Table of Contents

• 1. Alphabet (GOOGL) – Head of Cloud Thomas Kurian …

• 2. SentinelOne (S) – Co-Founder/CEO Interview with …

• 3. Zscaler (ZS) – CEO & CFO Interview with Goldman …

• 4. Uber (UBER) – CEO Dara Khosrowshahi Interviews …

• 5. Microsoft (MSFT) – CTO Interviews with Goldman

• 6. Credit-Related Interviews – Mastercard, Visa, J …

• 7. Adobe (ADBE) – Earnings Snapshot

• 8. Macro Data

During the week, I published Shopify, Airbnb, MercadoLibre and Nvidia investor conference reviews along with Celsius and Starbucks news. I also published PayPal, Amazon and SoFi investor conference reviews along with an Oracle earnings snapshot.

I plan to cover the Oracle and Adobe quarters in more detail and a few more interviews from this past week’s Goldman Sachs conference next week. Some of that coverage will include AMD, ServiceNow, Datadog and MongoDB. I continue to work on the upcoming SoFI Investment Case refresher.

1. Alphabet (GOOGL) – Head of Cloud Thomas Kurian Interviews with Goldman Sachs

5 Categories of the GenAI Opportunity for Google Cloud:

Kurian spent the bulk of this event offering investors an insight-packed overview of the cloud business. The presentation was split into GOOGL’s 5 GenAI offerings, which all sit on the Vertex AI platform.

GenAI Category – Infrastructure:

Starting with the bottom infrastructure layer, Alphabet offers a series of chips, switches and memory bandwidth optimized for its cloud environment. Kurian was also quick to remind investors that this cloud business offers 70x the liquid cooling capacity (new new data center technology replacing/supplementing air-cooled) vs. any other hyperscaler. 

The company takes a similar approach to AWS on chips. It’s investing heavily in the category, with its latest 6th generation Tensor Processing Units (TPUs) offering 3x performance and 2.5x inference cost lead vs. competitors for some specific workloads. At the same time, the search giant openly partners with best-in-class GPU players like Nvidia and AMD to let customers use whatever hardware they want within the cloud environment. There’s some real evidence of the company beginning to flex its muscles in GenAI hardware. 90% of all AI unicorns use GCP for model training and inference, while 60% of all AI startups and large incumbents like Ford do as well.

GenAI Category – Developer Tools:

The next category is developer tools. The firm aims to give developers all of the support they need to connect AI models (such as Gemini or models from partners such as Anthropic) to enterprise systems for eventual app and agent creation. Ultimate model choice lets developers and enterprises standardize on Google Cloud Platform (GCP) regardless of which tool works best for them. Again, client choice and avoiding vendor lock is a powerful way to create more open, valuable and sticky cloud contracts. If developers don’t have what they want, they’ll just go somewhere else. 

GCP also supports a wide range of model services. For example, its model grounding tool vets query accuracy, with adaptive grounding to prioritize which responses actually need double checking. That’s a big cost saver for companies. It also features model distillation capabilities to shrink massive parameter models down to smaller, task-specific models for clients like Samsung. All in all, 2 million developers are now building with its cloud-native, AI platform. 45% of these projects, with the help of system integrators like Accenture, are now live and ramping usage.

GenAI Category – Data Analytics:

The next category is data analytics, which is an imperative complement to GenAI models and apps. As I frequently say, competing models can stand out from the size and relevance of the datasets they’re trained on. Knowing this, GCP (like both AWS and Azure with its Vertex debut) takes a fully open approach here. Customers can connect any data source (structured, semi-structured and unstructured) to GCP with “super low latency.” From there, it offers dynamic data agents/assistants for conversational querying, optimal data migration, visualization, insights and spreadsheet building. As a result of all of these tools, machine learning query volume for Big Query (how it monetizes) is up 80% year-to-date. The agents should also, per Kurian, drive more subscription seat growth, as it lowers the barrier to conducting complex, multi-modal data analytics.

