OpenAI is losing the enterprise AI race. Sam Altman's defensive response proves it: When Brad Gerstner asked how a $13B revenue company justifies $1.4 trillion in compute commitments, Sam's response was telling. "If you want to sell your shares, I'll find you a buyer." Not an answer. A threat. Meanwhile, the numbers tell the real story. Enterprise LLM API market share: → OpenAI: 50% (2023) → 25% (2025) → Anthropic: 12% (2023) → 32% (2025) → Google: 7% (2024) → 20% (2025) Anthropic didn't waste resources on: • Image generation • Consumer devices • $1.4 trillion moonshots In 18 months, OpenAI went from dominant to second place. But there’s an important detail. While OpenAI burns through billions and Anthropic raises rounds, Google sits on $100B+ in cash. They could price tokens at negative margins forever drowning out both OAI and Anthropic. • OpenAI: Lives fundraise to fundraise • Anthropic: Needs constant capital infusions • Google: Could subsidise losses indefinitely Google doesn't need to win on model quality. They just need to make it unprofitable for everyone else. My takeaway: OpenAI is caught between Anthropic winning on enterprise trust and Google threatening to vaporise the entire business model. Especially when you're spending 100x your revenue and watching your 50% enterprise market share evaporate. Sam says he wants to go public so critics can "short the stock and get burned." At this rate, they might not have to wait long.

NEWS: AI agents will automate 80% of work. But not all agents are created equal. I sat down with Mihir Shukla (Co-founder & CEO of @AutomationAnywh) to cut through the noise. Three types of AI agents exist: 1. Personal productivity agents ↳ Email summaries and basic tasks ↳ Helpful but not transformational ↳ 10-15% productivity gains 2. Captive AI agents ↳ Locked inside CRM/ERP systems ↳ Built-in conflict between savings and sales ↳ 10-15% productivity gains 3. Process agents (the game-changer) ↳ Work across multiple applications ↳ Autonomous or human-assisted ↳ 40-80% productivity gains Process agents don’t just automate existing work faster. They enable work that was impossible before. → Petrobras: AI agent reasoned through complex Brazilian tax laws, saving $120M in 3 weeks → Supply chain: Agent balances inventory 4x daily across 32 warehouses, saving $200M The next 5 years: • New vocabulary: work orchestrators, process reasoning engines • New agentic solutions that don't look like today's apps • Almost every knowledge worker's role will evolve My takeaway: The first two automate tasks within silos. Process agents break silos and transform entire workflows. That's the difference between 15% productivity gains and 80% process transformation. The AI-first autonomous enterprise is being built right now.

NEWS: Adobe just dropped Custom Models for Firefly AI. You can now train Firefly on your own images to generate content that matches your unique style.