Imagine you’re running a shipping company. You’ve got the trucks. You’ve got the warehouses. You’ve got a fleet management system that tracks fuel consumption down to the liter. But every time a customer wants to ship a package, they have to walk into the warehouse, find a truck driver, negotiate which vehicle to use, and […]
Your AI Stack Has a Missing Layer (Here’s What It Costs You) Read More »
Imagine hiring a Nobel Prize-winning mathematician to sit in a restaurant and calculate a 15% tip on a $40 lunch bill. They would get the answer right, certainly. But you would be paying hundreds of dollars an hour for a task that a $5 pocket calculator could do instantly for free. This sounds absurd, yet
Model Arbitrage: Why You Shouldn’t Use GPT-5 for Everything Read More »
In the current landscape of Large Language Model (LLM) development, we are witnessing a frenetic “feature race” centered on one specific metric: context window size. A year ago, 32k tokens felt revolutionary. Today, providers like OpenAI, Google, and Anthropic are normalizing windows of 128k, 200k, and even 1 million tokens. For AI engineers and architects,
The Hidden Cost of Context: Why You’re Paying Too Much for Data You Don’t Use Read More »
