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In today's Cloud Wars AI Minute, I examine how GitHub Copilot squads and Claude Code agent teams are changing the way AI agents communicate, collaborate, and solve complex problems. Highlights 00:12— And today, we want to talk about AI coding squads. We're seeing this change about how we're seeing agents being able to go and work on different, really complex projects. And we used to have this one assistant that would go out and everything else, but now we're starting to see teams of agents going and doing things, and we see different configurations of this. 00:54 — So you could have a front-end developer, a back-end developer, an auditor, all of these different things, and they're just basically different personas. And then the beauty of this is where we talk about something like Claude Code subagents, which has been out for a while. This is more the concept of a task agent, where you have a parent that is going to spin off subagents underneath it. 01:34 — Well, when we get into GitHub Copilot squads, we actually see this changing, where what we're having is that each of these different personas are created as members of a team, and the teams work together to be able to come with, like, a common shared team memory and allow them to be able to communicate back and forth, to be able to assign tasks and collaborate and communicate with one another. 02:02 — And this makes it where you end up with a more robust way of actually solving problems, where you're not having to orchestrate it all through a single, a single agent that's supposed to make the decisions on everything. Now you have different personas that can weigh in their opinions and play their role. You can kind of think of it just the same way you would have a human team. 03:15 — But we're going to start seeing more and more of the different AI creators or the different providers of agents starting to take this tack, where they're going to have more of a squad or a team of agents versus having a parent-child relationship, like we've seen in the past. So, something to keep your eye on and pay attention to as you continue to move forward in your AI journey itself. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans speaks with G2 Krishnamoorthy, Vice President of AWS Databases, about how agentic AI is reshaping enterprise data strategies and accelerating business innovation. Krishnamoorthy explains why AI-ready data foundations, knowledge graphs, and purpose-built databases are critical to unlocking the potential of intelligent agents. The conversation explores how AWS customers are dramatically reducing processing times, why forward deployed engineering is transforming technology partnerships, and how security, interoperability, and infrastructure economics will influence the next generation of enterprise AI applications and database innovation. AWS's AI Data Strategy The Big Themes: AI-Ready Data Foundations Drive Innovation: As enterprises embrace agentic AI, establishing a strong data foundation is becoming essential to unlocking sustainable business value. G2 Krishnamoorthy compares agentic AI to a powerful car and the data foundation to the road it needs to travel. Regardless of how sophisticated AI becomes, organizations must ensure their data is accessible, well-structured, and ready to support innovation. Importantly, these investments extend beyond AI applications.Forward Deployed Engineers Accelerate Transformation: AWS is investing in forward deployed engineering (FDE) to help customers translate emerging technologies into production-ready business solutions. Rather than simply providing database products and technical guidance, AWS engineers work directly within customer environments to understand specific challenges, demonstrate solutions, and support implementation. Krishnamoorthy explains that this approach can span cloud migration, data integration, cataloging, contextual knowledge development, and AI-enabled process redesign.Agentic AI Requires Stronger Security Governance: As AI agents gain the ability to perform actions on behalf of users, security and governance become increasingly critical. Krishnamoorthy identifies two major priorities for AWS: ensuring trusted agentic operations and strengthening defenses against emerging vulnerabilities. AI agents must operate within appropriate authorization, authentication, and auditing controls while maintaining the identity and permissions of the users they represent. AWS is working with Amazon Bedrock and AgentCore capabilities to establish guardrails around agentic experiences.The Big Quote: “You need to have the elasticity. You really need to actually be able be truly effortless in terms of managing capacity. You really want to reduce the cost of operations dramatically." More from G2 Krishnamoorthy: Follow G2 Krishnamoorthy on LinkedIn or learn about knowledge graphs and AgentCore Identity. