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The Deep View: Conversations: Daily Summaries Delivered
by The Deep View
From frontier labs and enterprise platforms to emerging startups reshaping entire industries, The Deep View: Conversations podcast interviews the brightest minds and the most influential leaders in AI.
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The most recent episodes — sign up to get AI-powered summaries of each one.
- 4 days ago50 min
How to turn everyday frustrations into AI wins
Your next big AI win may come from someone your leadership team would never think to pick.In this episode of The Deep View Conversations, we sit down with Todd Earwood, CEO of Betra Works and an AI investor at HalfCourt Ventures, to explore what it takes to deploy AI for useful work inside organizations. Drawing on his work with 1,200 leaders and executives, Todd explains why the people closest to the work often see AI opportunities that executives miss. He shares how a university athletics sales rep used AI to uncover new ticket buyers, how a warehouse employee helped a manufacturer rethink a 22-year-old spreadsheet, and why a skeptical, experienced employee became an unexpected AI champion.We also discuss Todd's book, Adapt & Adopt, and his approach to teaching people how to identify useful AI tasks, evaluate opportunities, and build momentum from individual wins to broader adoption.Other topics covered:• Three paths to putting AI to work in a business• Why employee frustrations can reveal valuable AI opportunities• The gap between personal AI use and workplace adoption• What Todd learned from investing in more than 100 AI companies• Building a tech career outside San Francisco and New York• Why meeting recorders and voice dictation can make an immediate difference• Using Claude to protect your calendar and prioritiesIf you're leading a team, trying to make AI useful in your own job, or deciding where to start, this conversation offers practical ways to connect AI's capabilities with the work people do every day.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.comTIMELINE0:00 Introduction2:27 From AI investing to real-world adoption7:19 Three paths to making AI useful10:16 Adapt & Adopt: learning how to think16:34 Unexpected AI wins in sales and manufacturing21:14 Finding AI opportunities in the work you hate23:45 Why your AI champions may surprise you27:02 Investing in AI before the boom33:49 Building a tech career beyond the coastal hubs40:44 Meeting recorders, Wispr Flow and everyday AI45:24 Using AI to protect your time48:58 Closing advice: slow down when life gets hard
- 1 weeks ago39 min
6 timeless attributes for succeeding in the AI era
AI is making it easier for employees to work beyond their specialties and that has big implications for the future organizations of all sizes. In this episode of The Deep View Conversations, we sit down with Bill Barton, chief operating officer at Rokt and the former leader of the Alexa team at Amazon. Rokt has gotten called out by some of the biggest tech companies in the world for its innovative use of AI inside the company. In fact, several of them have had Rokt come and talk to their teams about how they do it. So we wanted to have Bill on the show to share those insights with a larger audience.Barton shares how Rokt is using an internal AI fleet across software development, finance, legal, security and other functions. He explains how AI is helping blur the boundaries between roles, why the company has moved from more than a dozen job ladders to four, and what it takes to turn experimentation into everyday practice.Other topics covered include:• Why Bill returned to Rokt after trying retirement• How AI is expanding the reach of generalists• Enabling shared AI experimentation companywide• Why fewer, more flexible systems can help teams move faster• How Barton thinks about productivity gains and hiring• What Google search reveals about frictionless AI• Why more powerful tools can make it harder to step away from workBill also shares his six timeless attributes that can help anyone succeed in the AI era: relentlessness, resilience, rigorousness, inquisitiveness, optimism and humility.For leaders rethinking their teams and professionals navigating changing roles, this conversation connects the possibilities of AI with the habits and judgment needed to make them useful.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
- 2 weeks ago26 min
How open models change the economics of AI
Companies want to own the intelligence that makes their business valuable. So what will that mean for the AI models they use, and the systems they build around them?In this episode of The Deep View Conversations, we sit down with Justin Boitano, VP of enterprise AI at Nvidia, to explore why NVIDIA is investing in open models and how enterprises are turning them into specialized intelligence. Boitano talks about why NVIDIA makes Nemotron's datasets, training techniques and model weights openly available, how proprietary business knowledge can become a competitive advantage, and why lower token costs can unlock much greater demand for AI.The conversation also examines why the agent harness that manages tools, memory and execution can matter as much as the model itself. Boitano shares how Nvidia worked with CrowdStrike on AI models for cybersecurity, why AI incidents need the equivalent of an aviation flight recorder, and how OpenShell moves agent controls into the infrastructure layer.Other topics covered:• Why NVIDIA is building open models alongside its chip business• What Nemotron needs to compete with China's open models• Owning institutional knowledge, protecting data and controlling AI costs• How model development helps NVIDIA improve hardware efficiency• Why harness engineering is becoming a new frontier for AI• Moving cybersecurity from finding bugs to verifying and fixing them• Transparency and learning from AI incidents• OpenShell, sandboxing and enforceable limits on agent access• How Justin uses Hermes as an AI chief of staff• Jensen Huang's approach to priorities and team alignmentIf you're deciding how to build enterprise AI, where your company's competitive advantage comes from, or how to give agents useful access without giving them unlimited control, this conversation offers a perspective from Nvidia's work across the ecosystem.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
- 3 weeks ago45 min
Who will police the AI agents?
