AI Infrastructure & Agent Protocols
The model gets the attention; the infrastructure decides whether anything ships. Protocols for agents to talk to each other, benchmarking that tells you the truth, inference that doesn't bankrupt you at scale — this is the layer where good AI products quietly succeed or fail.
What we see go wrong is teams optimizing the demo and ignoring the pipeline: no benchmarks, no cost model, no plan for when context grows or traffic spikes. The boring work — measuring overhead, defining interfaces, reducing waste — is exactly what separates a prototype from a production system.
These are the infrastructure- and protocol-level concepts our council generated. They're aimed at the practitioners who know the hard part was never the model.