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans speaks with Gary Miller, Oracle Customer Success Officer and Executive Vice President of Oracle Customer Success Services, about how AI is reshaping enterprise operations and customer expectations. Miller explains why businesses are shifting from AI experimentation to measurable outcomes. He also discusses how Oracle is evolving its customer success strategy to help organizations accelerate adoption while managing costs and security. Looking ahead to Oracle AI World, Miller previews Fusion Claw, AI Success Navigator, and new capabilities designed to speed implementation and deliver business value. Industrializing AI for Business The Big Themes AI Becomes a Business Imperative: Gary Miller explains that enterprise AI conversations have changed dramatically over the past year. Rather than simply exploring AI assistants or experimenting with emerging technologies, organizations are prioritizing measurable business outcomes. Competitive pressure is pushing companies to adopt agentic AI faster, rethink workflows, and demonstrate returns on their investments. Miller describes this transition as moving from the democratization of AI to its industrialization, emphasizing repeatability, efficiency, and disciplined implementation.Industrializing AI Requires Coordination: Miller says that industrializing AI involves much more than providing employees with access to intelligent tools. Organizations need structured processes for discovering, deploying, and reusing existing AI capabilities across departments. Without coordination, companies risk duplicating development efforts, increasing expenses, and undermining their expected returns. For large enterprises, the challenge becomes especially significant when thousands of employees can independently create agents.AI Governance Enables Faster Innovation: As companies accelerate AI adoption, security, governance, and cost management become increasingly important. Miller argues that organizations should establish governance structures before deploying agents extensively. These frameworks must define which data agents can access, what processes they can execute, and when human involvement is required. Oracle's embedded governance capabilities within Fusion provide identity management, access restrictions, and operational boundaries that organizations can use as a foundation for broader AI policies.Big Quote: "Do a pilot, get it into production. Many many initiatives fail between pilot and production, and then scale it and learn from that in continuous innovation. So it's building. I call it building the muscle for ongoing innovation." More from Gary Miller and Oracle: Follow Gary on LinkedIn or learn more about Oracle AI Success Navigator, Fusion Claw, and Oracle AI for Fusion Applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Christian Klein is transforming SAP from an enterprise applications leader into an AI-powered cloud powerhouse. Highlights 00:01 — We got some big numbers yesterday from SAP for Q3, and one of the highlights of this, I would say, we see acceleration in its cloud revenue growth, acceleration in its current cloud backlog growth, and also in its cloud ERP suite numbers. So, a powerful quarter for SAP across Q3, and you can really see the evidence here of SAP's ambitious AI strategy starting to kick in. 00:36 — Cloud revenue for Q3 is up 26% to $7.5 billion. Last quarter, I think it was 24% growth. Cloud backlog, 28% to $27 billion. Last quarter, it was 27% growth. Cloud ERP suite up 29% to $6.61 billion. Cloud ERP Suite is a subset of their overall cloud revenue. And the company's total revenue, I thought this was interesting, up 13% to $11.5 billion. 01:08 — Now, certainly its traditional license business is going down. We see the rapid cloud growth pulling the whole company upward. Very, very impressive number there, 13%. Also, SAP announced that its full-year cloud guidance is going to hit what it said will be toward the upper end of the range that the company gave earlier this year. 02:19 — The Autonomous Enterprise, the big new brand promise that SAP announced at Sapphire this year. He said it's gaining customers' confidence. It's trying it in parts. It's feeling more and more comfortable with it. And Klein believes that the Autonomous Enterprise is really starting to kick in with the momentum here. 03:40 — So, as the company gets bigger, its growth rate is increasing — a very difficult thing to do. The growth rates that SAP has been putting up for the last several quarters are much higher than its primary competitors in this category. No other big enterprise — I used to call them apps company, but now we have to call them enterprise apps, agents, data, and platform company — is growing nearly as fast as SAP is. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Google Cloud's $3 million in computing credits could help European researchers tackle some of science's most persistent challenges. Highlights 00:03 — Google Cloud, alongside Google DeepMind, are planning to give up to 200 leading European scientific researchers direct access to Google's frontier models, as well as $3 million in Google Cloud computing credits. The credits are essentially there to ensure researchers have the computing capacity that they need for their research. 00:27 — So, beyond the models, researchers will also have access to some incredibly powerful tools like AlphaFold 3, a well-known tool that helps predict molecular structures, WeatherNext, a weather forecasting tool, and AlphaGenome, which helps researchers study DNA. This is part of a European initiative supporting the EU's AI for Science initiative called RAISE, the Resource for AI Science in Europe. 