AI agents can act faster than humans can review them. So how do companies keep control without slowing everything down?In this episode of The Deep View Conversations, Jason Hiner sits down with Blake Brannon, chief innovation officer and a co-founder of OneTrust, to explore why AI governance needs to evolve from static rules to decisions made in real time.Brannon explains why an agent can inherit an employee's identity and access without inheriting their trust. He makes the case for independent guardian agents that evaluate what other agents are trying to do, apply a company's policies, and redirect or block actions when necessary.One example captures the challenge: deleting CRM records could be routine cleanup or an attempt to inflate a salesperson's performance. The action alone doesn't tell you whether it should be allowed. Its purpose matters.Topics covered:• How OneTrust evolved from data privacy to AI governance• Why first-party data and customer trust go together• Why human review can't keep pace with a growing population of agents• How guardian agents and independent checks could help close the trust gap• The difference between containing AI and aligning it with business policies• Why governance should help companies move faster• What the bring-your-own-device era teaches us about AI adoption• How Blake uses visual storytelling and voice-to-text tools to work more effectivelyIf you're deploying AI agents and trying to move beyond experiments without giving up control, this conversation offers a practical way to think about the systems that need to surround them.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
- 4 weeks ago24 min
How AI changes cybersecurity's balance of power
AI is accelerating cyberattacks. Could it also give defenders the upper hand?In this episode of The Deep View Conversations, we sat down with Adam Meyers, CrowdStrike's head of counter adversary operations, at Fal.Con 2026 to explore how AI is changing the balance of power between attackers and defenders. Meyers explains why he believes security teams can now match the speed and scale of their adversaries, how CrowdStrike is training offensive and defensive AI models against each other, and why the harness that guides an AI model can matter just as much as the model itself. He shares how changing that harness helped CrowdStrike reduce false positives in its vulnerability research without changing the underlying model, and how cyberdefenders are uniting to assist one another.The conversation also goes inside the live disruption of the Sality botnet, explores how nation-state attackers are using agents that learn from their mistakes in seconds, and examines why powerful AI systems need clear boundaries as they pursue their goals.Topics covered:• Why AI could change the defender's dilemma• How CrowdStrike and its partners disrupted a botnet that had operated for more than two decades• Training red team and blue team models based on Nvidia's Nemotron models and CrowdStrike's security data• Why AI harnesses are critical to reducing hallucinations and false positives• How AI attacks are compressing the time organizations have to patch vulnerabilities• What the Hugging Face incident raises about goal-seeking agents and guardrails• Why local, open-weight models matter to both attackers and defendersIf you're trying to understand what AI means for cybersecurity, how to put agents to work safely, or where specialized models can make a difference, this conversation offers a view from someone tracking the adversaries firsthand.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm Get The Deep View daily newsletter for clear analysis of AI's biggest developments and practical insights you can put to good use: subscribe.thedeepview.com
- Sep 27, 202628 min
Why your phone still isn't the ultimate AI assistant
Nearly every smartphone launched in the past year features agentic AI capabilities, offering users an early look at what a fully agentic smartphone future could do for them. Of course, the tech powering it is driven by the chipsets.In this episode of The Deep View Conversations, we talked with Vinesh Sukumar, Qualcomm's VP of AI at the Snapdragon Summit, the company's annual conference where it launches its latest processors. This year, the launch included the mobile platforms Snapdragon 8 Elite Extreme Gen 6 for phones and Snapdragon Sound Elite Gen 2 for wearables.Vinesh discussed how the chipsets came to be, including the special considerations made during their design such as improving