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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.
- Today24 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
- 1 weeks ago45 min
#65 - Why iPhone Duo could change how we use AI - Sabrina Ortiz
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 phoneIf 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
- 2 weeks ago51 min
#64 - What OpenAI is building for a post-prompt future - Tara Seshan, Ty Geri
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 workIf 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
- 2 weeks ago43 min
#63 - Cheap AI raises the cost of bad judgment - Florian Douetteau
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 lazinessIf 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
- 3 weeks ago27 min
#62 - How openness became AMD’s AI strategy - Andrew Dieckmann
AI's appetite for compute keeps growing, but so does the pressure to deliver more intelligence per watt and per dollar. Can AMD's first rack-scale AI system open up an ecosystem dominated by Nvidia?In this episode of The Deep View Conversations, we sit down with Andrew Dieckmann, AMD's general manager of its data center GPU business, to unpack the company's Helios platform and the rapidly changing economics of AI infrastructure. Dieckmann explains why frontier AI requires more than just GPUs. It demands tightly engineered racks that combine GPUs, CPUs, networking, software, cooling and serviceability. The conversation examines the tension around AI data centers: hyperscalers still cannot get enough compute, while communities worry about power, water and whether the benefits justify the buildout. Andrew argues that responsible deployment and open ecosystems are essential as these systems become intelligence factories.The conversation then turns to Helios: AMD's performance claims against Nvidia Vera Rubin, pricing and value, the first likely customers, and the Cerebras partnership for high-throughput, low-latency inference. Andrew closes with his advice for leaders navigating AI velocity: reassess priorities more often and use coding agents as force multipliers for scarce engineering talent.Topics covered:• Why AMD is moving from chips to full rack-scale systems• AI demand, data center constraints, and community impact• Open hardware, open software and customer choice• How agentic AI changed infrastructure planning• Helios performance, efficiency, pricing and customers• AMD Helios versus Nvidia Vera Rubin• How AMD and Cerebras split inference workloadsThis conversation offers a clear look at the technology and economics shaping the infrastructure that will power everyday AI and the breakthroughs to come.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
- 3 weeks ago55 min
#61 - The economics pushing AI toward open models - Jeff Morgan
AI's next power shift isn't gonna happen in a data center. In this episode of The Deep View Conversations, we sat down with Jeff Morgan, co-founder and CEO of Ollama, to explore why open models are gaining momentum, and why enterprises and developers increasingly want more control over their AI.Morgan explains how Ollama grew from a two-week experiment into software used across 80% of the Fortune 500, how the economics of coding agents are pushing teams toward open models, and why cost, privacy and control are becoming decisive advantages. He also breaks down the hardware shift bringing data-center-class AI workloads to Apple silicon, Nvidia DGX Spark and systems powered by AMD, Intel and Qualcomm.The conversation also covers:• How the team behind Docker Desktop came to build Ollama• Why open models could soon process the majority of enterprise AI tokens• The role of harnesses, tool calling, routing and subagents• How Ollama fits into the open-source AI stack and where its business model comes in• Why new US and European open-model labs are emerging• Why companies may need to own and customize their intelligence layerIf you’re interested in open models, coding agents, enterprise AI or the shift from cloud-only AI to powerful local systems, this conversation offers a clear look at where the ecosystem is heading.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 ago1h 32m
#60 - Are foldables the best AI phones now? - Sabrina Ortiz
For almost a decade, foldable phones have been a product looking for a problem to solve. They may have found their lane.In a special episode of The Deep View Conversations, we make sense of Google's and Samsung's latest hardware and the AI announcements that came with them. But mostly, we talk about the new folding phones, the Pixel 11 Pro Fold and the Z Fold 8. While folding and flip phones have existed for years, this summer both Google and Samsung upped the ante by launching new experiences that let AI enthusiasts make the most of the added screen real estate for AI workflows. Topics covered include:The new AI features available on the Pixel 11 phones How Gemini contributes to the AI experience on mobileDoes Google still have the lead in AI hardware?The minimal hardware improvements to the Pixel devicesThe advantages of owning a foldable in the AI era How Samsung's Galaxy Z Fold 8 series comparesThe advantages of the Z Fold 8's "passport" form factorHow Apple's foldable, rumored to launch in September, will compete If you're trying to understand how AI is changing what you can do with a smartphone, and what your next phone purchase should be if you prioritize AI, you won't want to miss this episode. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: 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
- Aug 16, 202626 min
#59 - Let's talk about AI bubbles - Nat Rubio-Licht
AI bubble talk is rearing its head again, but the context is very different from the conversations in late 2025. In this episode of The Deep View Conversations, we unpack the common arguments about an AI bubble and explain why reality naturally falls somewhere in between the doomsayers and AI absolutists. We look at AI's "Tinker Bell problem": the boom depends partly on people continuing to believe in AI's potential, even as public skepticism grows. Beneath that belief cushion, enterprise contracts drive most of AI labs' revenue, while strong hyperscaler earnings and compute shortages suggest durable demand is building. We debunk a viral claim that a $200 Claude subscription costs Anthropic $8,000 to serve. We also look at enterprises' push for more control, efficiency and measurable ROI, including one company's claim that some engineers' token use costs 1.5 times their compensation. Other topics include:• Training, inference, API pricing and token economics• Real value, snake oil and the hype cycle• Why AI demand outruns compute supply• Why the AI bubble may look more like bubble wrap• Market rotation into energy and materials If you're trying to separate durable AI demand from hype and understand where a real correction could begin, then this conversation offers a framework for thinking about what may pop, what may deflate and what may keep growing. Keep in mind that this is industry analysis and not investor advice. 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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About The Deep View: Conversations
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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