$CRM and Anthropic Announce Claudeforce "Salesforce and Anthropic are announcing Claudeforce, an expanded strategic partnership bringing Claude’s intelligence and reasoning together with Salesforce’s trusted enterprise harness to make its data, workflows, business logic, actions, and governance securely accessible to power agentic experiences wherever work happens. The Claudeforce partnership launches with Salesforce in Claude, a Plugin with 37 prebuilt sales skills that enable sellers and agents to reason over live revenue context, automate pipeline updates, and take governed action right from Claude — with the power of Salesforce directly where sellers work. The companies plan to introduce more integrations across Claude, Salesforce, and Slack, expanding each company’s use of the other’s technologies." research.alpha-sense.com?doc…

$CRWD CEO George Kurtz says the Mythos moment they flagged in spring, as expected, showed up as a growth driver and tailwind in their results. Technologies addressing rogue AI agents and shadow AI, like AIDR, had a phenomenal quarter, while Cloud, Identity, Next-Gen SIEM, and Endpoint were all accelerating, with exposure management growing given that companies cannot keep up with patching. "So, as we mentioned in the spring, the Mythos moment was building, and as we told you, it was going to be a growth driver and a tailwind for us, and you saw that show up in our results. When we think about AI agents going rogue, when you think about the need for protecting AI and understanding where shadow AI is, it all points to the technologies that we're building and delivering here, like AIDR, which just had a phenomenal quarter. No surprise, obviously, Cloud identity Next-Gen SIEM Endpoint were accelerating and exposure management, which is a big element now given the fact that companies can't keep up with the patching. So when you put all of that together, it comes to what we said the Mythos moment was a point of acceleration and we see those tailwinds continuing."

$SNPS CEO Sassine Ghazi says he is not worried about AI models bypassing commercial EDA tools end to end without their participation, because these models are not static and constantly need to learn and retrain. Accuracy and determinism are essential for autonomous chip design workflows, and customers will not invest hundreds of millions of dollars without confidence it will work. He views this as a significant demand opportunity for their software across training and inference rather than a threat, with Synopsys proactively engaged with customers on building these autonomous workflows. "I don't need to go back or go as far as 10 years ago. You're right around 2017 we introduced and invested and saw great results with DSO.ai centered around reinforcement learning. If you look at the last three years, the focus was around Copilot generative AI move to agents. Right now we're talking about autonomous designs. As you start looking at an autonomous workflow, the most important thing is accuracy and determinism. Customers will not invest hundreds of millions of dollars in a product without having the confidence that it is going to work. The portfolio we have with the sign off leadership is essential to building these autonomous workflows. We are participating with our customers on how to achieve an autonomous workflow. It's not like it's happening without our participation. We're proactively engaged with them to re-engineer how they're looking at the future of engineering with AI being the center of that evolution. I am not worried at all that at some point that model can do the end to end without our participation. Because you have to remember these models are not static. They're constantly changing. They constantly need to learn. So the opportunity is the opposite. It's not a threat. It's a significant demand for our software to train to inference to constantly enable that faster design to deal with the complexity. And we're at the center of it."

$NVDA CEO Jensen Huang says AI agents use roughly 15 to 100 times more compute than a human using the same tools, depending on the problem. Their broader business beyond hyperscale cloud, including sovereign AI, NeoClouds, AI startups, and enterprises, represents about half of their business and is growing 100% a year, which he expects to eventually be larger than what they currently see in cloud. Despite demand being much greater than 70%, supply allows them to confidently deliver 70% growth, which they are guiding to for the first time in order to give customers, shareholders, and the supply chain a consistent view. "As you probably are aware, AI has become useful and the AI agents that are being adopted everywhere use an enormous amount of compute. First of all, the large language models are larger than ever because they're smarter than ever. And these agents go through reasoning and planning multiple, multiple turns of tool use. The amount of compute necessary for an agent versus a human using it is probably 15 to 100 times depending on the type of problem you're trying to solve. And so the amount of compute necessary is just extraordinary. That's a factor that almost everybody sees. The part that people don't see about our growth because we're practically singular, because the nature of how we deliver products, we're the only company in the world that creates and builds, offers an entire AI factory platform, a full-stack system and customers can still mix and match. However, most companies just don't have the skills to do that or desire to do that. And so there's an entire part of the market that we experience growth. There's sovereign AI, the original IaaS, there's NeoClouds there's AI startups, there's enterprises where we're seeing, which represents about half of our business and that's growing 100% a year, that part of the world's computing is likely to be larger over time than even what we're currently experiencing in the cloud. I think the demand that we see is driven by all of those factors. It is also the case that you can no longer procure technology per se and stand up this infrastructure. You've got to go secure the land, power and shell, which oftentimes is a couple, two, three years out. All of the rest of the supply chain necessary to align the construction, the power, the cooling, all of the labor that's necessary. AI infrastructure is creating so many jobs all over the United States and all around the world, it just takes a lot more planning. And so we're involved in securing infrastructure now further down the pipeline. Just as a long time ago people asked me why it is that we're working with memory suppliers when we're a chip company? And today people understand it's really quite genius that we were working on our supply chain so far. Upstream we work with power generator companies, downstream we work with land, power and shell companies all around the world. And that helps prepare all of this computing that's going to be built that will ultimately deploy for our ecosystem and our customers. And so we just have a lot greater visibility now upstream/downstream It is the case that we've never forecasted or never guided to a year in advance. And, even though our demand is much greater than 70%, our supply allows us to confidently deliver 70% and we're going to continue to work with our supply chain to increase on that. But what we wanted to do is to be consistent with everybody from our customers, our shareholders, our supply chain. Everybody sees the same view. And the reason why that's important is because, everybody's putting a lot of resources at play. And so we wanted to make sure that everybody has the same set of information. And we've got a huge year coming up next year and it's going to be pretty extraordinary."