connectivity, on-device support for large models, longer battery life, and other features crucial to smoothly running agentic AI applications. We also discussed what the future of a truly agentic AI phone looks like and what's been holding it back.Topics covered:• What an ideal agentic smartphone experience would look like • The demands agentic AI models make of mobile chipsets• The obstacles to agentic solutions becoming a game changer • The crawl, run, walk phases of agentic solutions, and where we are now• The role of other smart devices in creating agentic experiences • How support for a 30 billion MoE on-device model was made possible • Qualcomm's role in working with partners to bring AI experiences to lifeIf you want to learn more about how the latest chipsets will change the future of Android flagship devices in the next year, including new AI experiences, this conversation will give you a clear idea.📺 Watch on YouTube: https://youtu.be/YXvw9Gw41Xg 🎧 Listen in your favorite podcast player: Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology.And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.comDisclaimer: Sabrina Ortiz's travel to Snapdragon Summit was paid for by Qualcomm. The Deep View's coverage is editorially independent from the companies we cover.
- Sep 24, 202654 min
AI safety needs more than good intentions
Can AI move fast and still be safe? As the debate over AI safety and innovation grows more polarized, we explore the practical work of making powerful systems accountable.In this episode of The Deep View Conversations, we sit down with Navina Singh, CEO of Credo AI, to talk about what AI governance means for frontier labs, enterprises, and policymakers. They explore why governance is broader than regulation, how organizations can test and verify their AI systems, and what happens when capabilities advance faster than oversight.Topics covered:• Why Navrina sees AI safety and innovation as goals that can advance together• What the Hugging Face agent incident raises about frontier AI oversight• The “spectrum of trust,” from internal testing to independent audits and regulation• The risk of regulatory capture and the role of open models• How businesses weigh AI capability, cost, and control while managing "governance debt"• How Credo AI uses forward-deployed governance experts to help companies put oversight into practice• Why expertise, taste, and judgment remain valuable as AI takes on more workIf you’re building, buying, or governing AI, this conversation offers a practical way to think about trust without losing sight of the technology’s promise.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
- Sep 20, 202624 min
Who will be the adult in the room on AI?
What does it take for companies to use agentic AI to transform the enterprise, without losing control of the technology?In this episode of The Deep View Conversations, we sit down with Shibani Ahuja, SVP of data and AI strategy at Salesforce, to discuss how one of the world's leading software companies is applying AI with practical use cases, matching governance to risk, and building toward larger transformations ahead. Salesforce has surprisingly embraced a "headless" AI strategy that lets customers use any AI to access their Salesforce data safely and securely. That includes its own Slackbot, which sits inside one of the world's most widely used business messaging systems. In this interview, we learn more about why Salesforce wants to give customers optionality.Shibani also lays out Salesforce’s four modes of enterprise AI, from everyday assistive tools to agents that can reshape end-to-end operations. We also discuss Koa, Salesforce’s new CRM reasoning model, why the model-plus-harness approach is so critical, and why adaptability may be the defining enterprise skill of the AI era.Topics covered:• Why organizations should start with practical, level-one AI use cases• How Salesforce matches governance and ROI expectations to the risk of an AI deployment• What Koa, Salesforce's AI model built on NVIDIA Nemotron, changes for enterprise AI• Why operating models, process expertise, and professional services matter as much as the latest technology• Shibani's case for AQ: the adaptability quotient for technology stacks and teamsIf you’re trying to make AI more efficient, safer, and more ROI-driven, this conversation offers a practical framework for how to build it, how to govern it, and where to start.Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
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