation, from a team at Google DeepMind. So this is this point where we now have not just single AI agents to delegate decisions to or problems to, but in fact systems of AI. And so this creates a different challenge. And the key point is, I’m saying this, is around you are delegating tasks, but when you are delegating tasks it’s more than just saying, okay, which agent gets the task. You have to understand responsibility. So where does accountability reside? Who is responsible for that? How clarity around the roles of the agents, what are the boundaries of what it is they can do and cannot do, the clarity of the intent, and how that’s communicated and cascaded through the agents, and the critical role of trust and appropriate degrees of trust in the systems. So this means that we have to define what are the different characteristics of the task. And in the paper it goes through quite a few different characteristics. And a few of the critical ones was the degree of uncertainty around the task. Obviously, if it is very clear that can be appropriately delegated, but many tasks and problems are uncertain. And so this creates a different dynamic. Whether verifiable, as you know you have high-quality information, or whether that’s the degree of uncertainty around whether decisions are reversible, the degree of subjectivity, because not everything is data-driven. And so assessing these task characteristics start to define where human judgment plays a role, how do you create those checks, and how do you build that. So this creates a system so intelligent delegation is not just how the humans delegate, but in turn the structure of how that cascades down through the agents. So this requires this idea of dynamic assessment. So you’re not just setting and forgetting. You are continuously reassessing what is happening with the context, what is changing in the stakes, any uncertainty. So you’re coming back to be able to ensure there’s not just a single delegation structure, but you’re changing it over time. And you’ll continue to adapt as you’re executing, and be able to monitor, replan, and set. So transparency has to be built into the structure so that you have where the decision is made, what authorizations are given, you know where the audit trail is visible so you can always see what is going on in those structures. And being able to scale how you are coordinating the systems. And if it’s just small scale that’s fine, but you want to be able to build something which has been able to move across many agents. And so this requires a way of being able to discover which agents are most appropriate and be able to essentially establish the delegation of a particular task to them again on a dynamic basis. And essentially this final principle of systemic resilience, where you have to expect that things will go wrong. So there’s continuing monitoring, being able to understand that these systems can be attacked in various ways and being able to recover. So, very solid paper, quite deep, but really giving some very good principles for how it is we can delegate to AI systems. So the final of the three papers goes to a bit of a higher level. It’s called Agentic Interactions, and it’s from Alex Imas, Sanjog Misra of the University of Chicago, and Kevin Lee at the University of Michigan. And what they’re looking at is what happens on a macro scale when increasingly decisions are delegated to AI agents. So this is the agent economy that I’ve been talking about for a very long time, which is now very much coming to the fore. And so what they do is they look at what happens when we start to delegate more and more economic decisions, such as buying and selling decisions. So what they found is extraordinarily interesting. They found that the AI agents in fact do behave very similarly to their human creators. And in fact what you can observe is that there are differences in the agents where you can infer the gender and the personality of the person who is delegating the agent. Even though there is no information, the agent doesn’t even know what the gender or the personality is, they are actually flowing through. So in fact agents represent us in the market as it were, potentially very accurately. But this goes directly to the second point where this idea of machine fluency. And so AI fluency is very much a term in vogue at the moment. So the authors talk about this idea of machine fluency which is how well can a user put their intent and align that with the agent so the agent is aligned with them. And in fact they found that there’s very significant degrees of difference in those. And those people who are better at being able to get their agents to express their wishes could in fact amplify the economic outcomes of these people. And related to that in fact they showed there was a correlation that higher educational levels mean that you were able to better delegate to AI, and your AI agents performed better and gave you better returns. So again pointing to these ways in which we’re starting to see potentials for aggravation of differences in the agentic economy when our agents who act for us in the economy start to reflect among other things educational differences or capabilities in how it is we express our results and our intentions through AI. There was one very interesting and I suppose counterintuitive result. Women get better outcomes in negotiation when using AI agents than they do in human-to-human interactions. Again this is without the AI agents knowing that they are representing a woman or not. But in fact this shows that the style and the way on the machine fluency the ways in which women are able to instruct and put their intent into the AI agents is in this study superior to those of males. And there’s of course in the real world unfortunately a bias towards male performance in negotiation. And that was inversed in the study. So exceptionally interesting. So just pulling back some of the common themes of these three papers. We increasingly want a world where humans have relationships to agents. We are starting to work with them in teams and systems. And we’re starting to build economies where humans are represented by agents. And essentially our relationship to those agents and our ability to delegate effectively is driving value of course to the individual but also across these agentic systems that are emerging. So this is early on because the realities of these agentic human-agent systems are pretty early at this point. But this starts to point to some of the potential, some of the challenges, some of the opportunities, and some of the work that we have to do. So I will be sharing more on these kinds of topics in my interviews with people and also of course on the Humans Plus AI website. So just go to humansplus.ai. Actually to be frank it hasn’t been updated a lot recently but we will be sharing a lot more there. Or LinkedIn is where I share the most actually, and getting back on Twitter as well if you’re interested. But I’ll be diving deep and trying to share what I find is useful as well as interesting in helping us to create a world where humans are first. AI complements us. The reality is we are moving to humans plus AI systems. And if we design that well with the right intentions we can make this absolutely one which drives human value first. So glad to have you on the journey. Have a wonderful rest of your day. The post Ross Dawson on Humans + AI Agentic Systems (AC Ep34) appeared first on Humans + AI.

Innovate or Cry – Episode #33Agentic Revolution: OpenClaw, autonome KI-Agenten und die Zukunft der ArbeitIn dieser Folge von Innovate or Cry diskutieren Manuel Kreutz und Dr. Babak Zeini die neuesten Entwicklungen rund um Agentic AI und autonome Systeme.Ausgangspunkt der Diskussion ist OpenClaw – ein Open-Source-Projekt, das zeigt, wie sich KI von einem reinen Chat-Interface hin zu autonomen Agenten entwickelt, die eigenständig handeln, Tools nutzen und komplexe Aufgaben ausführen können.Die beiden Hosts analysieren, welche technologischen Bausteine hinter solchen Systemen stehen – von persistenter Identität und Memory-Systemen bis hin zu Skill-Marktplätzen und autonomen Entscheidungsprozessen.Dabei geht es nicht nur um technologische Möglichkeiten, sondern auch um die entscheidenden Fragen für Unternehmen:Wie können autonome KI-Agenten produktiv eingesetzt werden?Welche Security- und Governance-Risiken entstehen durch autonome Systeme?Welche Rolle spielen Open Source Ökosysteme in der nächsten Phase der KI-Entwicklung?Und wie verändert Agentic AI langfristig Digital Business und Innovation?Ein zentrales Thema der Folge:Autonomie in KI-Systemen kann enorme Effizienzgewinne ermöglichen – verschiebt aber gleichzeitig die Komplexität in Richtung Strategie, Governance und Architektur.Zum Abschluss wagen Manuel Kreutz und Babak Zeini einen Blick in die Zukunft:Welche Szenarien sind für Agenten-Systeme realistisch – und stehen wir möglicherweise am Beginn einer Entwicklung, die langfristig in Richtung technologische Singularität führt?Key TopicsDie Agentic Revolution und warum 2026 als entscheidendes Jahr giltOpenClaw: Architektur, Fähigkeiten und Community-ÖkosystemUnterschiede zwischen Chatbots, Copilots und autonomen AgentenSicherheitsrisiken wie Prompt Injection und kompromittierbare SkillsGovernance und Kontrollmechanismen für autonome SystemeStrategische Implikationen für Unternehmen und digitale OrganisationenZukunftsszenarien für KI-Agenten und AI-ÖkosystemeChapters00:00 – Einführung und Überblick zur Agentic Revolution06:20 – OpenClaw: Architektur und Funktionsweise von KI-Agenten17:08 – Sicherheitsrisiken und Herausforderungen autonomer Systeme22:47 – Potenziale für Unternehmen und Business-Anwendungen28:54 – Technologische Entwicklungen und neue Architekturmodelle33:56 – Zukunft der Agentic AI und mögliche Markt-Szenarien41:50 – Technologische Singularität und langfristige AuswirkungenKeywordsAgentic AI, OpenClaw, KI-Agenten, Automatisierung, Innovation, Cybersecurity, AI Development, Open Source, Zukunftstechnologien, Digital Business Hosted on Acast. See acast.com/privacy for more information.

Everyone talks about AI agents. Very few talk about what they actually change inside enterprises. At the DataDriven Conference, Ravit Jain sat down with Rajeev Krishnan from PwC to unpack what the agentic shift really means for data, governance, and Master Data Management.PwC and Reltio have been working together for years, but the conversation is now moving beyond implementations to real business outcomes. Rajeev shared how their Agent OS ecosystem is being integrated with Reltio to deploy agents that handle tasks data teams have struggled with for years. Things like resolving match queues, auto-classifying records, and improving data quality without constant manual effort.What makes this important is simple. Enterprises already know they need trusted master data. The challenge has always been the operational burden required to maintain it. Agentic AI is starting to change that equation by reducing operational cost while strengthening the data foundation needed for AI-driven decisions.We also discussed what leaders are wrestling with in 2026. Two themes stood out.First, governance is no longer just about data. It is about governing data in the age of AI.Second, organizations are facing a real tension between using data to power AI and using AI to fix their data. The right path depends on the use case, not a one size fits all strategy.It was a grounded conversation about how enterprises are moving from AI experiments to operational impact.#data #ai #datadriven #reltio #theravitshow

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/

For episode 684 of the BlockHash Podcast, host Brandon Zemp is joined by Hoolie Tejwani, Head of Coinbase Ventures.Coinbase Ventures is the corporate venture capital arm of the major cryptocurrency exchange Coinbase, launched in 2018 to invest in early-stage crypto and Web3 startups. Its mission is to support "exceptional founders" building the foundation of an open financial system, aligning with Coinbase's overarching goal of increasing economic freedom in the world.  The firm has backed over 600 companies and operates with a highly collaborative approach, offering portfolio companies operational guidance, strategic partnerships, and access to the wider Coinbase ecosystem. 