01:08 — So, there are the obvious geopolitical impacts here. This is certainly going to give the EU's science and technology sector a boost. But for me, this is actually a lot more significant than those potential economic gains. I see this as a really outstanding demonstration of how we can pivot AI towards solving some of the problems that we've been unable to solve without this model infrastructure. 01:34 — Now, I think we've all been promised a great deal in terms of the potential social impact of AI, targeting those really difficult problems, but I think the onus has been on the developers of this technology, the companies, to make those discoveries. For me, this is a much more targeted and scalable approach. 01:54 — Google's committing resources to the RAISE initiative, but the EU is putting the wider framework in place. This, I think, is how we get to the root of some of our most persistent challenges using AI: by not only developing the technology, but also building the structures that enable it to be put to work where it's needed most, and not making it the sole responsibility of the model developers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore why Google Cloud could achieve an astonishing 90% to 100% revenue growth rate in Q3. Highlights 00:03 — We got some big numbers coming out later this week from SAP for Q3, and then next week we've got Google Cloud, Microsoft, ServiceNow, all on October 28 and October 29. Palantir will release its Q3 numbers the first week of November, but let's take a look here at Google Cloud's Q3. 00:25 — I think there's a very good chance the revenue growth for Q3 could be anywhere from 90% to 95%, even 100%. Let me show you the numbers that drive this thought for me. And again, Alphabet will report its results October 28. If we look over the last four quarters at Google Cloud's growth, its revenue, and its quarter-to-quarter incremental growth, which is becoming for me an extremely important metric, here's what we get. 02:00 — To hit 90% growth for Q3, Google Cloud would have revenue of $28.9 billion, and that would require it to grow in Q3 versus Q2 by $4.1 billion. That's a huge stretch, but look what it did in Q2, $4.8 billion. So even if it brings in less incremental revenue this quarter, they could still grow 90%. 02:48 — Now, to hit this 100% number, its revenue would have to be $30.4 billion. That would require an incremental growth, Q3 versus Q2, of $5.6 billion. It's a big stretch, big number, but if you look at the trajectory here of what they've been doing the past few quarters, it is a big stretch, but it is by no means unreasonable, unfeasible. 04:56 — Say Google Cloud grows only 90%. That is still just phenomenal. Twice as fast, at least, as AWS. About three times faster than Microsoft is growing. 95%, 100% — these are astonishing figures for a business as big as Google Cloud's. It shows just how well the number one company on the Cloud Wars Top 10 is doing here. Visit Cloud Wars for more.

00:10 —Microsoft has launched MAI Transcribe to Streaming, a real-time speech-to-text model and Microsoft's first model in the streaming transcription category. The new model has already proven to be incredibly powerful. 00:31 — It operates in 60 languages with continuous automatic language detection, and according to Microsoft's testing, the new model ranks number one for accuracy in both final and partial transcripts. The new model can handle partial text as the speech is arriving, which means reasoning can begin even before a speaker finishes talking, and this is particularly useful for voice agents. 00:59 — Microsoft is also launching two new voice models, MAI Voice 2.1 and MAI Voice 2.1 Flash. Microsoft has positioned this new Flash model alongside MAI Transcribe to Streaming, and I'm just going to read a line from Microsoft AI on that: "Together, they give users the fast and fluid building blocks to create conversational experiences with no compromise on accuracy or voice quality." 01:26 — Ultimately, Microsoft has set the stage here for a complete solution for voice agents. And I'll quote again from a recent Microsoft AI release: "Pairing MAI Transcribe to Streaming with MAI Voice 2.1 Flash buys time back on both ends. The time saved gives your agent more room to reason, use tools, and check its answer, all while keeping the conversation moving at a human conversational speed." 01:53 — The breadth of AI use cases is so massive that we're seeing more and more of this specificity, even from companies like Microsoft that have massive generalized AI toolkits. But to win in the AI era, it's going to take this kind of mastery of specific use cases, not just delivering a catch-all solution. Thank you for watching. Visit Cloud Wars for more.

