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Higgsfield is the most untold story in tech. $1BN in ARR in 18 months. Faster than everyone other than OpenAI and Anthropic. They spend $4M a month on models. They expect this to be $100K per person per month. They have 150 people working in a content machine. They will breed more millionaires than any other company in Kazakh history. For the first time, @alexmashrabov on the journey to $1BN in ARR. (below) 1. The Power of the Immigrant Founder Coming from Uzbekistan, Alex was pushed into competitive programming at age eight as his single path to reach the United States. For international founders, placing top in global competitions serves as the ultimate social elevator, instilling the relentless work ethic required to build breakout companies. 2. My Biggest Lessons in the Journey to Finding Product-Market Fit @higgsfield burned over $10 million of its $16 million seed round chasing hype and narrative rather than product quality. With under $5 million left, the team pivoted to product-led growth, solving camera control for creative directors, which immediately triggered organic hypergrowth without paid ads. 3. The 150-Person Content Team Powering Higgsfield's Billion in ARR Nearly half of Higgsfield's workforce consists of 150 in-house creative professionals producing tutorials, ads, and cinematic projects. Generating 90 minutes of TV-quality AI video requires 100 hours of raw output, proving human taste and curation remain the primary drivers of distribution. 4. We Spend $4 Million per Month on Models Higgsfield spends $4 million monthly on internal model usage, averaging $10,000 per employee so teams can freely vibe code and test workflows. Uncapped inference compute acts as a force multiplier, allowing top talent to discover breakthroughs at maximum velocity. 5. Why Chasing Benchmarks Is Bullshit and the Corporate Misalignment Occurring Public benchmarks have devolved into corporate psyops where lab researchers overfit test data to secure bonuses before job-hopping. Text-to-video benchmarks ignore real production workflows requiring 3,000-word prompts, proving direct customer iteration beats artificial leaderboards. 6. Why Team Sizes Won't Be Impacted as Much as People Think While AI handles over 60% of basic support requests, complex B2B environments cannot eliminate human teams. High product velocity constantly shifts rules and context, requiring smart, coordinated operators across legal and customer success. 7. Americans Are Way More Promiscuous When It Comes to Leaving Companies Silicon Valley workers routinely jump jobs every two years, prioritizing short-term trends over deep commitment. This transactional market gives international hubs an advantage, where cultural loyalty and team stability build compounding technical moats. (links in comments)

Many schools today hold smart kids back. They’ve eliminated gifted classes to address “historical inequity.” “This is so misguided,” says @MichaelPetrilli, of @educationgadfly. We show how that hurts ALL kids:

With @Cybertruck, we introduced & scaled many automotive firsts 48V architecture: 4x lower current that enables thinner, lighter wiring True Steer-by-Wire with no mechanical steering link, enabling variable steering response Combined with rear-wheel steering, this also brought coordinated front + rear steering for greater low speed maneuverability & high speed stability Structural stainless-steel exoskeleton: allows exterior panels to carry structural loads, resulting in far higher torsional stiffness Full-hard stainless air bending: forms ultra-hard exterior panels without damaging the visible surface Etherloop: gigabit vehicle network that eliminates ~70% of cross-vehicle wiring

Everything you need to master in 2026 to get rich: • Using Astra 6 high for planning, low for execution • Grok Bot to manage day to day • Coding loops • Taking advantage of Codex's computer use • Herdr to manage tons of agents • /goal • Running local models • Karpathy's Autoresearch • Building an X audience • Creating videos • How machine learning works • How databases work (been using Convex) • Using API's • Training your own LoRAs • Elimination of doom scrolling • Most importantly: focus

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