Sumo Logic's VP of Security Strategy reveals how a ground-up agentic framework transformed their platform, and why clean data and autonomous agents are rewriting the rules of cloud security.Topics Include:Sumo Logic is a cloud analytics platform ingesting data from complex IT stacks.Built on AWS from the start, leveraging microservices for scalable solutions.Early AI efforts produced a natural language query co-pilot for security data.Bolting AI onto existing platforms proved brittle and one-dimensional.Customer feedback drove a decision to redesign AI from the ground up.The Dojo AI framework unifies purpose-built agents across the entire platform.New agents include a SOC analyst agent, knowledge agent, and MCP server.New frontier models on Bedrock give the whole platform an instant brain transplant.Autonomous agents require rethinking security controls beyond traditional programmatic guardrails.Federal and global customers demand rigorous, levelled-up security across all regions.Clean, normalized data proved the biggest unlock for reliable AI query results.Agent-to-agent communication and MCP will define the next era of AI platforms.Participants:Chas Clawson – Vice President, Security Strategy, Sumo LogicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this HFS Research videocast with Mindsprint, Ashish Chaturvedi speaks with Rohit Sharma and Unnikrishnan Sasikumar on how supply chains are moving from visibility to intelligence amid disruption—shifting from AI pilots to outcome-led transformation (working capital, margin, customer experience). They explore what's driving demand today including real-time planning, control towers, supplier collaboration, predictive analytics and what's next: agentic AI for exception handling and the path to autonomous supply chains, grounded in trustworthy data foundations and an ecosystem approach across SAP/Microsoft cores plus specialist startups. Key discussion points include:Enterprise demand today is still centered on “visibility + decision support.” Most current programs focus on real-time planning, control towers, supplier collaboration, and AI-driven dashboards/analytics to enable faster decisions during disruption. Clear shift from tactical work to integrated, tech-enabled operations. Buyers are moving away from manual Excel forecasting and siloed portals toward integrated solutions that support automated exception handling (including agentic AI), plus broader ecosystem collaboration and traceability.A widening “spend today vs build tomorrow” gap is shaping strategy. Enterprises are still investing heavily in analytics modernization, cloud, and data foundations, while major tech vendors are pushing hard on generative AI and agentic architectures—creating a sequencing challenge. Trustworthy data is the gating factor for autonomous supply chains. The conversation emphasizes that without strong data foundations (freshness, accuracy, governance, and resolving conflicting data sources), autonomy can create bad decisions (e.g., stock-out risk when systems think safety stock exists). Organizational capabilities matter as much as technology. Beyond platforms and tools, capability building and guardrails (e.g., CoE / governance frameworks) are positioned as essential to unlock value from data and AI.The partner stack is hybrid: ERP core plus startup innovation. SAP and Microsoft are described as dominant “core” stacks, while many enterprises augment them with specialist startups/scale-ups for niche planning, visibility, risk, and sustainability, requiring an ecosystem approach.Progress is real, but not linear. Enterprises are still getting foundations right, even as the tech investment trajectory points clearly toward more autonomous, AI-driven supply chain operations.Read the HFS Horizons Report on Intelligent Supply Chain Services 2025: https://www.hfsresearch.com/research/hfs-horizons-intelligent-supply-chain-services-2025

AI agents are only as good as the data and context behind them. At DataDriven 2026, I caught up with Sushant Rai from Reltio to talk about their latest announcements and where they see enterprise AI heading next. The big theme was clear. Context is everything. Without trusted enterprise data grounding AI systems, outcomes fall short. That is exactly where Reltio is placing its bets with its Context Intelligence Platform and the evolution of Agent Flow.We talked about how Agent Flow is moving beyond experimentation into real execution. From out-of-the-box agents for governance and operations, to a new Agent Builder that lets teams create agents with simple prompting, the focus is on making agentic AI practical for enterprises. Trust was another major point. Susant emphasized the need for observability, transparency, and explainability so organizations understand what agents are doing and why. Without that, adoption stalls. Looking ahead, Reltio is investing heavily in unstructured data processing, agent-driven data quality, expanded zero-copy integrations, and stronger identity resolution to unify enterprise data at scale.The direction is clear. Enterprises are shifting from dashboards to intelligent systems powered by context-rich data.#data #ai #datadriven #reltio #theravitshow

In this episode of What's Next, host Aki Anastasiou is joined by Justin Hume, Samsung South Africa's Vice President of Mobile Experience, to unpack the launch of the new Galaxy S26 range and what Samsung's latest AI upgrades mean for everyday users. They explore Samsung's on-device AI approach, the shift toward agentic AI assistants that work across apps, and the industry-first privacy display on the S26 Ultra designed to protect sensitive information in real time. Justin also highlights key camera improvements, Knox-powered security, South African availability and pre-order deals, and how the new Galaxy Buds 4 fit into a more intelligent, connected AI lifestyle.

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.

Monday has been hit harder than almost any other public SaaS company. With $1.3BN in ARR, the company is valued at just $3.8BN; a more than 60% fall since IPO. Today, Eran Zinman, Monday's CEO joins Harry Stebbings in the hotseat to walkthrough six of the biggest threats to Monday's business; what is real, what is not and what are the unknowns.  AGENDA: 05:47 Six Threats Monday Faces Today  07:04 Threat #1: Vibe Coding: Will Companies Vibe Code Everything 11:24 Threat #2: Will OpenAI and Anthropic Own the Application Layer  13:52 Threat #3: Will Agents Turn Monday and Salesforce into a Database 18:43 Why is Monday Adding 15% Headcount When Everyone is Cutting? 21:40 How Monday is Using AI to be More Efficient 27:49 What Happens to Seat Pricing? What Comes Next? 34:17 What No One Sees About Enterprise AI Adoption 37:13 How Google AI Overview Smashed 10% of our Customer Acquisition 38:49 If Bullish on Monday, Why Has Eran Not Bought More Stock… 40:38 How to Manage Internal Morale When Stock is Down 60% 44:08 Do Private Companies Have Advantages Public Companies Do Not Have 47:28 With $1.5BN in Cash, Why is Eran Not Buying More Companies… 53:30 What is the Most Offensive Bet Eran Would Like to Take? 57:13 Quickfire: Marriage, Biggest Short, Mentors  

The Trio kick off with the rumors about Apple's March 4th event and the possible return of a budget 12-inch MacBook on an A18 chip, which leads to a very poorly researched price analysis and a pitch for a MacBook sock accessory. Steve and Aaron talk about how agentic-assisted coding at work has been mentally exhausting and how they miss actually writing code. The conversation covers why LLMs are rough for greenfield projects, what "vibe coding" actually means (and why they're not doing it), the Alex Hillman episode follow-up, and Steve's experiment running different models against Bento Fit to produce slop PRs that Kotaro then spent an hour reviewing for some reason. Steve also crashes out about the state of the industry and public perception of AI. It's a lot.## Chapters- 00:00 Introductions- 01:51 Rumors and Speculations on New Macs- 10:43 The Impact of Pricing on Apple's Product Strategy- 11:53 The Developer Perspective on a New MacBook- 17:36 Comparing MacBooks and iPads in Today's Market- 18:36 The MacBook Sock- 21:12 Mac App Renaissance- 22:26 Follow-Up: Alex Hillman Episode- 25:12 Agentic Coding Flow States- 29:50 Balancing Traditional and AI-Assisted Development- 33:26 Navigating the Challenges of Greenfield Projects- 38:00 The Dilemma of AI in Coding- 41:48 Navigating Agentic Coding and Professional Ethics- 43:50 The Reality of Code Maintenance- 44:36 Public Perception of AI and Software- 47:41 Steve Crashes Out About the Industry- 51:24 Bento Fit Slop PRs- 58:37 Wrap-Up- 59:37 One More Thing...- 01:00:50 Tag## Show Notes- Apple "Experience" event March 4th, rumored budget MacBook with A18, ~12 inch, fun colors, maybe $699–$799- Updated Studio Display and touchscreen MacBooks also rumored- People buying $600 Mac Minis for OpenClaw setups- Mac app renaissance? More Mac apps being submitted, possibly thanks to LLMs making AppKit less painful- Alex Hillman episode follow-up: 219 views, 5 likes, watch hours up 46,639%- Agentic coding fatigue: Steve and Aaron are tired. No flow state. Just planning, reviewing, iterating.- Greenfield projects with LLMs produce average code. Better to write some bespoke code first and give the robot examples.- "We're not vibe coding." Steve proposes "agentic-assisted" as the term. The acronym is AA, which... maybe not great.- Code is a liability. 1,000 lines a day is not a good metric.- People outside the bubble mostly know ChatGPT, don't pay for it, and hate it- Steve ran three slop PRs on Bento Fit with different models as an experiment. Kotaro reviewed one for an hour anyway.- Bento Fit's $4.34 in tip revenue resulted in a $10 tax bill- OpenCode now has a $10/month plan for open source models## Links**Bento Fit**Website: https://bentofit.app**Tools & Services Mentioned**OpenClaw: https://openclaw.ai | OpenCode: https://opencode.ai | T3 Chat: https://t3.chat | Codex CLI: https://openai.com/codex | Claude Code: https://claude.com/product/claude-code**One More Thing**AppJawn LLC: https://appjawn.comApps: Clipdish, Mio Vino, Minimalist Meditation Timer**PhillyCocoa:** http://phillycocoa.orgIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.

