THE NEW MAG 7 OF AGENTIC AI Stage one of AI was all about hardware -- servers, GPUs, and the scaffolding. Stage two is applications: embedding intelligence directly into the workflows, infrastructures, and physical systems that run trillion-dollar economies. This is where true economic capture happens. And it’s where a different Mag 7 is emerging -- not just $GOOGL, $MSFT, $NVDA, $AMZN, $META, $AVGO, or $TSM, but the companies that already have AI moats deep enough to withstand the flood. They’re the platforms that have already built vessels for the storm. The Operating System of AI $PLTR has become the execution layer. AIP carries out decisions, orchestrating resources, policies, and workflows across fractured systems in real time. In defense, that means coordinating logistics, surveillance, and supply across thousands of nodes with no human lag. In energy, it means balancing grids dynamically against weather and demand. Once embedded, AIP becomes the nervous system of the enterprise, wired into procurement and compliance in ways that make removal not just costly, but catastrophic. Last quarter underscored this: revenue passed $1B with 48% YoY growth, U.S. commercial nearly doubled, bookings surged past $2.3B, and government wins extended from Army to Space Force to Maven Smart. The Gatekeeper of the Modern Internet $NET is building the execution moat for agentic AI at the edge. Agents need to talk to the real world -- APIs, websites, networks -- and Cloudflare already mediates 20% share of global traffic. That position makes it the enforcement layer. Workers AI allows inference at the edge, Zero Trust secures the surface, and emerging pay-per-crawl models flip economics so that as agents scrape the web, the web itself monetizes. Whoever controls the traffic path sets the rules of engagement. Cloudflare doesn’t need to own models -- it owns the choke points between models, agents, and the internet. The Guardian of the Cloud Era $CRWD moat is a budgetary lock-in that scales directly with agentic activity. In an AI-driven enterprise, every autonomous action expands the attack surface. CrowdStrike isn’t just defending endpoints anymore -- it’s selling a control plane for machine-speed security, where ARR expands in lockstep with workload growth. Net new ARR re-accelerated to $221M, Charlotte AI’s ~85% sequential growth validated OPEX savings from automated triage, and Falcon Flex made ARR expansion usage-led. Falcon Cloud now contributes ~$700M ARR, extending dominance into runtime -- where autonomous software actually operates. Security here is a compounding flywheel, and CrowdStrike owns the rails. The Foundation of AI Data Liquidity $SNOW has positioned itself as the liquidity layer. Agents don’t just need training data -- they need governed, queryable, cross-cloud streams they can act on. Enterprises are consolidating on the Data Cloud, not scattering across silos: 125% NRR has returned, RPO backlog hit $7B, and $MSFT Azure channel growth is ~40% YoY. Cortex AI SQL and OpenFlow (~6,000 weekly active accounts) give agents a native language to reason over enterprise data. Once wired into production workflows, Snowflake becomes the substrate agents breathe through -- removing it would suffocate systems already running. The Database of AI-Driven Applications $MDB has turned Atlas into the memory plane. The open-source “commoditization” bear case has flipped -- open source became the funnel, and now enterprises are committing wholesale. Deutsche Telekom shifted billing for ~30M subs, an automaker migrated ~8.5M vehicles, all because agentic apps demand retrieval quality, vector embeddings, and streaming writes inside one substrate. Atlas collapses operational and retrieval into a single stateful memory -- the layer agents recall and update in real time. Once that’s in place, nothing else can hold state and recall at scale, making displacement very difficult. The AI Network for Mobility & Robotics $TSLA is the only one fusing digital and physical moats. Dojo trains the models, the fleet provides inference at scale, and early robotaxi pilots carve the regulatory path. Autonomy in physical space requires a vertically integrated data flywheel, and Tesla has it. Energy is the second leg: Megapacks integrate into grids where agents balance electrons. Optimus shares the perception stack with vehicles, turning mobility advances into robotics progress and vice versa. Tesla’s autonomy stack is unique because it runs on real-world data across mobility, energy, and robotics at global scale. The Control Center for Public Safety $AXON has transformed public safety into an AI-native platform. Tasers and body cams distribute the hardware, but Evidence_com and its software ecosystem create institutional lock-in. Agencies legislate around the platform, making it the de facto operating system for video, case management, and real-time dispatch. Once AI upgrades video comprehension and response, the moat only deepens -- because you don’t rewrite laws or retrain forces to swap vendors. Final Thoughts That’s what it means to have an AI lifeboat: not surviving the storm, but consolidating power as autonomous agents reshape budgets, networks, institutions, and the physical world. Stage one rewarded those who sold GPUs to the model rush. Stage two rewards those controlling the points where agents plug into reality.