GenAI Category – Security:

The next piece of the opportunity is in security. This category is not only a separate growth vector, but a place where GCP can showcase some self-proclaimed advantages to drive customer trust and broader GCP adoption. For example, it sees 75% lower downtime rates vs. competitors and 50% lower vulnerability rates vs. “other clouds.” 

Mandiant, its threat hunting arm, helps collect threat intelligence from Google’s gigantic databases. Its traffic is rapidly growing, per Kurian. Mandiant also prioritizes threats, tests existing system configurations, flags issues and tells you exactly where you will probably be attacked while even writing the audit file for the case. This greatly helps in expediting remediation. 

GenAI Category – Apps:

Finally, we have GenAI applications. The company is actively lacing in GenAI tools like content creation, text summaries, translation and customer service automation to uplift the overall value of Google Workspace. One hospital system is using these tools to manage bed throughput and save $250 million per year in costs; Techniker Krankenkasse (largest health insurer in Germany) is using GenAI Workspace tools to cut claim handling from about 25 minutes to 3 seconds. 

While GenAI is deeply integrated into its established Workspace suite, Alphabet is also building new GenAI apps in areas like customer service. Many companies are doing the same thing, but Kurian sees their offering as best-in-class in a few areas. First, it can handle traffic from web, mobile, call centers and brick-and-mortar environments. Next, Kurian sees this product as world-class for answer accuracy rates, which is especially important for regulated sectors like healthcare and banking.

Kurian is determined to create the best environment out there for developers to build their own GenAI apps. For evidence of this objective being in reach, 75% of independent software vendors (ISVs) work with GCP for AI.

GenAI Go-To-Market:

Kurian got the same batch of questions that AWS’s Garman got earlier in the week. It’s notable how frequently their answers were nearly identical. On go-to-market changes for GenAI, GCP is acting identically to AWS. It is focused more on “selling outside of the IT organization” to customer experience, marketing, financial and other teams based on the specific use case. It’s focused on training its teams to specialize by industry and stress the points of tangible value creation and short payback periods. Secondly, and also like AWS, it’s dedicated to building the exact solutions that customers want to diminish onboarding friction and pace of GenAI adoption.

• SIs like Accenture have doubled their roster of employees certified on its AI systems in the last year.

2. SentinelOne (S) – Co-Founder/CEO Interview with Goldman

Architecture:

Since the CrowdStrike outage, conversation surrounding technological architecture for security platforms has been front & center. CrowdStrike prides itself on the ultra-light weight agent, real-time data streaming and fantastic 3rd party review scores. But SentinelOne’s scores are also excellent, and it thinks its approach is actually better. CEO Tomer Weingarten got an immediate question about SentinelOne’s somewhat heavier, more algorithm-packed security agent compared to CrowdStrike.

In his mind, it’s not about the weight of the agent, but how lightweight SentinelOne actually is in terms of touching a client’s kernel (the most sensitive, core part of its operations). SentinelOne touches the core far less frequently and intensely than CrowdStrike and requires fewer software updates too. To the company (and intuitively), not touching the kernel materially diminishes the risk of its own software or algorithm updates leading to breaches of these all-important cores. It has created a work-around in Mac and Linux (not yet a Windows option) to emulate the data and insight produced by a kernel to learn from it and shield it without getting in its way. Bright people in the industry will subjectively argue about which approach is better than the other.

• At this week’s Windows Summit, a large portion of the chat focused on how to limit kernel access and improve security. The overarching takeaway is that there will be incremental policies and controls added to make kernel access more strict, rather than eliminating that access altogether.

As Weingarten candidly said during the call, no platform (in any part of security) is perfect for every need. It’s about which batch of strengths and weaknesses are the most compelling for an individual deployment. SentinelOne finds itself being the most compelling more times than not; CrowdStrike would invariably say the same thing. In reality, they both should continue to find profitable growth within the massive, growing sector.

