Was thinking about this over the weekend. What if LLMs were Italian food? Let me know what you think of the list (but remember you're arguing with an Italian). ChatGPT → Margherita Pizza The crowd-pleaser. Gemini → Lasagna Built with data layers (Search, YouTube, Android, etc.) Claude → Osso Buco Slow-cooked, meticulous, and expensive. Grok → Spicy 'Nduja Loud, punchy, sometimes TOO punchy. DeepSeek → Cacio e Pepe Simple ingredients, hard to make, shockingly good. Llama → Family-Style Antipasto Platter Open and shareable. Kimi → Tiramisu New on the menu and winning fans over fast.

the @kong AI gateway 2.0 is a piece of art. Not only it scales to quadrillions of token without missing a beat but has the best policy management in the industry. Of course all you see here is usable headless via API and CLI. Try it out 🦍

3 root causes of "The AI Fragmentation Tax" 1) Visibility is fragmented: About half of companies don't track LLM API costs at all, even when AI is core to the product. 2) Forecasting is broken: Only 15% of companies can predict AI spend within ±10% accuracy, which makes budgeting and margin protection nearly impossible. 3) Infrastructure is sprawling: Agents, MCP servers, LLMs, APIs, and event streams all connect across on-prem, cloud, and hybrid environments. Every touchpoint generates cost that's invisible in isolation but huge in aggregate. Even companies not integrating AI into their product directly are still heavy consumers of third-party LLMs, so they add cost with no measured revenue to offset it. The fragmentation tax compounds the longer it exists. Every release cycle makes it worse if you don't address the 3 root causes. That's why we're obsessed with building a unified cost governance layer for our customers. As AI speeds up the convergence of many capabilities, margin discipline becomes a differentiator.