Jack Chambers Ward hosts Search with Candour with guest Dena Warren, SEO Lead at Techquity, to discuss how e-commerce brands can prepare for AI search and LLMs.They cover how the importance of consistent product data across on-site content, feeds, and maximising structured data (product, FAQ, reviews).Dena highlights using user-generated content, avoiding duplicate manufacturer copy, and ensuring key content is visible in HTML rather than hidden behind JavaScript interactions, feed optimisation using OpenAI's product feed spec, and, of course, scepticism about LLMs.txt.Follow Dena:Techquity: https://www.techquity.co.uk/LinkedIn: https://www.linkedin.com/in/dena-warren-b44106139/Dena's recommendations:Ahrefs unlinked mentions: https://ahrefs.com/content-explorerAlsoAsked: https://alsoasked.com/Kelewele recipe: https://www.africanbites.com/kelewele-or-alocospicy-fried-plantains/Resources:https://developers.openai.com/commercehttps://productfeed.cloud/Time stamps00:00 Introduction01:39 Meet Dena Warren02:39 Why Clients Ask Now04:38 Avoiding AI Snake Oil06:52 Product Data And Schema10:18 Personalised Comparison Prompts12:13 2026 Ecommerce Essentials15:56 JavaScript And Crawlability17:33 Cloudflare Bots Panic20:54 Feed Specs For AI24:10 Agentic Commerce Readiness26:44 No Separate AI Subsites30:59 Multimodal Images And Video34:06 Shopping In Context35:08 3D And Video Demos36:05 Machine Readable Packaging37:29 SEO Shiny Object Traps38:02 llms.txt Scepticism42:22 Agentic Commerce Reality46:16 Agent Ready Checkout49:43 Small Brands Can Win53:52 Recommendations58:27 Episode Wrap up

In this HFS interview, Genpact's Yasir Andrabi and Macdonald Okolie discuss why AI has so far fallen short of expectations in insurance—and what needs to change. The conversation explores how agentic AI, data-driven underwriting, dynamic risk prioritization, and the Genpact Insurance Policy Suite are helping insurers move beyond basic workflow automation to fundamentally rethink underwriting judgment, capacity management, and underwriting economics. In the discussion, Yasir Andrabi, Agentic AI Leader for Insurance, and Macdonald Okolie, Global Head of Insurance Underwriting Practice at Genpact, outline a clear reason insurance AI hasn't moved the needle: most insurers have digitized underwriting workflows without addressing deeper issues around data quality and decision-making. Reviewing the Genpact Insurance Policy Suite, the conversation focuses on shifting underwriting from speed to judgment—using agentic, data-driven prioritization to direct limited underwriting capacity toward the risks that matter most, based on profitability, risk-adjusted returns, and likelihood of binding. By embedding third-party and exposure data while maintaining clear human-in-the-loop controls for accountability and regulatory compliance, Yasir and Don frame underwriting AI not as another layer of automation, but as a structural lever for changing the economics of underwriting.

The word is spreading through the education community that a new kind of artificial intelligence enables students to complete an entire course with a single prompt. As one educator explained, with just a simple setup, a student can put an entire course on autopilot and go back to playing video games. It's called Agentic AI, and it has sparked a new round of handwringing and calls to go back to blue books and pencils. To kick off 2026, the creators of SAMR, TPACK, Triple E, SETI, and the Gen AI U frameworks met to unravel how this technology may impact teaching, learning, and the future of proving that a student's degree or credential actually indicates competence. The big takeaway is that the solutions start with asking the right questions. Follow on X: @CFKurban @hcrompton @lkolb @punyamishra @jonHarper70bd @bamradionetwork Related Resources: The AI Tech Fatigue of 2025 Was Real: How Educators Are Planning to Regain Control in 2026 | AI Agents: A New Era in Higher Education | Cheating Lessons: Learning from Academic Dishonesty | SAMR | The SETI Framework | TPACK | Triple-E | The GenAI-U Framework BRN-X: Gen AI Podcast Lab Dr. Punya Mishra (punyamishra.com) is the Associate Dean of Scholarship and Innovation at the Mary Lou Fulton Teachers College at Arizona State University. He has an undergraduate degree in Electrical Engineering, two Master's degrees in Visual Communication and Mass Communications, and a Ph.D. in Educational psychology. He co-developed the TPACK framework, described as “the most significant advancement in technology integration in the past 25 years.” Dr. Caroline Fell Kurban is the advisor to the Rector at MEF University. She was the founding Director of the Center of Research and Best Practices for Learning and Teaching (CELT) at MEF University and teaches in the Faculty of Education. She holds a BSc in Geology, an MSc in TESOL, an MA in Technology and Learning Design, and a PhD in Applied Linguistics. Fell Kurban is currently the head of the Global Terminology Project and the creator of the GenAI-U technology integration framework. Dr. Liz Kolb is a clinical professor at the University of Michigan and the author of several books, including Cell Phones in the Classroom and Help Your Child Learn with Cell Phones and Web 2.0. Kolb has been a featured and keynote speaker at conferences throughout the U.S. and Canada. She created the Triple E Framework for effective teaching with digital technologies and blogs at cellphonesinlearning.com. Dr. Puentedura is the Founder and President of Hippasus, a consulting practice focusing on transformative applications of information technologies to education. He has implemented these approaches for over thirty years at various K-20 institutions and health and arts organizations. He is the creator of the SAMR model for selecting, using, and evaluating technology in education and has guided multiple projects worldwide. Dr. Helen Crompton is the Executive Director of the Research Institute for Digital Innovation in Learning at ODUGlobal and Professor of Instructional Technology at Old Dominion University. Dr. Crompton earned her Ph.D. in educational technology and mathematics education from the University of North Carolina at Chapel ill. Dr. Crompton is recognized for her outstanding contributions and is on Stanford's esteemed list of the world's Top 2% of Scientists. She is the creator of the SETI framework. She frequently serves as a consultant for various governments and bilateral and multilateral organizations, such as the United Nations and the World Bank, on driving meaningful change in educational technology.

Apple Treats discusses latest news and dives deeper into agentic coding future. Another in-person episode – a good tradition. Podcast hosts: - Danis Tazetdinov: associate principal software engineer at EPAM Systems, https://twitter.com/edeniska, https://mastodon.social/@Deniska - Vladimir Burdukov: lead software engineer at EPAM Systems, https://twitter.com/chippcheg, https://mastodon.social/@chippcheg Daily source of mobile news: https://appletreats.substack.com Don't forget to subscribe: https://linktr.ee/AppleTreats Watch this episode: https://www.youtube.com/watch?v=h9DHc8B2RI0

In this episode, host Friederike Ernst is joined by John Paller, founder of ETH Denver, to reflect on nine seasons of North America's largest Ethereum gathering and where the ecosystem goes next. John shares his "red pill" moment in 2016 and the subsequent realization that Ethereum was not just a corporate efficiency tool, but a way to rewire the global economic system. He discusses the evolution of the Biddle meme and how ETH Denver has become a market-driven aggregator for crypto's shifting narratives, from DeFi summer to the current era of institutional adoption.They delve into a candid critique of the Ethereum Foundation's "Infinite Garden" philosophy, with John arguing for more "structural vision" and actionable roadmaps to compete with the aggressive narratives of chains like Solana. The conversation highlights Agentic AI as the ultimate "Trojan Horse" for mass adoption, enabling a future where users interact with sovereign bots rather than complex private keys. Finally, John explains his Regulation Membership proposal to the US Congress, aiming to provide a federal securities exemption for on-chain cooperatives and restore true economic agency to the "little man." Topics00:00 Intro & Context04:15 Recruitment Tech to Ethereum: John's Genesis Story09:30 Inventing the "Biddle" Meme at Denver 201815:00 Is Ethereum a "Neo Casino" or a Settlement Layer?21:45 Critiquing Idealism: The Infinite Garden vs. Reality27:10 Why Solana is Not "Sufficiently Decentralized35:20 Agentic AI: The End of signing Transactions manually42:15 The Roman Catholic Church & Institutional Co-opting49:00 German Cooperative Culture & On-Chain Credit Unions 55:30 Regulation Membership & The SEC Challenge59:45 Zero Knowledge Identity & Privacy RightsLinksJohn Paller on X: https://x.com/PallerJohnETH Denver: https://www.ethdenver.com/Opolis: https://opolis.co/Lido: https://lido.fi/stvaults?mtm_campaign=epicenterNEAR: https://near.ai/ Sponsors: 1. Lido V3 introduces stVaults: modular staking infrastructure that lets builders and institutions deploy custom staking vaults, while staying anchored to stETH as a shared liquidity layer. Get started building with Lido V3 today: https://lido.fi/stvaults?mtm_campaign=epicenter2. NEAR AI Cloud now lets developers deploy OpenClaw—the rapidly growing open-source AI agent platform—inside Trusted Execution Environments, providing hardware-level encryption with cryptographic attestations. With OpenClaw on NEAR AI Cloud, you can run agents with cloud convenience, but without traditional cloud data exposure. No hardware to manage. No trust assumptions required. Learn more at near.ai.