Go-To-Market:

SentinelOne, like Zscaler and so many others, has been hard at work on revamping its go-to-market approach. It’s pushing to tighten relationships with channel partners and bringing in proven talent to usher in the next several years of growth. As part of this, it recently made another c-suite change by bringing in Barbara Larson as its new CFO (recently hired a new CMO and CRO too). Larson previously served as Workday’s CFO and the Senior Director of Field Financial Planning at VMWare.

This change is a response to SentinelOne’s ramping size in markets. It wants to “switch gears for how it grows scale” to push its revenue base across $1 billion and well beyond. It thinks it needs a “tremendous financial leader” to do that, and sees Barabara as the person. The praise for Larson can also be taken as a bit of shade thrown at outgoing CFO David Bernhardt. Considering this and SentinelOne’s issues with accounting in previous years, it’s good to see Bernhardt staying on with the company for another year to ensure a smooth transition. Furthermore, during the interview, Tomer told investors that this decision has been in the works for a long time. This wasn’t sudden or a response to any internal issues.

Competitive Landscape Following the CrowdStrike Outage:

There was a bit of investor disappointment from not getting a large upward guidance revision last quarter amid CrowdStrike’s issues. We have to remember that this only happened 8 weeks ago and the situation is highly fluid.  SentinelOne was not ready to assume what that benefit would be last quarter, so elected to forgo doing so. This could lead to compelling outperformance in quarters to come. Tomer told investors that they should be ready to quantify the financial impact next quarter. SentinelOne does expect a concrete benefit from this outage, and is already seeing pipeline favorability along with rising win and close rates. 

The firm sees many customers forgoing more workload growth with Falcon to invest more resources in SentinelOne. This joint coverage is routine in network security, and should become more popular following this summer’s outage.

Somewhat surprisingly, SentinelOne isn’t getting that aggressive on pushing customers to displace CrowdStrike. It’s simply trying to be there for customers and help in any way it can. This, it thinks, is what will maximize the positive impact of its competition’s mistakes.

Tomer talked about the idea that SentinelOne has led in MITRE evaluations for four years, yet still doesn’t see other companies or the market fully embracing that reality. Why? Because SentinelOne’s marketing budget is a small fraction of Microsoft's, CrowdStrike’s, Palo Alto’s, etc. It sees the most discerning buyers picking its product over the others, but also sees a lot of market confusion driven by (it thinks) false claims from competing products. 

Step one for SentinelOne accelerating its own marketing engine was inflecting to profitability. That’s now in the rearview mirror. The more important step two will be reaching annualized profitability. This should be in Q2 or Q3 of next year and is when it plans to really lean in. It doesn’t struggle with great tech; it struggles with go-to-market. A lot of that struggle is due to lacking resources to drive awareness and it’s now building the war chest needed to alleviate this growth bottleneck.

It has grown from 1% market share to 5% in a few years with a small fraction of the cash to drive awareness. Imagine what it can do as it becomes capable of more meaningfully spending budget here.

The Future Cross-Sell Opportunity:

SentinelOne remains primarily focused on new customer wins. It is readily launching products across cloud and data security, and it has rounded out its platform quite a bit over the last couple years – organically and via M&A. Still, the opportunity for new customers remains the most promising. And? It merely gives SentinelOne more opportunity to drive more cross-selling growth down the road with what it views as best-in-class products.

Cloud Security Opportunity:

SentinelOne’s main focus in cloud security is on runtime security, rather than Cloud Security Posture Management (CSPM). It sees CSPM as largely commoditized and has a product that it’s even considering offering for free in a bundle with other tools. Runtime security (like cloud workload protection (CWP)) is really where it thinks it can stand out. The market is highly fragmented and ready for the taking. 

3. Zscaler (ZS) – CEO & CFO Interview with Goldman Sachs

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