Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I break down Microsoft’s evolving AI consumption strategy and how it compares with Salesforce, UiPath, and other major industry players.

Highlights

00:19 — Microsoft just announced the GitHub Copilot harness for Copilot Studio — a really cool new capability that enables an agentic reasoning loop.

00:33 — As part of this release, it said that on September 1, it's going to start charging for consumption on the GitHub Copilot harness specifically. This is an interesting move for Microsoft because 90% of Fortune 500 organizations have actually given developers a way to be able to explore their curiosity and consume this technology

01:12 — To compare and contrast in this space, Microsoft on the GitHub Copilot harness is giving $0, if you use the Copilot Studio standard harness, there's actually free allocation for developers to go play with this. Now, if we compare this to other players in the industry, such as Salesforce, which Agentforce provides 200,000 Flex Credits to be able to come in.

02:05 — What I would tell you is that I'm expecting that this is going to not necessarily be something that will be able to continue in a market where there's a lot of demand. Just to give you perspective, when GitHub Copilot was doing this before, it took about seven weeks for them to realize that there was a problem with this, and they corrected it.

02:50 — This is lining up to Satya Nadella back on July 29th, saying that it's evolving its business model to go beyond per-seat licenses and are leaning into consumption. So, we will continue to see these types of things, and I expect to see other growing pains like this for all vendors as consumption starts to become the new metric.

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In today's Cloud Wars Minute, I look at how Google Cloud is expanding the Gemini ecosystem into the automotive world through its partnership with Mahindra.

Highlights

00:03 — Google Cloud is partnering with the Indian automobile manufacturer Mahindra to get Gemini Enterprise installed directly into its vehicles. That's another interesting example that we're seeing here of AI leaping out of the digital space and becoming something much more physical.

00:23 — In this new development, the automotive agent in Gemini Enterprise is being integrated into MAIA, Mahindra's Artificial Intelligence Architecture platform. Beyond being a voice assistant, Gemini can understand natural language requests and actually interact with a car and its functions.

00:41 — Sashi Sreedharan, Managing Director of Google Cloud India, explained that "by enhancing its in-vehicle assistant with an automotive agent built on Gemini Enterprise, Mahindra is creating personalized and helpful conversational interactions for navigation, search, media communication, and other vehicle controls that will help drivers navigate and explore rich features in a more natural and helpful way."

01:13 — What we're seeing here is pretty significant: AI operating at the edge, with this idea of the digital and physical working together, and the car becoming the AI endpoint. This is also a really important way for Google Cloud to expand the Gemini ecosystem beyond smartphones, PCs, and enterprise software.

01:37 — The real opportunity that I see here isn't necessarily about Gemini as an AI assistant, but where the tech is embedded; it's those all-important endpoints.

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In today’s Cloud Wars Minute, I look at how AI monetization is moving beyond execution and into creation as agentic development becomes more costly and valuable.

Highlights

00:15 — One of the things that I want to talk about today is the meter moving upstream. A lot of this has to do with the fact that what we're starting to see is that the cost that is associated with the actual build process is starting to get really high. And the reason behind that is the concept of an agentic reasoning loop and the cost that's associated with the build process.

01:35 — And what you're starting to see is that the build is actually costing a lot more because of the fact that we're using these different AI models in an agentic reasoning loop to be able to go do the build process. An example of this would be Microsoft starting to charge for the creation of agents inside of Copilot Studio.

02:03 — This is not something that's new in the industry because of the fact that we see other vendors that have tried this across the board. An example is that is exactly what you see in GitHub Copilot and Claude Code. These are definitely going to be tools that are building and being able to execute, and we're seeing a massive amount of adoption in this space to be able to allow builders to be able to build.

02:49 — We definitely are going to see some movement in this space. We're probably going to see each of these different vendors want to compete on who can give the best experience and do it in a cost-effective way. It's going to be very interesting to see how this starts to play in the concept of discoverability of different products and of different vendors.

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In today's Cloud Wars Minute, I analyze Salesforce’s latest results and why Dreamforce could be critical for proving its AI opportunity is here now.

Highlights

00:03 — Salesforce yesterday released its Q2 results, and I'd say that while there's some very good things in there, it's a little bit of a mixed bag relative to what some other companies in its category are doing. But let's take a look at this because I think the big, the big news here, aside from the numbers, is Salesforce announced a huge new partnership with Anthropic.

00:41 — Customers will be able to tap into the power of Anthropic reasoning with their Salesforce applications and agents and data. So I think that offers a lot of potential for the future. But some of the key numbers here: we saw Salesforce revenue go up 11% for Q2, ended July 31. That's $11.3 billion relative to Q1.

01:30 — Its AI and data products—starting to break those out—said they now have an annualized revenue run rate of about $3.85 billion, almost $3.9 billion. It said that's up 210%, and then for Agentforce, annualized run rate of almost $1.5 billion, it said that's up 240%, and this, that.

02:43 — Combine that with the incredible presence of Salesforce applications and agents all over the world, all sorts of businesses. Bring those together. I'm sure for Anthropic, this is great too, as they aspire to become an enterprise powerhouse. The Salesforce partnership and connection here gives them entrée to some huge customers and huge opportunities.

04:21 — It's got to step up the urgency on that, and I think the deal with Anthropic is going to be just the medicine that's needed here for Salesforce. Got a detailed article that'll go into this on CloudWars.com, and we'll be following up more next week with the analysis of what Marc Benioff and others talked about on the earnings call.

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In today's Cloud Wars AI Minute, I explore why falling token prices aren't necessarily making AI transactions cheaper.

Highlights

00:01 — So, one of the things that I want to talk about today is going to be the token economy. And what we're actually seeing is that tokens are about 12 times cheaper than they've been before.

01:30 — But what we're seeing is the average cost of a transaction is actually going up, and that is because of the fact that while token prices are coming down, the amount of tokens it takes to process something is actually going up. We're actually seeing a 520 percent increase in the amount of tokens that you're going to need to have per unit of work.

01:56 — And the reason behind this has been this agentic reasoning loop and the reasoning models that are starting to go and process. As a matter of fact, you're actually seeing that most recently, we've even seen that chat-based things and chat conversations that have happened between humans and agents have actually now, for the first time, started to fall off.

02:30 — So, if this industry trend continues, what you're going to see is that we're going to continue to see this drop. But what we want to see is we want to start also seeing some sort of normalization and drop happening on the average amount of tokens spent on a per-transaction basis.

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