The Deep View: Conversations

The Deep View
  • 4.8 (16)
  • Technology
  • Updated Weekly

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.

  1. 2d ago ·  Video

    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 effectively If 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

  2. 6d ago ·  Video

    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

  3. Sep 27 ·  Video

    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 life If 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.com Disclaimer: 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.

  4. Sep 24 ·  Video

    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 work If 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

  5. Sep 20 ·  Video

    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 teams If 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

  6. Sep 11 ·  Video

    Why iPhone Duo could change how we use AI

    Apple's first foldable iPhone makes the case that a bigger screen is better for nearly everything in the AI era. Its new Apple Watch features raise a harder question: how much of our conversations should AI remember? In this special episode of The Deep View Conversations, we record from Apple's campus in California following its September 2026 event to unpack the iPhone Duo, the new Audio Intelligence features in Apple Watch, and what Apple's latest devices mean for AI. We share our first hands-on impressions of the Duo, explain why foldables are becoming more useful for AI agents and multitasking, and examine the price and hardware compromises that come with Apple's new form factor. We also debate Live Rewind and Siri Recap, two new Apple Watch features coming in beta later this year. We disagree on which feature we would feel more comfortable using, opening up a broader discussion about privacy, trust, and staying present. The conversation also covers: • How the iPhone Duo compares with foldables from Google and Samsung • Why Apple's software experience is the Duo's biggest advantage • Camera, battery, durability, and Touch ID tradeoffs • Whether foldables will eventually become the default iPhone • Siri AI, iOS 27, and Apple's approach to other smart features without AI washing • The social questions surrounding AI-generated conversation summaries • The iPhone 18 Pro's camera upgrades and Apple's computational photography • Apple silicon, the A20 Pro, and the possibilities of running AI models locally on a phone If you're following the future of AI in phones and wearables, this conversation connects Apple's announcements to the ways people will actually use them, along with the questions that still need answers. 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

  7. Sep 6 ·  Video

    What OpenAI is building for a post-prompt future

    AI is transitioning from just answering questions to doing valuable work. The next challenge is making agents more accessible and simple enough that the technical details fade into the background. In this episode of The Deep View Conversations, we sit down with two members of OpenAI's ChatGPT Work team, Tara Seshan and Ty Geri, to dig into ChatGPT Work and what OpenAI is doing to make advanced agent capabilities useful to a lot more people. We also dig into some of the current challenges and how the team is approaching them.  Seshan and Geri explain how scheduled tasks and proactive assistance are changing the way people start their workdays, why AI lets teams move from debating ideas to testing prototypes, and how personalized software can turn one-off needs into purpose-built tools. They also discuss the challenge of token costs and model selection, why "super app" isn't the most useful framing for ChatGPT and Codex, and what it will take for agents to become more persistent, proactive, and connected. The conversation also covers:• How OpenAI is trying to bridge local and cloud workflows• Why Tara and Ty start their days with agents instead of Slack• Building personal apps and tools without traditional software overhead• The tradeoff between model capability, cost, and user control• More persistent agents and proactive personal assistance• Connecting agents to email, calendars, enterprise systems and third-party tools• Privacy, security and administrative controls for agentic work If you’re figuring out where agents fit into your work or what has to improve before you trust them with more of it, then this conversation offers a practical look at how OpenAI is preparing for that transition. 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

  8. Sep 3 ·  Video

    Cheap AI raises the cost of bad judgment

    AI makes software easier to create, but the harder and more valuable challenge is controlling what gets built, proving that it works, and managing it over time. In this episode of The Deep View Conversations, we sit down with Florian Douetteau, CEO and co-founder of Dataiku, to explore how large organizations can turn AI agents from impressive demos into safe, maintainable systems that deliver measurable business results. Douetteau explains why enterprise AI models are becoming commoditized, why companies may buy 90% of their agents but build the 10% that differentiates their business, and why the emerging discipline of "agent management" will be essential. He also breaks down the dilemma facing CEOs: move too slowly and competitors may gain a structural cost advantage; move too quickly without control and one major AI failure could create a crisis. Topics covered: • Why the cost of creating with AI is falling toward zero• Where value will accrue as models commoditize• How to balance openness, innovation and enterprise control• Why subject-matter experts must retain ownership of AI agents• Why business problems, not perfect data, should drive data strategy• How enterprises can prioritize transformative AI use cases without stifling experimentation• The three qualities Dataiku now values most when hiring• How leaders can use AI without falling into cognitive laziness If you’re trying to move enterprise AI beyond pilots, govern a growing portfolio of agents or understand where durable value will emerge as AI creation becomes cheaper, this conversation offers a practical framework for building quickly without losing control. 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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4.8
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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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