Anduril Industries is a defense technology company building AI-powered systems for military and national security missions. Founded in 2017 by Palmer Luckey and others, it develops autonomous drones, surveillance towers, underwater vehicles, command-and-control software, and counter-drone technologies. Unlike traditional defense contractors such as Lockheed Martin or RTX Corporation, Anduril follows a software-first model: it invests its own capital to build AI-enabled defense products, then sells finished capabilities to governments, much like a Silicon Valley software company rather than a conventional cost-plus defense contractor. This approach has attracted significant investor interest as military spending increasingly shifts toward autonomy, AI, drones, and software-defined warfare. Its AI platform, Lattice, integrates data from sensors and autonomous systems to help military operators detect, track, and respond to threats in real time. The company aims to modernize defense by combining advanced software, robotics, and autonomous systems into scalable, mission-ready solutions. 2024 revenue: approximately $1.0 billion, according to the company. 2025 revenue: approximately $2.2 billion, officially disclosed by Anduril when it announced its $5 billion Series H financing in May 2026. 2026 outlook: management is reportedly forecasting around $4.3 billion in revenue, although this is a projection rather than reported results. This makes Anduril one of the fastest-growing private companies in the defense sector. Its latest funding round (May 2026) valued the company at approximately $61 billion, placing it among the world's most valuable private technology companies. Here is the history of Anduril's valuation growth 2017: $88M valuation (Seed) 2019: $1.04B (Series B) 2020: $1.92B (Series C) 2021: $4.6B (Series D) 2022: $8.5B (Series E) 2024: $14B (Series F) 2025: $30.5B (Series G) 2026: $61B (Series H) Source: Evan

Not because demand is slowing. Because costs are becoming impossible to ignore. Here are the numbers: 📈 Chinese AI models now process ~18.5 trillion tokens per week on OpenRouter. 🇺🇸 US models? Around 6 trillion. That's a 3x gap. Why? • Lower energy costs. • More efficient models. • Aggressive pricing that's reshaping the competitive landscape. Meanwhile, something interesting is happening inside large enterprises. Companies including Amazon, Walmart, Cisco, Uber, and Meta are reportedly introducing internal limits on AI usage as spending exceeds expectations. One striking example: A software company saw its AI bill jump 7x overnight after moving from a flat-rate subscription to usage-based pricing. Suddenly, the true cost of AI became visible. And this is only the beginning. 📊 Goldman Sachs estimates AI agents could increase token consumption by 24x by 2030. That creates a fundamental challenge: AI demand may keep exploding... while AI budgets become increasingly constrained. The next competitive advantage won't just be building the smartest models. It will be building the most cost-efficient ones. The AI story is evolving: ➡️ From "Who has the biggest model?" ➡️ To "Who delivers the lowest cost per useful output?" The winners of the next AI wave may not be those with the most compute... ...but those who make intelligence affordable at scale. Do you think AI spending is finally reaching a reality check, or is this just a temporary pause before the next investment wave? Source: FT, Global Markets Investors

This scatterplot chart below shows that earnings do matter for AI-themed stocks, but for the rest of the Technology universe, earnings really don't matter YTD. Source: Konstantin Fominykh