Bob Evans welcomes Christopher Lochhead, Head Buccaneer at Category Pirates, to Cloud Wars Live, exploring the extraordinary opportunities and challenges emerging from artificial intelligence. Drawing on decades of experience in technology, entrepreneurship, and category design, Lochhead examines the rise of personal AI, the disruption of digital commerce, California's proposed billionaire tax, and growing concerns about AI regulation and corporate accountability. Trust, Technology, and Entrepreneurship The Big Themes Personal AI Emerges as the Next Frontier: Lochhead argues that artificial intelligence is entering a new phase, moving beyond productivity tools toward personal AI assistants capable of managing everyday activities. While early generative AI applications focused on developers, writers, and content creators, the next major opportunity involves systems that understand users' calendars, communications, relationships, finances, and personal preferences. Lochhead identifies Meta's Muse as an early example of this emerging category, potentially positioning the company ahead of Apple and Google.AI Shopping Threatens Traditional Commerce Models: The rise of AI-powered shopping assistants could fundamentally transform how consumers discover, evaluate, and purchase products. Lochhead explains that personal AI systems can already recommend purchases based on individual requirements, compare alternatives, and increasingly complete transactions. This development presents a strategic dilemma for major commerce platforms. He contrasts Amazon's reported decision to restrict Muse's shopping capabilities with Spotify's more open approach to AI-driven transactions.AI Regulation Raises Questions About Corporate Motives: Lochhead delivers a forceful critique of Anthropic and broader AI industry narratives surrounding existential risk, sentience, and government regulation. He argues that warnings about catastrophic AI outcomes deserve scrutiny when the same companies continue developing and commercializing increasingly powerful systems. In his view, calls for strict regulation could also serve commercial objectives by restricting open-source competition and limiting corporate liability.More about Christopher Lochhead and the topics discussed in this podcaast: Connect with Christopher Lochhead on LinkedIn and learn about Anthropic's vision of Claude's character and California's billionaire tax debate. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how CEO Aneel Bhusri is accelerating Workday's AI ambitions and positioning the company to compete with larger enterprise technology rivals. Highlights 00:09 — Workday introduced some very interesting new agentic solutions and innovations this week at Workday Rising, and I wanted to touch on those. And also mention, I think, a very key partnership that Workday has strengthened with Anthropic. It's really going to be part of what I'm calling its all-in commitment to agentic AI. 00:35 — More recently, three big things have really paved the way for Workday's emergence into the AI field in a big time. One was about a year and a half ago, the hiring of Gerrit Kazmeier from Google Cloud. He's now Workday's president of products and technology. He's been a huge proponent for the AI boost. 00:54 — The second thing was about a year ago, the acquisition of Sana for $1.1 billion, and third was early this year, Aneel Bhusri's move from executive chairman back into the CEO role to really push this forward. So a lot of what they announced at Rising this week were the fruits of those developments. 01:18 — First, Sana is now the Workday home. It's a single, sort of wide-open AI experience that's going to run all of Workday's applications, but it also orchestrates the agentic work that's being done, not just agents that ask questions and offer suggestions, but get the work done. 01:39 — Second thing is four new, what Workday calls autopilot agents. You know, playing on the notion copilots help, autopilots actually do the work. So these autopilot agents are in accounting, payroll, talent acquisition, and deployment, where they can help you figure out the right way to handle all these things. 02:16 — Their decision intelligence is a new set of agents working across HR and finance that help model out the best scenarios, all with the grounded, governed data that Workday has. Work Intelligence helps customers figure out the right place to deploy agentic solutions, how to work those, how to get the best ROI from them. 03:12 — Now Workday, being smaller than most of the big ones like Oracle and SAP and Salesforce and Microsoft, has had to use advanced technology and being out on the front edge of these things to remain fully competitive, and to give customers the trust that Workday is going to continue to push them into some of these new advanced areas. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine ServiceNow's launch of Flow and why its rapid deployment and one-click automation capabilities could change employee service management. Highlights 00:03 — ServiceNow has launched Flow. It's a standalone, conversational AI-native service desk designed to handle employee requests through Slack, Microsoft Teams, and email. This means users can bypass those traditional portals and ticketing systems altogether. So, what's Flow? Well, essentially, it's a startup-like offering within ServiceNow, and its big selling point is speed and simplicity. 00:48— ServiceNow says Flow can be deployed in under a day with no infrastructure or implementation project required. Now, importantly, because Flow is a standalone product, customers that don't already subscribe to ServiceNow can still purchase it. ServiceNow says the new service will still deliver, and I quote, "the same reliable results expected from ServiceNow's comprehensive service management portfolio." 