Our guest on this week's episode is Per Hong, senior partner and global lead of Kearney Foresight. By now we have all heard that the emergency tariffs placed earlier in the year were ruled illegal last week by the Supreme Court, but now we have new tariffs – and the potential of war with Iran. There is lots going on right now that could have major impacts on our supply chains. Our guest helps us to unravel it all and offers advice on how supply chain leaders should prepare for whatever is next.Have you ever heard of a pandemic echo?  Apparently that is what is happening right now within the parcel delivery fleet sector. Ben Ames helps us to understand what it means and why it is affecting parcel. More than half (55%) of supply chain leaders expect that advancements in agentic AI systems will reduce the need to hire for entry-level positions, and 51% say the technology will drive a shift to overall workforce reductions. That's according to a survey from business and technology insights company Gartner, released this week. We look at the numbers from this report and what they may mean for hiring in supply chain jobs going forward.Supply Chain Xchange  also offers a podcast series called Supply Chain in the Fast Lane.  It is co-produced with the Council of Supply Chain Management Professionals. The latest series is now available on Top Threats to our Supply Chains. It covers topics including Geopolitical Risks, Economic Instability, Cybersecurity Risks, Threats to energy and electric grids; Supplier Risks, and Transportation Disruptions  Go to your favorite podcast platform to subscribe and to listen to past and future episodes. The podcast is also available at www.thescxchange.com.Articles and resources mentioned in this episode:KearneyFleets adjust focus from efficiency to resilience, Geotab saysReport: Agentic AI to reduce entry-level hiring needsVisit DC VelocityVisit Supply Chain XchangeListen to CSCMP and Supply Chain Xchange's Supply Chain in the Fast Lane podcastSend feedback about this podcast to podcast@agilebme.comThis podcast episode is sponsored by: WernerOther linksAbout DC VELOCITYSubscribe to DC VELOCITYSign up for our FREE newslettersAdvertise with DC VELOCITY

Eric Seufert (Mobile Dev Memo) joins Ari Paparo and Eric Franchi for a wide-ranging conversation on the future of apps, AI agents, walled gardens, and the shifting power dynamics in digital advertising. They dive into the so-called “SaaS-pocalypse” and discuss whether AI agents could replace apps entirely. They also discuss Apple's emerging AI gatekeeping strategy (and what it means for developers), Meta's acquisition of Manus and the automation of advertising, and AppLovin's reported ambitions to build a social network from scratch. Along the way, they explore whether independent ad tech can survive in a world dominated by Meta and Google, how AI is reshaping landing pages and commerce journeys, and why fully autonomous “agentic commerce” may be more mirage than inevitability. Takeaways AI agents may change how people use apps, but apps will not disappear.  Owning the user surface area matters because it protects monetization and customer relationships.  Agentic commerce sounds compelling, but platform incentives make full disintermediation unlikely.  Apple is tightening rules around sending personal data to third-party AI services, and enforcement is increasing through app rejections.  Apple keeps definitions vague to preserve latitude, which can create uncertainty for developers.  Apple may use Private Cloud Compute partnerships to control AI distribution and take a share of revenue.  Running meaningful AI inference on a device is limited by memory, so cloud processing remains central.  Meta's Manus acquisition reinforces the push toward end-to-end campaign automation in Ads Manager.  The next step is AI that improves the post-click journey, not just the ad setup.  Meta's business AI vision could move optimization from landing pages into conversational purchase guidance.  Some startups should look beyond Meta's core strengths and build in channels that Meta is less focused on.  Building a new social network requires massive spending, but AppLovin has the cash flow and distribution to attempt it. Chapters 00:00 Intro & Eric Seufert Returns 02:26 Marketecture Live Announcements 06:11 The SaaS-pocalypse 10:14 Why Apps Won't Die 11:54 Why Super Apps Failed in the West 13:27 Private Markets & AI Valuations 14:10 Apple's AI Tracking Transparency 17:08 Apple's Gatekeeping Strategy 21:15 App Store Delays & Vibe Coding 22:24 Meta's Manus Acquisition 24:12 Meta's Business AI Vision 29:44 Can Anyone Compete With Meta? 30:45 AppLovin's Social Network Ambitions 36:04 Infillion Acquires Catalina 41:26 The Trade Desk Earnings Breakdown 46:23 Executive Turnover & Competitive Landscape 50:38 Profound's $1B Valuation 54:14 AdSense for AI & LLM Monetization 58:00 Walmart Connect Growth Learn more about your ad choices. Visit megaphone.fm/adchoices

Nicole Nitsche spricht mit Mirko Krauel von Otto Payments über KI-Agenten, Verantwortung und Payment als strategische Orchestrierungsschicht

Explore how AI could reshape crypto and finance, redefining traditional systems and introducing new threats. As AI-powered agents promise efficiency, Haseeb, Tom, Tarun, and guest Illia Polosukhin critique Citrini's controversial predictions on a global financial crisis and consider whether AI might just save or further complicate crypto's role in the economy. 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. Joining us is Illia Polosukhin, co-founder of NEAR Protocol and contributing author to the original transformers paper that's revolutionized AI. Buckle up as we delve into AI's burgeoning role in the crypto world, dissect the sensational claims from Citrini's article predicting an AI-triggered financial crisis, and explore the potential of agentic coding in reshaping traditional systems. Let's get into it! Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Hosts ⭐️Haseeb Qureshi, Managing Partner at Dragonfly ⭐️Tarun Chitra, Managing Partner at Robot Ventures ⭐️Tom Schmidt, General Partner at Dragonfly  Guest⭐️ Illia Polosukhin, Co-founder of NEAR Protocol Disclosures THE 2028 GLOBAL INTELLIGENCE CRISIS by Citrini and Alap Shah https://www.citriniresearch.com/p/2028gic Timestamps 00:00 Intro 01:06 AI Agents Meet Crypto 08:06 Dark Forest Threat Model 15:31 How Close Are We 18:41 AI Coding Risks in Crypto 27:27 Citrini 2028 Crisis Explained 35:01 Demand Shock Missing Money 37:55 Automation Limits and Human Value 44:13 AI Zero Days and Botnets 51:40 Escrow Courts and Enforcement 56:05 Illia on Vibe Coding Future Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of FYI, Brett Winton and Nick Grous sit down with Leif Abraham, co-founder and co-CEO of Public. They examine how the brokerage landscape is shifting as digital-native investors seek more sophisticated tools, and why Public is focused on the top quartile of earners positioned to compound wealth. Leif discusses agentic AI workflows, generated assets, platform design trade-offs, prediction markets, and how Public is balancing short-term monetization with long-term customer lifetime value.Key Points From This Episode: 00:00:00 Public's positioning in the modern brokerage landscape00:07:17 The K-shaped economy and focusing on the top quartile00:09:04 Building a “serious” financial service centered on trust00:10:06 Product depth vs. simplification in brokerage design00:11:00 Generated Assets: prompting AI-built custom portfolios00:13:21 Digital natives as hybrid self-directed investors00:15:04 How AI is transforming internal product development00:19:55 Launching agentic workflows for money movement and trading00:23:38 Compressing the distance from idea to execution00:27:34 Guardrails, approvals, and trust in AI-driven execution00:30:26 Short-term trading revenue vs. long-term lifetime value00:33:32 Agents as retention and lock-in strategy00:35:05 Replacing financial advisors: automation, advice, and emotion00:37:54 Tokenization and private asset access00:40:40 Prediction markets and avoiding sports betting00:45:55 Building the last investing account customers ever openEditing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)

This week, the team dives into the feud that has been brewing between Anthropic and the Pentagon — and what it says about how the government interacts with tech companies. Later, Zoë tells us why figuring out whether you are agentic or mimetic has become the new litmus test in Silicon Valley. Plus, we discuss the key takeaways from the State of the Union address and give a farewell to the TAT-8 undersea cables — the ones that made our modern internet possible.  Learn about your ad choices: dovetail.prx.org/ad-choices

