The Deep View: Conversations

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

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

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

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

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 workloads
This 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