Cursor didn't win by having the best AI.
It won by obsessing over one leverage: developer experience.
Most startups spread resources across product, marketing, and sales.
The best ones find one advantage and compound it relentlessly.
https://t.co/0dv7oloDVw
Do you know your model's license?
MIT → no restrictions Apache 2.0 → permissive + patent protection Custom (Llama, Mistral) → commercial limits, MAU caps, attribution rules
Most teams check benchmarks. Before using a model in production, always check the license.
Cascading: begins with cost-effective model; escalates if confidence is low. Pays sequentially. Better for unpredictable workloads. Production uses both.
Running everything on GPT-5.5 or Claude Opus when you should route to DeepSeek is the operational equivalent of hiring a cardiac surgeon to change a bandage.
The cost differential is approximately 34x. Here is how to build an AI router that selects the right model automatically.
Two distinct patterns. Do not conflate:
Routing: upfront classification followed by direct execution to the selected model. One decision, one invocation. Lower latency. Requires precise classification.