00:56 — I think one of the most interesting things about Flow, beyond its speed and remarkably light onboarding requirements, is the way that it works from an agentic AI perspective. It doesn't just answer questions. Once a request has been resolved, users can actually automate the workflow with just a single click. So, if the same issue arises again, Flow can deal with it automatically. 01:26 — It hasn't just built another AI chatbot. Instead, it's turning the service desk itself into an agentic operation. But there's another interesting point here. As Amit Zavery, President, CEO, and Chief Product Officer at ServiceNow, has said, the company is investing where it sees AI-native market opportunities and isn't necessarily trying to replace or detract from its existing business. 01:58 — ServiceNow is offering Flow at no additional procurement costs to its existing customers, positioning it as an alternative or an addition for specific departments, for remote teams, or newly acquired business units that need rapid deployment or prefer a different operating model. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Google Cloud's Gemini Enterprise is delivering remarkable customer outcomes and transforming AI investments into measurable business value. Highlights 00:02 — I wanted to fill in some pretty interesting details about customer outcomes with AI projects from Google Cloud, ones that are using Gemini Enterprise. Got some pretty eye-popping examples of that. These were released last week at the launch of the Gemini agent event, and CEO Thomas Kurian laid out a dozen of these very, very interesting, detailed customer outcome stories. 01:00 — There's the Department of Defense, with three million users now using Gemini Enterprise, and those three million altogether have built 100,000 agents with them. Interesting to see that this is in a highly regulated, highly secure environment, and it's been rolled out and adopted and deployed at that scale, with 100,000 agents being built by those people in the DoD. 01:25 — Commerzbank, document processing costs cut by 30 million dollars with the help of Gemini Enterprise. NTT cut 300,000 hours from document access and retrieval. It said it went from two weeks in most cases to now happening instantly. Grupo Marista insurance firm cut the time for processing hospital claims from 72 hours to four hours. 01:53 — Liverpool, one of Mexico's largest retailers, built a discovery agent, and they built that and deployed it in one week, and they have said now that it is expected to have a 10x ROI on the money that it costs to run that trial. 03:25 — Businesses are using AI here to either accelerate the pace of their operations, to make their people more productive, to cut down on a lot of busy work, get people doing more valuable high-level work, and in many cases, generating new revenue streams, boosting the customer experience that's happening here. 04:00 — If you measure your own company's aspirations and achievements to date with AI against these, are you going to feel happy about that? Are you going to feel kind of like, you know, you're falling behind the times here? I think these are great ideas or great projects here that are going to stimulate a lot of ideas for how others can do things to advantage. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how Gemini agent combines Google Cloud's AI stack, cross-cloud capabilities, and governance to address pressing enterprise challenges. Highlights 00:03 — I think late last week, Google Cloud rocked the whole agentic AI category here with a very interesting development of what it's calling Gemini agent. It spans both the personal AI that we've heard a lot about lately from OpenAI and Grok and Meta, but also, I think much more importantly, the big focus on it is for enterprise AI. 01:39 — This is heavily an enterprise AI product, although it can do those other things. The key is that it sits across Google Cloud's world-class AI stack. That gives it, then, more capability, more flexibility, and better economics for enterprise customers. And in his keynote address, Kurian focused on the affordability that comes now with Gemini agent, the simplicity engineered into it. 02:24 — He said, "The prompt window is the new user interface." Kurian also focused, I think rightly so, on how Gemini Agent, with some of the lakehouse capabilities within Google Cloud, can now work across and tap into data from all the different major clouds, different data stores, applications, tools, and other solutions. 03:00 — A big part of its promise is the ability to work end-to-end across the entire enterprise. They've got to be able to go in and work across different vendors, different applications, and so forth like that. Part of this, then, you can say goodbye to egress fees, which have been a pain in the neck. 04:22 — Customers are saying, "Hey, I'm being pushed inside my organization to do a number of things faster and differently than I've ever done them before, and I need to have tech partners, tech vendors who speak to me in my language about my priorities, my outcomes, and the things that I need to achieve right away." 04:40 —So I think this was just a great launch here by Google Cloud, not only for what the product is able to do, but how that aligns with what customer priorities are. