Palantir CEO Alex Karp went on CNBC and announced a partnership with Nvidia to build an AI model that's fully air gapped for the US government. It's the biggest signal yet for a concept called sovereign AI, and it raised a question every enterprise should be asking: is my data, my prompts, and my competitive edge sitting inside someone else's model? Dhaval Kapadia and Venkatesh Sankaran recorded this emergency episode because they couldn't stop arguing about what it means.

Disclaimer: This episode was shot on July 12th, so the recent AI adoptions etc might or might not be discussed in it.

In this episode:

• Why Palantir and Nvidia's government AI deal is the biggest sovereign AI signal yet
• What sovereign AI actually means, explained simply
• The three questions every enterprise should be asking about their data, their prompts, and their competitive edge
• How Palantir is using Nvidia's open source models and air gapping them from the outside world
• Will Anthropic and OpenAI ever support sovereign AI, or does it break their business model
• The "fresh air" problem: how a fully closed system risks cutting itself off from innovation
• Why the disagreement matters: different tiers of enterprises will adopt this differently
• The realistic path for mid sized companies: on prem SLMs instead of full sovereign infrastructure
• How routing only the hardest questions to the big LLMs can cut token costs by 90 percent or more
• Why the hardware needed to run these models is about to get dramatically smaller
• Who becomes the second, third, and fourth sovereign AI customer after the US government

Timestamps:
00:00 Why this is an emergency episode
01:24 What just happened: Alex Karp, Palantir, and Nvidia
02:53 Sovereign AI, explained simply
05:45 The three questions every enterprise should ask
08:49 How the Palantir Nvidia deal actually works
10:52 Will the big LLM labs ever support sovereign AI
11:46 The "fresh air" problem: staying open to innovation
13:43 Where the hosts disagree
16:31 The realistic path for mid sized companies
16:51 Using SLMs to cut token costs by 90 percent
19:19 Why the hardware barrier is about to disappear
20:23 What comes after the US government

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Anthropic's most powerful model was blocked by the US government within days of launch, then released again with reinforced guardrails. In episode 6 of Enterprise AI Insiders, hosts Venkatesh Sankaran and Dhaval Kapadia trace the full Fable 5 and Mythos timeline and what it means for any enterprise trying to stay at the AI frontier.

They also break down the $9 billion the biggest players have committed in a matter of weeks to place AI engineers directly inside enterprise customers, and the ROI reckoning now hitting CFOs after a year of open-ended AI spending.

In this episode:
• The Fable 5 and Mythos timeline: restricted, pulled back, and re-released
• What happens to enterprises when access to frontier models can be switched off
• Why the pause gives open-source and on-prem models room to catch up
• OpenAI's new model lineup and the same safety gating playing out again
• Forward-deployed engineers: AWS, Microsoft, OpenAI, and Anthropic committing roughly $9B in weeks
• Why this is "outsourcing in reverse" and how the cost gets baked into contracts
• The ROI reckoning: Uber's token spend, the 95% experiment failure rate, and what actually returns value
• Token cost, on-prem NVIDIA, and the cloud-vs-device calculus every CFO now faces
• Why multi-vendor strategy matters more than ever

Enterprise AI Insiders is a business show for CEOs, CXOs, and founders, not a tech show. Hosted by Venkatesh Sankaran and Dhaval Kapadia.

This episode was recorded on July 11th, 2026. Figures and developments discussed were current as of that date and may have changed since. Nothing in this episode is financial, investment, or legal advice.

Satya Nadella's viral essay, "A Frontier Without an Ecosystem Is Not Stable," argues that legacy enterprises, not AI labs, will define the next phase of AI. It's sparking a comeback for small language models and on-prem, enterprise-owned AI systems.

Databricks' Data + AI Summit doubled down with Genie, an agentic system built to learn how your enterprise actually works. And Microsoft, Salesforce, and ServiceNow are now in an all-out platform war for the enterprise AI stack, even as 70 to 80% of AI experiments are failing.

In this episode:
• Why the center of gravity is shifting from AI labs to legacy enterprises
• The "harness" concept and why AI has to live inside the enterprise
• The comeback of small language models and on-prem deployment
• The token budget problem: burning a year's spend in three months
• Databricks' Genie and the "20,000 employees, 2 million agents" framework
• The platform war between Microsoft, Salesforce, and ServiceNow
• The 5 pillars to evaluate any AI platform on: build, deploy, govern, scale, secure
• Why 70 to 80% of enterprise AI experiments are failing right now
• Global platforms beyond the West: Alibaba, Sarvam, and regional AI
• Vendor lock-in and how to manage it

Enterprise AI Insiders is a business show for CEOs, CXOs, and founders, not a tech show. Hosted by Venkatesh Sankaran and Dhaval Kapadia.

Recorded on 18th June, 2026. Figures and developments discussed were current as of that date and may have changed since. Nothing in this episode is financial, investment, or legal advice.

Claude's new Mythos and Fable 5 models can run autonomously for up to 12 hours. Apple just gave Siri a major AI overhaul at WWDC. Anthropic and OpenAI have both filed for IPOs targeting trillion-dollar valuations. Dhaval Kapadia and Venkatesh Sankaran cover the biggest enterprise AI stories of the last few weeks.

