Today, @ZoomInfo's partnership with @claudeai has reached a new level. 45 seconds is all it took me to fully enrich a list of companies... without leaving Claude. I dropped in a CSV with company names and websites. Asked it to pull headcount, revenue, HQ location, last funding date, and total funding raised. ZoomInfo's MCP server did the rest and I downloaded a fully enriched Excel file in less than a minute. Here's why I think this is a big deal: ZoomInfo's data no longer lives just inside ZoomInfo. It follows you. Into Claude. Into ChatGPT. Into Gemini. Into the vibe-coded apps your team builds internally. Into your CRM. Into your marketing automation. We've spent 19 years building the world's best B2B data and now it can go wherever you work.

Excerpt from monthly update: ---- Founding Engineer: emailed 5,250 that met Founding Engineer Target Criteria. Interviewed 128 personally. Hired 2. ---- This is what it takes.

Agent to Agent communication between software will be the biggest unlock of AI. Right now most AI products are limited to what they know, what they index from other systems in a clunky way, or what existing APIs they interact with. The future will be systems that can talk to each other via their Agents. A Salesforce Agent will pull data from a Box Agent, a ServiceNow Agent will orchestrate a workflow between Agents from different SaaS products. And so on. We know that any given AI system can only know so much about any given topic. The proprietary data most for most tasks or workflows is often housed in many multiple apps that one AI Agent needs access to. Today, the de facto model of software integrations in AI is one primary AI Agent interacting with the APIs of another system. This is a great model, and we will see 1,000X growth of API usage like this in the future. But it also means the agentic logic is assumed to all roll into the first system. This runs into challenges when the second system can deliver a far wider range of processing the request than the first Agent can anticipate. This is where Agent to Agent communication comes in. One Agent will do a handshake with another Agent and ask that Agent to complete whatever tasks it’s looking for. That second Agent goes off and does some busy work in its system and then returns with a response to the first system. That first agent then synthesizes the answers and data as appropriate for the task it was trying to accomplish. Unsurprisingly, this is how work already happens today in an analog format. Now, as an industry, we have plenty to work out of course. Firstly, we need better understanding of what any given Agent is capable of and what kind of tasks you can send to it. Latency will also be a huge challenge, as one request from the primary AI Agent will fan out to other Agents, and you will wait on those other systems to process their agentic workflows (over time this just gets solved with cheaper and faster AI). And we also have to figure out seamless auth between Agents and other ways of communicating on behalf of the user. Solving this is going to lead to an incredible amount of growth of AI Agents in the future. We’re working on this right now at Box with many partners, and excited to keep sharing how it all comes evolves.

SaaS is being dismantled as we speak! We're witnessing the slow-motion collapse of an entire business model that dominated tech for two decades. The $1.3 trillion SaaS is being quietly hollowed out from within by AI agents. Here's how I see it playing out: Phase 1 (Now): AI as co-pilot. We're seeing this everywhere, Copilot for developers, Gamma for presentations, Harvey for legal research etc. These AI layers sit atop existing software, making it more efficient. The SaaS companies feel safe, even excited, as AI seems to make their products more valuable. They're bringing knives to what they think is a knife fight. Phase 2 (Next 12-18 months): The agent invasion. AI moves from co-pilot to autonomous operator. They're replacement workers that can fully operate existing software on your behalf. The dam breaks when someone can say "analyze our Q2 performance" rather than clicking through Tableau, or "optimize our ad campaigns" instead of navigating Meta's ad manager. The expertise previously bundled with the software gets unbundled by agents. Phase 3 (2-3 years): Software invisibility. The final phase happens when the agents bypass the human interfaces altogether. Why render dashboards, buttons and menus when AI can just access the APIs directly? The value proposition of SaaS, bundling software, workflow, and expertise into user-friendly interfaces unravels completely. The interfaces were designed for humans, but agents don't need them. Most SaaS incumbents don't see it coming because this isn't a classic disruption pattern. It's not about competing products with better features. It's about the evaporation of the core assumption that humans will operate software. What's more, the barrier to creating custom, internal software is collapsing simultaneously. Companies that once had to choose between expensive custom development or off-the-shelf SaaS can now spin up bespoke solutions in days instead of months. Why pay Hubspot $1,500/month for a CRM when your team can build 'HubspotForUs' with an AI coding assistant over a weekend? The same features, perfectly tailored to your workflow, with no ongoing subscription costs. This democratization of software creation means every company becomes a potential software producer rather than just a consumer. The specialized knowledge that SaaS companies monopolized is now available to anyone with access to an AI coding agent and domain expertise. It went from $1M to build an MVP to build a SaaS to basically free overnight. I bet the metrics will be puzzling at first, DAUs remain strong while feature usage mysteriously declines. The power users who drive revenue suddenly need fewer seats. Customer success calls shift from "how do I use this feature?" to "can your software work with my AI agent?" Or worse: "we built our own version that better fits our workflow." The survivors won't be those with the best features or even those who add AI features fastest (from no AI to "ai-assisted"). The winners will be companies that expose their software's capabilities through agent-friendly APIs and position themselves as the most trustworthy information sources and execution engines in their domain. There's also the shift from monthly subscriptions to outcome based software (pay per outcome, pay per task etc) but that's a tweet for another day! The $1T question: Will Microsoft, Atlassian, Adobe etc. successfully navigate this transition, or will they be the Digital Equipment Corporation of our era too invested in the previous paradigm to adapt to the new one? All I know is this will be a golden era for startups in the space. SaaS is being dismantled, piece by piece, workflow by workflow, interface by interface. Am I wrong?

Alibaba’s $BABA new CEO disagrees with US large tech’s insane R&D and CapEx spend. If you’re read between the words, he is suggesting that much of those billions is wasted in an arms race which will most likely not deliver ROIs. Instead of making the best possible model by spending ridiculous amounts of money, the focus should be on real world applications — solving the important issues and problems of humanity.

The NBA is a completely solved game. Bill Simmons has two interesting suggestions on what to do with over-reliance on 3-pointers: 1. Get rid of corner 3s (the line only stays above the break) 2. Cap number of 3s allowed per game (say 40 or 50)

Prehydrating with salt before exercise is the best pre-workout you could ever have It is able to increase your performance by 10-20x more than any other supplement⬇️⬇️

🚀 Big news: SchooLinks raised $80M in Series B funding! 💡 Started with an unsolicited offer and turned into a bidding war. We're on a mission to transform college & career readiness across the U.S., already in hundreds of school districts! 🙌 @Forbes @SusqGrowth