In this episode of One Vision — FinTech Fuse podcast, Theodora Lau and Jas Randhawa discuss the Universal Commerce Protocol (UCP) and implications for agentic commerce. They explore the challenges of chargebacks, the need for regulatory clarity, and the importance of consumer independence in the evolving landscape of e-commerce. While adoption is likely to grow, major risks include consumer manipulation, monopolistic outcomes, and the amount of personal data agents may require (buying, browsing, health, and other patterns), increasing privacy and security concerns. Now is the time to engage with policymakers and advocate for regulatory clarity and for the well-being of consumers. 00:00 Welcome Back to One Vision + Introducing Jas Randhawa (StrategyBRIX)01:10 What Is the Universal Commerce Protocol (UCP)? The Big Picture03:27 How UCP Works: Product Cataloging for AI Shopping Agents07:05 KYA (Know Your Agent): Identity, Authorization & Trust08:58 Chargebacks in Agentic Commerce: Who's Liable When Things Go Wrong?12:02 Fraud Detection Breaks: Geolocation, New Signals & Re-Engineering Controls13:44 Agent Independence & Consumer Protection: Bias, Collusion, and Oversight Gaps21:28 Regulatory Clarity (or Lack Thereof): The ‘Wild West' Phase + T&Cs Reality28:06 Time to Get Ready: Travel Use Cases, Audit Trails, and Dispute Proof33:26 Sanctions, VPNs, and High-Velocity Agent Behavior: Financial Crime Risks37:12 Are We Too Early? Will Consumers Adopt—and at What Cost?42:59 Privacy, Data Control & The Need for Neutral Standards Bodies (Wrap-Up)47:45 Final Thoughts#AI #AgenticCommerce #UCP #Agents #Fintech Hot take:  ”The amount of information this agent now needs to have about me is shocking and it scares me a little bit because you're talking about buying patterns, browsing patterns, sleeping patterns, health pattern. For this agent to be really effective, it just needs to know everything that's in my head, right? It's gonna be very effective, but that's again, a major risk because no one's watching out for the consumer.”Hot take: “ The future of this world is unfortunately not you or me. It's a lot of these younger kids, their ecosystem is a lot different. These products are being designed for them."More about our guest 

Transferable lessons - how overlooking fundamental security and data trust leads to Generative and Agentic AI failuresSteps for embedding security checkpoints and governance directly into your AI pipelineStrategies to scale AI safely - avoiding costly retrofits - and positioning security as a key competitive advantageThom Langford, Host, teissTalkhttps://www.linkedin.com/in/thomlangford/Tim Roberts, Managing Director, AlixPartnershttps://www.linkedin.com/in/thrrobertsSatyam Rastogi, Director of Information Security & DevOps, BAMKOhttps://www.linkedin.com/in/hackersatyamrastogi/Deryck Mitchelson, Head of Global CISO Team & C-Suite Advisor, Check Pointhttps://www.linkedin.com/in/deryckmitchelson

Omni Talk Retail is live from eTail West 2026 with continued coverage powered by NetElixir. In this interview, recorded on site at eTail West, Anne Mezzenga speaks with Alex Seaman, Senior Vice President of Furniture.com, about the company's recent relaunch and its vision for the future of furniture shopping. Furniture.com is building a unified, AI driven platform designed to simplify one of retail's most complex and considered purchases. By partnering with trusted national furniture retailers, the platform enables shoppers to browse, compare, and check out across multiple merchants in one seamless experience, while retailers retain ownership of fulfillment and first party customer relationships. Alex explains how Furniture.com is leveraging standardized product data, conversational search, and its in house AI agent Dottie to reduce decision fatigue and bring joy back to home design. The conversation also explores why brand trust and strong retail partnerships will matter even more as AI powered discovery reshapes how consumers shop. Key Topics Covered: • The recent Furniture.com relaunch and AI powered foundation • Agentic checkout and multi merchant cart functionality • Standardizing and enriching product data across 75 plus retailers • Why trust and brand strength matter in an AI driven search landscape • Balancing B2B retailer partnerships with a shopper first experience • Solving decision fatigue in high consideration purchases like furniture Stay tuned for more interviews from eTail West 2026. #eTailWest #RetailInnovation #Ecommerce #AIinRetail #FurnitureRetail #OmniChannel #DigitalCommerce #RetailLeadership

A "reckoning" in software stocks has very real fears of agentic AI upending businesses, says Hatem Dhiab. He labels Intuit (INTU) as one example. Hatem considers Salesforce (CRM) a more nuanced story, expecting some parts of the business to see little to no effect. He then turns to the Mag 7 by explaining watch in Nvidia (NVDA) earnings and concerns on Tesla's (TSLA) AI-centric future. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

Two weeks ago on Reimagining Cyber, we explored how agentic AI could become the next major security choke point. Since then, things have escalated.Enterprises are restricting — even banning — AI agents. Security teams are scrambling to regain visibility. Vendors are rushing out “agent security” features. And early warning signs are already surfacing.In this episode, Tyler Moffitt answers the critical question: Did agentic AI just move from innovation to crisis?What changed in just a matter of weeks?This discussion breaks down:Why AI agents are fundamentally different from traditional automation and service accountsHow autonomous reasoning + persistent system access creates a new attack paradigmThe identity and API sprawl problem most organizations didn't realize they hadWhy compromised agents could give attackers automation at scaleThe growing wave of enterprise bans — and what they signalWhether regulation or a high-profile incident is likely to come firstTyler explains how agents don't just generate responses — they take action. They hold API keys, access internal systems, modify code repositories, interact with cloud infrastructure, and execute workflows. When deployed without guardrails, logging, or least-privilege controls, they can quietly multiply an organization's attack surface overnight.The core issue isn't that AI is malicious — it's that AI has become an acceleration layer. And when autonomy meets overprivileged access, traditional security models break.You'll also hear practical, immediate steps security teams should be taking now — from credential rotation and agent inventories to sandboxing and behavioral monitoring.This isn't an anti-AI episode. It's a maturity wake-up call.Because the organizations that build guardrails now will move faster and safer. The ones that don't may learn the hard way.If you're a CISO, security architect, developer experimenting with agents in production, or executive evaluating AI adoption — this is a conversation you can't afford to miss.As featured on Million Podcasts' Best 100 Cybersecurity Podcasts Top 50 Chief Information Security Officer CISO Podcasts Top 70 Security Hacking Podcasts This list is the most comprehensive ranking of Cyber Security Podcasts online and we are honoured to feature amongst the best! Follow or subscribe to the show on your preferred podcast platform.Share the show with others in the cybersecurity world.Get in touch via reimaginingcyber@gmail.com

Your renewal engine isn't getting smarter. It's getting more automated.I just pulled an Insights by Blueprint report, and the section on rules grabbed me by the collar. Insights by Blueprint positions itself as operator-informed research built to help real estate leaders make faster, smarter tech and ops decisions.Here's the point.Agentic AI in multifamily is shifting renewals from “staff workflow” to “system workflow.”What is agentic AI in the renewal process?It's software that can take actions.Not just answer questions.It can coordinate pricing logic, schedule outreach, and offer self-service paths without an onsite teammate touching every step.That matters because renewals are a retention engine.Retention protects occupancy.Occupancy protects NOI.And the onsite team is already overloaded.But the real disruption is not agent-to-human.It's agent-to-agent.Today, the enterprise agent gets sharper every month.It learns from resident behavior.It refines offers based on what works.It shows up with a “best and final” renewal number that feels inevitable.Tomorrow, the resident has a proxy too.Digital Mike.A personal agent that can shop comps, weigh concessions, read policies, and counteroffer based on my rules.Now you have negotiation at machine speed.Enterprise agent versus resident agent.Not emotional.Not awkward.Not time-consuming.That's the moment operators need to prepare for.Because your rules become your reputation.If your retention system is optimizing toward short-term rent at the expense of fairness, it will get exposed faster.If your comps logic is sloppy, the resident agent will find it.If your exceptions process is unclear, your team will be forced to “manual” their way through a machine-native world.So what should operators lock down now?Governance.Audit trails.Clear boundaries on what the system can offer.Clear boundaries on what it cannot.And if you want the report, there's a path.Blueprint's Martin Kelly has been publicly tied to the Insights by Blueprint launch and positioning.Start there. Follow the trail. Get the PDF.Read the rules section twice. Then ask one question: If a resident's agent negotiates against your renewal agent tomorrow, do you like the outcome it will produce?MultifamilyCollective Blog: https://www.multifamilycollective.comThe Daily Collective Book: https://amzn.to/3YI6BDaHosted by: https://www.multifamilymedianetwork.com

