From the blog
Insights on AI agents, MCP servers, and building software for the AI era.
The Thinking Dial: How AI Models Are Learning to Know When to Reason
The latest AI models no longer apply the same depth of reasoning to every problem. A new wave of research and API controls — adaptive thinking, effort parameters, hybrid thinking modes — lets models calibrate cognitive effort to task complexity. Here is what that shift means for your costs, latency, and product reliability.
The Inference Paradox: Why Your AI Bill Keeps Rising as Token Prices Fall
Token prices have fallen 280x in two years, yet enterprise AI budgets exploded 480%. Gartner, Deloitte, and FinOps data explain the paradox — and how to escape it.
The 68-Point Gap: Why AI Agents Stall Before They Ship
79% of enterprises have adopted AI agents in some form. Only 11% have them running in production. The 68-point gap between those two numbers is the most consequential story in enterprise technology right now — and the cause is not what most people expect.
Physical AI: The Sim-to-Real Breakthrough Has Arrived
In March 2026, Ai2’s MolmoBot achieved a 79.2% success rate on real robot tasks — trained entirely on simulation data, with zero real-world demonstrations. NVIDIA’s GR00T N2 arrived the same week. A quiet threshold has been crossed.