Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I unpack why Palantir’s customer-first AI approach is outperforming much larger rivals.

Highlights

00:06 — One of the drivers in 2025 and 2026 of that surge in the greatest growth market here has been Palantir, relatively small. It'll probably do seven and a half, $8 billion in the coming year.

00:42 — So I had a great chat, you can see it all, a one-on-one video conversation with Palantir architect Chad Wahlquist. Palantir's titles are a little peculiar, right? It has its own way of doing things, as it does in a number of ways. Chad's not just a typical enterprise architect.

01:23 — One of the things that's unique about Palantir is how its customers will come, sign an original deal, and then in a very short period of time, three, four, six months, greatly increase that deal because it's showing the value of the AI to the customer.

02:18 — Palantir is the company, I think, in sort of the more modern era, that's really brought this to the forefront. Chad and I talked about the partnership and the significance of that for customers, bringing together the immense data and industry expertise that SAP has.

03:15 — It's not a big rip-and-replace thing. How can we build on what you have and get you some very quick returns on this? Palantir's number one on the growth chart at 70%. Google Cloud surged into the number two spot at 63%.

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In this Cloud Wars special report, Bob Evans speaks with Chad Wahlquist, Architect at Palantir, about the company’s explosive Q1 performance and the deeper forces driving enterprise AI adoption. Wahlquist explains how Palantir’s model goes far beyond traditional software, combining forward deployed engineering, ontology, agentic AI, and enterprise infrastructure to accelerate customer outcomes.

AI Infrastructure Rising

The Big Themes:

AI Building AI: One of the most striking themes is the shift from companies building AI products to building AI products with AI. Wahlquist describes a major evolution in enterprise delivery models, where Palantir has moved from “boot camps” to “agent camps,” using AI agents to help rapidly construct customer solutions. This dramatically compresses timelines from projects expected to take months down to days. The deeper implication is that AI is no longer just the product layer; it is becoming the production mechanism itself.

SAP Migration Gets Reinvented: The SAP partnership emerges as one of the most strategically significant parts of the discussion. Wahlquist describes Palantir helping customers accelerate complex ERP migrations, including ECC-to-S/4 transformations, acquired-company integrations, and even mainframe modernization. Traditionally, these efforts consume years and hundreds of millions of dollars. Palantir’s approach uses ontology plus agentic frameworks to interpret structured and unstructured enterprise information, identify mismatches, and automate execution paths. He claims 50%+ time compression in migration work.

Efficiency As Corporate Proof Point: One fascinating element is Palantir’s operating model itself. Evans references Alex Karp’s claim that a company of Palantir’s scale would traditionally employ thousands of salespeople, while Palantir operates with a dramatically leaner commercial organization. Wahlquist argues that product effectiveness changes the equation: engineers demonstrating working systems on customer data become the real sales force. He also notes Palantir internally runs on its own software, using Foundry-based systems for CRM, ticketing, finance, and operations. This creates both operational efficiency and credibility.

The Big Quote: “What I’m seeing here is really the difference between, hey, I’m building AI products to I’m building AI products with AI.”

More from Chad Wahlquist:

Connect with Chad on LinkedIn, or learn about Palantir Foundry.

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In today's Cloud Wars Minute, I examine how AI demand is reshaping rivalries between Google Cloud, AWS, NVIDIA, and Anthropic.

Highlights

00:03 — According to reports, Anthropic has committed to a $200 billion five-year agreement for Google Cloud services and Google-designed chips, a deal that could account for more than 40% of Google Cloud's revenue backlog.

00:18 — This represents yet another escalation in the rapidly expanding partnership between Google Cloud's parent company, Alphabet, and Anthropic, following Alphabet's previously announced $40 billion investment into the company.

00:49 — The company also holds considerable infrastructure deals with providers, including AWS and NVIDIA, and what this deal underscores is the extraordinary scale of demand for AI services. The need for compute capacity has grown so large that even a $200 billion agreement may not be enough to meet future requirements.

01:33 — However, companies like Google Cloud, with the infrastructure required to support hyperscale AI development, are positioned at the very center of this massive transformation.

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In today’s Cloud Wars Minute, I look at how Google Cloud is pairing technical innovation with go-to-market execution to fuel AI growth.

Highlights

00:00 — One of the fastest-growing companies in the Cloud Wars Top 10 is Google Cloud, and it has just launched a program of Forward Deployed Engineers (FDEs), specializing in AI to help accelerate AI transformation at the point of the customer.

00:46 — I had a chance to speak about this new AI FDE program with Matt Renner, President and Chief Revenue Officer at Google Cloud, and he was talking about how this brings the innovation out at the point of the customer, the unique challenges customers are facing right now.

01:38 — It isn't Google Cloud's attempt to get into the services business so much as this is what the demand is from customers now: they need to get their AI capabilities up to speed as quickly as possible to become the AI-powered type of company they're going to need to be.

02:25 — Google Cloud, as I've mentioned before, has always been an on-the-front-edge technological innovator, but over the past couple of years, it's been bringing its go-to-market capabilities and go-to-market innovation up.

03:36 — These efforts are going to be ways to help ensure that customers have the support, the resources, the expertise from Google Cloud and the ecosystem to be able to evolve, innovate, and succeed more rapidly than ever before.

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In this Cloud Wars conversation, Bob Evans speaks with Matt Renner, Chief Revenue Officer at Google Cloud, about the explosive acceleration of enterprise AI adoption and how Google Cloud is scaling to meet it. Renner explains why customers are demanding immediate business outcomes, not experimental pilots years down the road, and shares Google Cloud’s response through expanded field engineering investments, ecosystem funding, and deeper enterprise co-creation. The discussion also explores Google’s differentiated AI stack strategy, the intensifying competitive landscape, and why AI security could become one of the industry’s most significant next battlegrounds.Google’s AI Scaling Play

The Big Themes:

AI Demand Has Moved Beyond Experimentation: Matt Renner makes clear that enterprise AI has entered a fundamentally different phase. Companies are no longer satisfied with proof-of-concept experimentation or exploratory pilots. Instead, executive teams want measurable business value quickly. This urgency is reshaping vendor expectations, deployment models, and customer engagement strategies. Google Cloud is seeing demand at a pace that traditional scaling models cannot satisfy, which is driving operational changes. This is not a speculative future trend, it is already happening.

The $750 Million Ecosystem Expansion Multiplies Capacity: Google Cloud’s $750 million ecosystem investment complements the FDE initiative by scaling partner-led implementation capacity. Renner explains that Google alone cannot meet enterprise AI demand, so partner ecosystems become force multipliers. The strategy is to expand from hundreds of specialists into thousands of technical practitioners capable of building agents, workflows, and AI-powered solutions. This reflects a practical recognition that enterprise AI requires broad execution capability, not just core platform excellence.

The AI Market Reset Is Reshaping Cloud Competition: Renner describes AI as a market reset that is materially changing competitive cloud dynamics. Google Cloud’s growth rates, contrasted against hyperscaler rivals, are presented as evidence that strategic positioning matters. The broader takeaway is that AI has altered enterprise buying criteria, infrastructure priorities, and vendor differentiation. Long-term investments in chips, models, data infrastructure, and platform integration are beginning to show commercial returns. Rather than incremental cloud evolution, Renner presents this as a structural shift in the market. Enterprises are reallocating attention and budgets around AI capability.

The Big Quote: “We’re seeing unprecedented demand for Google Cloud products infrastructure, all driven, frankly, from AI."

More from Matt Renner and Google Cloud:

Connect with Matt Renner on LinkedIn or learn more about Google Cloud AI.

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