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I examine why Google reportedly shut down its open-source bug bounty program and what the growing problem of AI slop means for enterprise security. Highlights 00:12 — Today, the subject is AI slop and how it's actually just started to shut down security programs. On October 1, we had Google go out and shut down its open-source bug bounty program. For those that don't know, that's basically Google saying, "Hey, submit bugs to us, and if you find really good bugs, then what we'll do is we'll research those, and we'll actually pay you for finding these bugs." 00:54 — What's really interesting about this specific thing is why did they shut it down? Well, it's actually because they have so much slop being produced from AI, where basically a bunch of different vendors or different people are using AI to submit a whole bunch of fake bugs that they're having to triage, and they don't know what to do about it. 01:40 — And so I think this is going to become interesting as the world starts to look at how you start to build these programs and how you open up and identify when you are being served AI slop or fake bounties or fake security audits and assessments versus real ones. 02:09 — So as we continue to move forward, I do expect that we will start to see more and more companies having to figure out how to be able to deal with this particular problem. We might even see new industries pop up that are going to be able to deal with this. 02:49 — We'll keep an eye on it here at Cloud Wars, and we'll keep you up to speed on what's going on. But it's a great thing to be looking at and researching yourself, and identifying where you might even be exposed to AI slop. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Workday is leveraging AI agents to empower employees, streamline benefits operations, and reshape traditional HR processes. Highlights 00:03 — Workday has launched Workday Total Benefits. It's an AI-powered benefits experience that Workday describes as a single, connected experience for employees, HR teams, benefits administrators, and benefits providers. From an agentic AI standpoint, agents can help employees compare benefit plans, understand policies, and make the most of their benefits year-round. 00:34 — And these agents can also take on administrative work that's traditionally made benefits programs costly and significantly complex to run. Workday Total Benefits includes Workday Wellness, which, I'll quote Workday on this, "connects benefit providers directly to Workday, streamlining benefits implementations and automating administration across systems." 01:14 —Looking ahead to 2027, Workday plans to introduce more capabilities, including a Benefits Guidance for Self-Service agent, which will provide employees with what Workday describes as proactive, personalized recaps of the benefits they've used and other ways to optimize them. 01:32 — I think this is a really good example of what Workday is actually doing here, positioning benefits as more than an annual administrative process. It's about continuous AI-driven benefits guidance and automation, and I think it's a really good example of how agentic AI can enable industries to rethink the very basis of how work that may have traditionally followed a very rigid path gets done in the future. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I look at the tension between AI regulation, industry self-governance, and America’s determination to remain competitive in the global AI race. Highlights 00:18 — Some regulatory things happening as the government in the U.S. started to take a look at AI in general. We had six of the CEOs of the major AI providers in the world really, went over to Washington and started talking about how they were going to do self-regulation. Now, the issue with this is going to be that that agreement has actually no penalties associated with it. 00:50 — So, if someone actually breaks the rules, doesn't mean that there's actually any penalties that are going along with this particular situation. And now, the other interesting part is that two of the six are now actually under FTC investigation over consumer risk, and so we have to really ask ourselves: Do we really believe that they're going to properly self-regulate? 01:54 — Now, the other thing is that there is a report that needs to be due to the Trump administration in 120 days. So, what I would tell you is, over the next 120 days, I would fully expect that we're going to get a lot of movement in this space on what are we going to do specifically around AI, which is now also being kind of formed on superintelligence. 02:18 — Now, I believe what they're trying to do here is say that AI governing maybe is not as necessary as superintelligence governing, and they're really kind of trying to draw a line in the sand on the difference between artificial intelligence and superintelligence. And so, I really think this is going to be interesting to see over the next few months what's going to happen in this space. Visit Cloud Wars for more.