“We know that trust is non-negotiable.” - Vinay BhaskarThank you for tuning in to The CUInsight Network, with your host, Robbie Young, Vice President of Strategic Growth at CUInsight. In The CUInsight Network, we take a deeper dive with the thought leaders who support the credit union community. We discuss issues and challenges facing credit unions and identify best practices to learn and grow together.My guests on today's show are Patrick McElhenie, Chief Growth Officer and Vinay Bhaskar, Chief Operating Officer of Scienaptic AI. We discuss where lending is headed and why the next leap in AI could fundamentally change how credit unions operate.In our conversation, Patrick and Vinay explain how Scienaptic helps credit unions approve more loans while reducing risk and improving members' experiences. We learn how Scienaptic's platform considers the full life cycle of the member so that decisions are not isolated. We then dig into the main topic of the episode: agentic AI, with Patrick breaking it down into simple terms for us. While traditional AI helps answer “Should we approve this loan?” agentic AI asks, “What should we do next?” Agentic AI can coordinate workflows across systems while keeping humans firmly in control.As we wrap up the episode, Vinay also shares where credit unions will first feel the impact, especially within the first 60-90 days. He projects fewer false declines, more targeted engagement, and teams spending less time chasing data and more time working directly with members. We talk about explainability, audit trails, compliance guardrails, and what “governed autonomy” really looks like in practice. Finally, in closing, Patrick shares what he sees for Scienaptic's future on the road ahead. Enjoy my conversation with Patrick McElhenie and Vinay Bhaskar!Find the full show notes on cuinsight.com.Connect with Patrick:Patrick McElhenie, Chief Growth Officer at Scienaptic AIscienaptic.aiPatrick: LinkedInScienaptic AI: LinkedIn | YouTubeConnect with Vinay:Vinay Bhaskar, Chief Operating Officer at Scienaptic AIscienaptic.aiVinay: LinkedInScienaptic AI: LinkedIn | YouTubeIn this episode:[1:11] - Patrick explains how Scienaptic enables fair, inclusive lending that boosts growth without increasing operational burden.[4:14] - Vinay reveals that their platform delivers consistent, context-driven decisions across the entire member journey.[6:52] - Hear how agentic AI moves lending from recommendation to coordinated, human-guided action.[10:08] - Early gains include faster approvals, fewer false declines, and real-time portfolio action.[13:17] - Vinay adds that built-in governance ensures explainability, auditability, and human oversight in every AI decision.[15:56] - With governed autonomy, credit unions control automation while strengthening member relationships[17:02] - Patrick discusses some of Scienaptic's plans for the future.

Better Tomorrow Ventures GP Sheel Mohnot talks with TITV Host Akash Pasricha about who could acquire PayPal and why Stripe, Apple, Amazon and the card networks might want it. We also talk with The Information's Ann Gehan about the shift from agentic commerce to checkout buttons inside AI chat products and Stephanie Palazzolo about the language and data challenges facing AI audio models and OpenAI's push into India, and we get into AI advertising economics and inference costs with Koah Co-founder Nic Baird and Theory Ventures GP Tomasz Tunguz.Articles discussed on this episode: https://www.theinformation.com/articles/17-people-crucial-ai-shoppinghttps://www.theinformation.com/newsletters/ai-agenda/chatgpt-faces-language-barriersSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/

With the rise of agentic AI, strong governance will help organizations manage security and accuracy. ModelOp CTO Jim Olsen describes...

Fraudology is presented by Sardine. Request a 1:1 product demo at sardine.ai In this solo episode, Karisse Hendrick checks in from a hotel room in San Diego at the Merchant Advisory Group (MAG) conference to share urgent intelligence from the front lines of e-commerce fraud before the full chaos of conference season begins. First, Karisse explores two sophisticated new fraud trends that are leaving even seasoned investigators scratching their heads. She breaks down the rise of the "Two-Victim ATO," a unique spin on account takeover where fraudsters leverage the "legacy" and trust of an active account to bypass security, only to hit it with a completely different person's stolen credit card. Then, she dives into a high-tech trend hitting digital gift card retailers: Malware-driven session hijacking. Karisse discusses how fraudsters "piggyback" on a legitimate customer's active session and device to commit a second, high-value theft—making it nearly impossible for traditional fraud systems to flag as a separate entity.Later in the episode, Karisse discusses the "scary" new frontier of Agentic AI. She shares insights from recent tests by major retailers showing that autonomous shopping bots are beginning to make purchases that are currently indistinguishable from human behavior, creating a massive "Know Your Agent" (KYA) challenge for the industry.In this episode, we discuss:The Two-Victim ATO: Why fraudsters are adding new payment methods to active, high-history accounts instead of just using cards on file.Session Hijacking & Malware: How bad actors are using VPNs and malware to "replay" or continue a legitimate customer's session to buy high-value gift cards. Agentic AI & KYA: The difficulty in identifying AI-initiated transactions and why current device ID technology can't tell the difference between a human and a bot.Upcoming Events: Details on the Merchant Advisory Group, and the first annual Merchant Fraud Alliance Conference in Chicago this October.Fraudology is hosted by Karisse Hendrick, a fraud fighter with decades of experience advising hundreds of the biggest ecommerce companies in the world on fraud, chargebacks, and other forms of abuse impacting a company's bottom line. Connect with her on LinkedIn She brings her experience, expertise, and extensive network of experts to this podcast weekly, on Tuesdays.

How do you redesign the most visited e-commerce webpage in the world? Rahul Chaudhari helped reshape the Amazon homepage during his years as a product leader there, before becoming VP of Product and Technology at Kohl's. In this episode, Rahul shares: Amazon's “customer backwards” approach - and how he used it to unlock half a billion dollars of value on the Amazon homepage The secret to product adoption: leverage existing customer habits to unlock new opportunities And how Amazon and Google raised the bar for digital experiences so high that now every other product pays the price Links Rahul's LinkedIn: https://www.linkedin.com/in/rahul-chaudhari/ Chapters 00:00 Intro: Rahul's journey from marketing to product 03:08 Why “mid” digital experiences no longer work 07:35 Rebuilding the Amazon homepage “hero” to be customer-backwards 12:48 Experimentation + adoption metrics: measuring what actually matters 14:20 Adoption > clicks: Defining the right success metrics 18:41 AI and the future of retail: Rethink the business model, not the tools 21:50 Agentic shopping: What happens when ChatGPT becomes the homepage? 23:30 From keyword search to intent-based shopping 25:57 AI needs containers, not just models 30:29 Will AI level the playing field for small retailers? 33:16 Conclusion Follow LaunchPod on YouTube We have a new YouTube page! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.Special Guest: Rahul Chaudhari.

This episode of The Times Tech podcast is sponsored by PwC.Artificial intelligence is entering a new phase. It's no longer just about chatbots generating text or analysing data. The next frontier is agentic AI systems that can coordinate tasks, make decisions and act with a degree of autonomy. In this sponsored bonus episode, brought to you by PwC, Katie Prescott speaks to Lilia Christoff, Partner for AI and Data at PwC, about what agentic AI really means in practice. Hosted on Acast. See acast.com/privacy for more information.

This theory explains how AI agents can make promises and build trust… with other agents. Today, we're talking to Doctor Mark Burgess, the originator of Promise Theory, and Tony Davis, Senior Director of Agentic Strategy at A&I Solutions. We discuss why command-and-control fails with autonomous AI agents, how agents respond to peer rejection instead of human disapproval, and why Promise Theory is the backbone of governing agentic workforces. All of this right here, right now, on the Modern CTO Podcast!  Thank you to A&I Solutions for sponsoring this episode. To learn more, check out their website her

Today on our show:Stripe's $140 Billion QuestionWhy Temu is the New Cross-Border StandardThe UPS $150k Exit: Strategic Rightsizing or a Teamster Trap?Is Agentic Commerce a Nothingburger? The Agentic Debate Series, presented by Logicbroker.- and finally, The Investor Minute, which contains 5 items this week from the world of venture capital, acquisitions, and IPOs.Today's episode is sponsored by Mirakl.https://www.watsonweekly.com/https://www.youtube.com/@WatsonWeeklyhttps://www.rmwcommerce.com/ecommerce-podcast-watsonweekly

In this episode of One Vision — FinTech Fuse podcast, Theodora Lau and Jas Randhawa discuss the Universal Commerce Protocol (UCP) and implications for agentic commerce. They explore the challenges of chargebacks, the need for regulatory clarity, and the importance of consumer independence in the evolving landscape of e-commerce. While adoption is likely to grow, major risks include consumer manipulation, monopolistic outcomes, and the amount of personal data agents may require (buying, browsing, health, and other patterns), increasing privacy and security concerns. Now is the time to engage with policymakers and advocate for regulatory clarity and for the well-being of consumers. 00:00 Welcome Back to One Vision + Introducing Jas Randhawa (StrategyBRIX)01:10 What Is the Universal Commerce Protocol (UCP)? The Big Picture03:27 How UCP Works: Product Cataloging for AI Shopping Agents07:05 KYA (Know Your Agent): Identity, Authorization & Trust08:58 Chargebacks in Agentic Commerce: Who's Liable When Things Go Wrong?12:02 Fraud Detection Breaks: Geolocation, New Signals & Re-Engineering Controls13:44 Agent Independence & Consumer Protection: Bias, Collusion, and Oversight Gaps21:28 Regulatory Clarity (or Lack Thereof): The ‘Wild West' Phase + T&Cs Reality28:06 Time to Get Ready: Travel Use Cases, Audit Trails, and Dispute Proof33:26 Sanctions, VPNs, and High-Velocity Agent Behavior: Financial Crime Risks37:12 Are We Too Early? Will Consumers Adopt—and at What Cost?42:59 Privacy, Data Control & The Need for Neutral Standards Bodies (Wrap-Up)47:45 Final Thoughts#AI #AgenticCommerce #UCP #Agents #Fintech Hot take:  ”The amount of information this agent now needs to have about me is shocking and it scares me a little bit because you're talking about buying patterns, browsing patterns, sleeping patterns, health pattern. For this agent to be really effective, it just needs to know everything that's in my head, right? It's gonna be very effective, but that's again, a major risk because no one's watching out for the consumer.”Hot take: “ The future of this world is unfortunately not you or me. It's a lot of these younger kids, their ecosystem is a lot different. These products are being designed for them.”More about our guest

