OpenAI just restructured everything. Everyone's talking about the $130B Foundation equity and Microsoft's 27% stake. But here's what technical founders are missing: The real game changed when they said "open weight models" are now possible. Think about it. OpenAI Foundation keeps board control. Microsoft gets API exclusivity until AGI (verified by an independent panel, whatever that means). And now OpenAI can release models meeting safety criteria into the wild. Meanwhile, GitHub dropped Agent HQ. VS Code ships with Agent Sessions. LangChain launched Deep Agents 0.2 with filesystem abstraction and context compression. The infrastructure shifted. Agents aren't experimental anymore. They're going first class. Simple as this 👆 Here's what nobody's connecting: > Cartesia raised $100M for Sonic 3 with 90ms model latency and 42 languages > NVIDIA released Nemotron Nano 2 VL for document and video understanding > IBM's Granite 4 Nano outperforms models twice its size > vLLM added Sleep Mode with 18 to 200× faster model switching The pace isn't slowing. It's compounding. But scroll through X and you'll see the same pattern: founders celebrating tools while burning out managing the context those tools create. Grok now summarizes trending AI news in real time on X. You can get the full week's releases in 30 seconds. Speed went up. Signal to noise? That's still on you. So here's my question for technical founders building with AI: Are you designing your stack for leverage, or just adding more tools that need babysitting? Because the companies winning right now aren't the ones with the most AI agents. They're the ones who figured out which problems agents actually solve versus which ones still need human judgment. What's your take? Are agents giving you more leverage or just more things to manage?