In this episode:

• Claude's Mythos and Fable 5: why long-running, hours-long autonomous tasks are a game-changer for enterprise
• How Fable 5 routes sensitive queries (cybersecurity, biology, chemistry) to safer models automatically
• Token efficiency vs. token cost: why running longer doesn't mean spending more
• Real enterprise use cases: quarterly reporting, code migration, and multi-month projects done in a day
• Apple's WWDC AI overhaul: what's new with Siri and the on-device privacy angle
• The Apple-Gemini partnership and what it means for enterprise data security
• Why Apple's ecosystem control could be a foot in the door for enterprise adoption
• Anthropic and OpenAI's IPO filings: trillion-dollar valuations and $50-100B capital raises
• SpaceX's IPO and the infrastructure race behind AI
• Why profitability pressure post-IPO could reshape how AI companies sell to enterprise
• The coming wave of small language models (SLMs) and vertical-specific AI tools
• Regulation on the horizon: the AI America Act and state-level AI laws

Subscribe and hit the bell for weekly breakdowns of the enterprise AI news that actually matters!

DISCLAIMER:

Recorded June 11, 2026. Figures and developments discussed were current as of that date and may have changed. This episode is for informational purposes only.

OpenAI is making a serious move into enterprise consulting, SAP just unveiled a 200-agent "Autonomous Enterprise," and new data shows a massive gap between AI ambition and AI readiness. Dhaval Kapadia and Venkatesh Sankaran unpack this week's three biggest enterprise AI stories.

Disclaimer: This episode was shot 1-2 months back, so the recent AI adoptions etc might or might not be discussed in it.

In this episode:

• Why OpenAI acquired UK-based Tomorrowco to launch Deployco, its own forward-deployed engineering arm
• Whether OpenAI's consulting push stays exclusive to its own tech, or opens the door to Anthropic and others
• The data access question: what OpenAI really gains by putting engineers inside client companies
• SAP's "Autonomous Enterprise": 200+ AI agents and 50 Joule assistants aiming to automate 30-70% of tasks in finance, HR, and supply chain
• The Dun & Bradstreet survey finding 97% of companies have active AI initiatives, but only 5% say they're actually ready
• Why the adoption gap comes down to skills, data infrastructure, and governance — not lack of investment
• The rise of Chief AI Officer roles and what's next for enterprise AI in 2026

Big Tech just committed over $700 billion to AI in a single year. In episode 2 of Enterprise AI Insiders, our hosts Venkatesh Sankaran and Dhaval Kapadia unpack the capex explosion, whether it pays off or becomes the next metaverse, and two moves quietly reshaping how enterprises adopt AI.

Venkatesh brings a 30+ year enterprise tech lens; Dhaval brings a finance and Wall Street lens. Together they cover three stories driving the AI economy right now.

In this episode:
• The hyperscaler spending surge: Amazon, Microsoft, Google, and Meta pushing past $700B, up from roughly $400B a year ago
• Where the money comes from (balance sheet, revenue, debt) and the ROI question investors can't yet answer
• Why Meta's stock fell 7% on its spending news, and whether AI is the next metaverse
• The GPU shortage, energy grid, and training demands behind the numbers
• Why Apple isn't counted among the hyperscalers
• Anthropic's $1.5B partnership with Blackstone, Apollo, Goldman Sachs, and others, and how forward-deployed engineers challenge traditional consulting firms
• How AI labs are pushing into mid-market companies through PE portfolios
• The Pentagon and Department of Commerce AI deals, why Anthropic dropped out, and why AI safety and human oversight matter from day one

The recurring theme: this shift needs more people, not fewer.

Enterprise AI Insiders is a business show for CEOs, CXOs, and founders, not a tech show. Hosted by Venkatesh Sankaran and Dhaval Kapadia. Listen and subscribe on Spotify, Apple Podcasts, and YouTube.

DISCLAIMER:

Recorded May 7, 2026. Figures and developments discussed were current as of that date and may have changed. This episode is for informational purposes only and is not financial or investment advice.

Every company will become an AI company. In the debut episode of Enterprise AI Insiders, Venkatesh Sankaran and Dhaval Kapadia lay out why AI has stopped being a tool you plug in and has become the operating system businesses actually run on.

Drawing on Venkatesh's 30+ years building enterprise tech platforms and Dhaval's finance and Wall Street background, they argue this shift is bigger than internet, mobile, and cloud combined, and moving far faster.

In this episode:
• Why "every company becomes an AI company" is the defining shift of the next decade
• Treating AI as a tool vs. as a business operating system
• The Starbucks playbook: how a coffee chain became a tech company, and what enterprises can learn from it
• Why large enterprises, not startups, hold the real AI advantage (hint: it's the data)
• What Blue Skies AI Studio is and how it bridges startups and enterprises
• Why slow-moving enterprises risk getting left behind

This is a business show for CEOs, CXOs, and founders, not a tech show. Upcoming episodes bring guests from across the enterprise and startup ecosystem.

Listen on Spotify, Apple Podcasts, and YouTube.