Guests: Alexander  Pabst, Global Deputy CISO, Allianz SE Michael Sinno, Director of D&R, Google Topics: We've spent decades obsessed with MTTD (Mean Time to Detect) and MTTR (Mean Time to Respond). As AI agents begin to handle the bulk of triage at machine speed, do these metrics become "vanity metrics"? If an AI resolves an alert in seconds, does measuring the "mean" still tell us anything about the health of our security program, or should we be looking at "Time to Context" instead? You mentioned the Maturity Triangle. Can you walk us through that framework? Specifically, how does AI change the balance between the three points of that triangle—is it shifting us from a "People-heavy" model to something more "Engineering-led," and where does the "Measurement" piece sit? Google is famous for its "Engineering-led" approach to D&R. How is Google currently measuring the success of its own internal D&R program? Specifically, how are you quantifying "Toil Reduction"? Are we measuring how many hours we saved, or are we measuring the complexity of the threats our humans are now free to hunt? Toil reduction is a laudable goal for the team members, what are the metrics we track and report up to document the overall improvement in D&R for Google's board? When you talk to your board about the success of AI in your security program, what are the 2 or 3 "Golden Metrics" that actually move the needle for them? How do you prove that an AI-driven SOC is actually better, not just faster? We often talk about AI as an "assistant," but we're moving toward Agentic SOCs. How should organizations measure the "unit economics" of their SOC? Should we be tracking the ratio of AI-handled vs. Human-handled incidents, and at what point does a high AI-handle rate become a risk rather than a success? Resources: Video version EP252 The Agentic SOC Reality: Governing AI Agents, Data Fidelity, and Measuring Success EP238 Google Lessons for Using AI Agents for Securing Our Enterprise EP91 "Hacking Google", Op Aurora and Insider Threat at Google EP236 Accelerated SIEM Journey: A SOC Leader's Playbook for Modernization and AI EP189 How Google Does Security Programs at Scale: CISO Insights EP75 How We Scale Detection and Response at Google: Automation, Metrics, Toil The SOC Metrics that Matter…or Do They? blog An Actual Complete List Of SOC Metrics (And Your Path To DIY) blog Achieving Autonomic Security Operations: Why metrics matter (but not how you think) blog

Josh chats with Brad Axen from Block about his creation Goose as well as the Agentic AI Foundation (AAIF). I am quite skeptical of many AI claims, but Brad has a very pragmatic view about where things are today and where we might see them head. Donating Goose to the AAIF is great news as well as seeing MCP and AGENTS.MD in the foundation. We discuss how to deal with the problem of raising up junior developers, challenges of AI PRs, and some thoughts on how to get started if you're interested in AI development. The show notes and blog post for this episode can be found at https://opensourcesecurity.io/2026/2026-02-goose-aaif-brad-axen/

In this episode, host Sandy Vance and Ted Dinsmore discuss the ever-evolving role of AI in healthcare, industry trends, challenges, and solutions. They explore the concept of agentic AI and the Model Context Protocol (MCP), which aims to enhance data integration and efficiency in healthcare systems. They also highlight the importance of building trust in AI solutions, particularly in rural healthcare settings. Listen in to learn how SphereGen is addressing these challenges through innovative AI implementation approaches. In this episode, they talk about: Latest AI trend: agentic AI and bots, and MCP in the healthcare industry MCP allows us to speed up that integration Trust is a huge issue when you're having an impact on the patient The benefits of using MCP for hospitals and patients The concerns about the changes and cuts to rural healthcare The most common use cases when transitioning: eligibility, prior authorization, and denials management The effects on how healthcare systems are doing business with EHRs Next big use cases and what's coming up next Solving challenges in rural healthcare over the next few years How rural healthcare and homecare are tied At the end of the day, it's all about how AI can help free up time for people A Little About Ted: Ted Dinsmore is the President of SphereGen Technologies, located in New Haven, Connecticut, Toronto, Canada, and Pune, India. SphereGen is a software consulting firm that develops and supports custom software solutions for clients in AI and Automation, Application Development, and Extended Reality (AR, VR, MR). His experience in the world of IT spans over 30 years. When Ted started his first consulting firm, he became invested in developing and supporting Microsoft solutions for large multinational companies. Wanting to stay at the forefront of emerging technologies, his current company, SphereGen, embraces the world of AI/Automation and Mixed Reality (MR). SphereGen focuses on improving processes for healthcare organizations by leveraging innovative technologies, along with partners UiPath and Microsoft, to solve business problems.

Exploring the concept of agentic AI and its transformative impact on business processes and personal productivity. Learn how virtual employees can automate routine tasks, standardize workflows, and free up human potential for higher-value activities.

In this episode of Minter Dialogue, host Minter Dial sits down with Peter Morgan, a theoretical physicist turned entrepreneur, data scientist, and AI consultant. With a career that spans from quantum particle physics to building tech companies and now leading Deep Learning Partnership, Peter Morgan brings a provocative and insightful perspective on the current state and future of artificial intelligence. Together, they explore the rapid evolution of AI — from large language models to today's focus on agentic AI and autonomous digital workers. Peter Morgan offers a candid look at the challenges and opportunities businesses face when implementing AI, demystifies artificial general intelligence (AGI), and weighs in on topics like AI and human emotion, the value of proprietary data, and ethical leadership in a time of technological upheaval. The conversation also spans the impact of AI on industries such as healthcare and cybersecurity, the shifting role of the human workforce, and what the emergence of agentic AI means for both business strategy and society at large. Whether you're an executive wondering how to future-proof your organization, or simply AI-curious, this episode offers a blend of humility, practical advice, and mind-expanding discussion that's sure to spark new ideas about our place in the age of intelligent machines.

Jim Love discusses how rapid adoption of agentic AI is repeating the industry pattern of shipping technology without security, citing issues like vulnerabilities in Anthropic's MCP and insecure open-source agent tools. He interviews Ido Shlomo, co-founder and CTO of Token Security, who argues AI agents are fundamentally hard to secure because they are non-deterministic, have infinite input/output space, and often require broad permissions to be useful.  Cybersecurity Today  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale.  You can find them at Meter.com/cst Shlomo proposes focusing security on access, identity, attribution, least privilege, and auditability rather than trying to filter prompts and outputs, and describes Token's "intent-based permission management" approach that maps agents and sub-agents as non-human identities tied to their purpose and allowed actions. The conversation covers real-world risks such as developer tools like Claude Code running with extensive access, widespread over-provisioning of admin permissions and API keys, exposure of unencrypted local token files, and misconfigurations that leak data publicly. Shlomo recommends organizations build governance processes for agents—discovery/inventory, boundary setting, continuous monitoring, and secure decommissioning—and says AI is needed to help police AI. He also highlights emerging trends like agent teams and multi-day autonomous tasks, and notes Token Security is a top-10 finalist in the RSA Innovation Sandbox 2026, planning to present an intent-and-access-focused security model for AI agents. 00:00 Sponsor: Meter's integrated networking stack 00:19 Why agentic AI security is breaking (MCP & open-source chaos) 02:53 Meet Token Security: practical guardrails for AI agents 04:57 Why you can't just ban agents at work (shadow AI reality) 06:24 Tel Aviv's cybersecurity pipeline: gaming, military, and startups 08:57 Why AI/agents are fundamentally hard to secure (new OS + 'human spirit') 13:44 Trust, autonomy, and permissions: managing the blast radius 18:17 Real-world exposure: Claude Code and the developer identity attack surface 20:16 A workable approach: treat agents as untrusted processes with identity + least privilege 22:33 Zero Trust for Agents: Access ≠ Permission to Act 23:27 Token's "Intent-Based Permission Management" Explained 25:29 Building the Identity Map: Tracing What Agents Touch 26:52 The Secret Sauce: Using AI to Secure AI in Real Time 28:10 Real-World Case: 1,500 Agents and Wildly Over-Provisioned Access 30:57 CUA 'Computer-Use' Agents: Exciting, Personal… and Terrifying 34:44 Secure-by-Default & Sandboxing: Fixing 'Always Allow' Dark Patterns 35:36 What Security Teams Should Do Now: Inventory, Boundaries, Governance 37:59 What's Next: Agent Teams and Multi-Day Autonomous Work 40:10 Tony Stark Vision: Agents That Improve the Human Experience 41:02 RSA Innovation Sandbox: Token's Big Bet on Intent + Access 43:01 Wrap-Up, Audience Q&A, and Sponsor Message

Feb 20, 2026 – Curious about agentic AI models like OpenClaw, Claude Cowork, and the major changes they're bringing to the market and software world? FSWM's Research and Trading Analyst Xavier Stonehouse discusses the current events...

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic. To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/ ----- In this episode, I sit down with my friend Rohit Krishnan - writer of the Substack newsletter Strange Loop Canon - for a hands-on conversation about what it actually looks like to build with AI agents today. Between us we're burning through tens of billions of tokens a month - I hit nearly 100 million in a single day this week - and we share what we're each running on our own machines. We dig into the quirks and surprising power of tools like OpenClaw, Claude Code, and Cowork, debate why AI remains stubbornly bad at good writing, and zoom out to ask what a world of trillions of agents might actually look like — and what economic infrastructure it will need. We covered: (03:15) What's on your screen right now? (04:30) OpenClaw (06:27) Rohit's agent, Morpheus (11:06) Azeem's agent, R. Mini Arnold (19:25) The analyst is now a machine (22:36) 100 million tokens in a day: the new normal (24:44) Building tools to improve AI writing: Horace and Broca (32:19) Why writing is the hardest eval for LLMs (39:18) Towards a trillion agents (42:09) The agentic economy: coordination, identity, and exchange (46:33) How to get started with OpenClaw (51:18) The hardest leap for new users ----- Where to find me: Exponential View newsletter: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azhar/ Twitter/X: https://x.com/azeem Production by EPIIPLUS1 Production and research: Baba Films, Chantal Smith, Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Our Head of U.S. Internet Research Brian Nowak joins U.S. Small and Mid-Cap Internet Analyst Nathan Feather to explain why the future of agentic commerce is closer than you think.Read more insights from Morgan Stanley.----- Transcript -----Brian Nowak: Welcome to Thoughts on the Market. I'm Brian Nowak, Morgan Stanley's Head of U.S. Internet ResearchNathan Feather: And I'm Nathan Feather, U.S. Small and Mid-Cap Internet Analyst.Brian Nowak: Today, how AI-powered shopping assistants are set to revolutionize the e-commerce experience.It's Tuesday, February 17th at 8am in New York.Nathan, let's talk a little bit about agentic commerce. When was the last time you reordered groceries? Or bought household packaged goods? Or compared prices for items you [b]ought online and said, ‘Boy, I wish there was an easier way to do this. I wish technology could solve this for me.'Nathan Feather: Yeah. Yesterday, about 24 hours ago.Brian Nowak: Well, our work on agentic commerce shows a lot of these capabilities could be [coming] sooner than a lot of people appreciate. We believe that agentic commerce could grow to be 10 to 20 percent of overall U.S. e-commerce by 2030, and potentially add 100 to 300 basis points of overall growth to e-commerce.There are certain categories of spend we think are going to be particularly large unlocks for agentic commerce. I mentioned grocery, I mentioned household essentials. We think these are some of the items that agentic commerce is really going to drive a further digitization of over the next five years.So maybe Nathan, let's start at the very top. Our work we did together shows that 40 to 50 percent of consumers in the U.S. already use different AI tools for product research, but only a mid single digit percentage of them are actually really starting their shopping journey or buying things today. What does that gap tell you about the agentic opportunity and some of the hurdles we have to overcome to close that gap from research to actual purchasing?Nathan Feather: Well, I think what it shows is that clearly there is demand from consumers for these products. We think agentic opens up both evolutionary and revolutionary ways to shop online for consumers. But at the moment, the tools aren't fully developed and the consumer behavior isn't yet there. And so, we think it'll take time for these tools to develop. But once they do, it's clear that the consumer use case is there and you'll start to see adoption.And building on that, Brian, on the large cap side, you've done a lot of work here on how the shopping funnel itself could evolve. Traditionally discovery has flowed through search, social or direct traffic. Now we're seeing agents begin to sit in the start of the funnel acting as the gatekeeper to the transaction. For the biggest platforms with massive reach, how meaningful is that shift?Brian Nowak: It is very meaningful. And I think that this agentic shift in how people research products, price compare products, purchase products, is going to lead to even more advertis[ing] and value creation opportunity for the big social media platforms, for the big video platforms. Because essentially these big platforms that have large corpuses of users, spending a lot of time on them are going to be more important than ever for companies that want to launch new products. Companies that want to introduce their products to new customers.People that want to start new businesses entirely, it's going to be harder to reach new potential customers in an agentic world. So, I think some of these leading social and reach based video platforms are going to go up in value and you'll see more spend on those for people to build awareness around new and existing products.On this point of the products, you know, our work shows that grocery and consumer packaged goods are probably going to be one of the largest category unlocks. You know, we already know that over 50 percent of incremental e-commerce growth in the U.S. is going to come from grocery and CPG. And we think agentic is going to be a similar dynamic where grocery and CPG is going to drive a lot of agentic spend.Why do you think that is? And sort of walk us through, what has to happen in your mind for people to really pivot and start using agents to shop for their weekly grocery basket?Nathan Feather: I think one of the key things about the grocery category is it's a very high friction category online. You have to go through and select each individual ingredient you want [in] the order, ensure that you have the right brand, the right number of units, and ensure that the substitutions – when somebody actually gets to the store – are correct.And so for a user, it just takes a substantial amount of time to build a basket for online grocery. We think agentic can change that by becoming your personal digital shopper. You can say something as simple as, ‘I want to make steak tacos for dinner.' And it can add all of the ingredients you want to your order. Go from the grocery store you like. And hey, it'll know your preferences. It'll know you already like a certain brand of tortillas, and it'll add those to the cart. And so it just dramatically reduces the friction.Now, that will take time to build the tools. The tools aren't there today, but we think that can come sooner than people expect. Even over the next one to two years that you start to get this revolutionary grocery experience.And so, it's coming. And from your perspective, Brian, once agentic grocery shopping does start to work, how does that impact the broader e-commerce adoption curve? Does it pull forward agentic behavior in other categories as well?Brian Nowak: I think it does. I think it does lead to more durable multi-year, overall e-commerce growth. And potentially in some of our more bull case scenarios, we've built out – even an acceleration in e-commerce growth, even though the numbers and the dollars added are getting larger. But there is some tension around profitability.We are in a world where a lot of e-commerce companies, they generate an outsized percentage of their profit from advertising and retail media that is attached to current transactions. Agentic commerce and agents wedging themself between the consumer and these platforms potentially put some of these high-margin retail media ad dollars at risk.So talk us through some of the math that we've run on that potential risk to any of the companies that are feeding into these agents for people to shop through.Nathan Feather: Well, in our work for most e-commerce companies, a majority – or sometimes even all – of their e-commerce profitability comes from the advertising side. And so this is the key profit pool for e-commerce. To the extent that goes away, there is one potential offset here, which is the lower fee that agentic offers for companies that currently have high marketing spend. To the extent that agentic offers a lower take rate, that could be an offset.But we think it's going to be very important for companies to monitor the retail media landscape and ensure they can try to keep direct traffic as best as possible. And things like onsite agents could be really important to making sure you're staying top of mind and owning that customer relationship.Now, on the platform side, search today captures an implied take rates that are 5-10 times higher than what we're seeing in the early agentic transaction fees. If this model does shift from CPC – or cost per click – towards a more commission based model, Brian, how do you think search platforms respond?Brian Nowak: I think the punchline is the percentage of traffic and transactions that retailers or brands or companies selling their items online that's paid is going to go up. You know, while search is a relatively more expensive channel on a per transaction basis, search works because there's a very large amount of unpaid and direct traffic that retailers benefit from post the first time they spend on search.Just some math on this. We're still at a situation where 80 percent of retailers' online traffic is free. Or direct. And so if we do get into a situation where there's a transition from a higher monetizing per transaction search to a lower monetizing per transaction agent, I would expect the search platforms to react by essentially making it more challenging to get free and direct and unpaid traffic. And we'll have that transition from more transactions at a lower rate; as opposed to fewer transactions at a higher rate, which is what we have now,Nathan, in our work, we also talked about a Five I's framework. We talked about inventory, infrastructure, innovation, incrementality and income statement, sort of a retailer framework to assess positioning within the agentic transition. Maybe walk us through what your big takeaways were from the Five I's framework and what it means that retailers need to be mindful of throughout this agentic transition.Nathan Feather: Well, for retailers, I think it's going to be very important that you're winning by differentiation. Having unique, competitively priced inventory with infrastructure that can fulfill that quickly to the consumer and critically staying on the leading edge of innovation.It's one thing to have the inventory. It's another thing to be able to be actively plugged into these agentic tools and make sure you're developing good experiences for your customers that actually are on this cutting edge. In addition, it's one thing to have all of that, but you want to make sure there's also incrementality opportunity.So [the] ability to go out, expand the TAM and gain market share. And of course what we just talked about with the margin risk, I think all of those are going to be very important. And so on balance for retailers, we do see a lot of opportunity. That's balanced with a lot of risk. But this is one of those key transition moments that we think companies that really execute and perform well should be able to perform nicely.Now finally, Brian, over the next five years, how do you think agent commerce reshapes competitive dynamics across the internet ecosystem?Brian Nowak: I think over the next few years, we're going to realize that agentic commerce is no longer a fringe experiment or a concept. It's a reality. And we may get to the point where we don't even talk about agentic commerce or agentic shopping. We just say, “‘This cool thing I did through my browser.' Or, ‘Look at what my search portal can do. Look at how my search portal found me this product. Look at how my groceries got delivered.' And it'll become part of recurring life. It'll become normal.So right now we say it's agentic, it's far off. It's going to take time to develop. But I would argue that every year that goes by, it's going to be becoming more part of normal life. And we'll just say, ‘This is how I shop online.'Nathan, thanks for taking the time todayNathan Feather: It was great speaking with you, Brian.Brian Nowak: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen. And share the podcast with a friend or colleague today.

Yeah, you prolly saw the news: OpenAI acquihired OpenClaw.