Systems | Development | Analytics | API | Testing

Most AI revenue will flow through tokens — and the two bottlenecks are tokens per watt (energy cost) and tokens per second (throughput). Tokens per watt determines how much output you can generate from a fixed energy supply — already constrained and getting tighter. Tokens per second sets the ceiling on how fast that revenue can flow. Kong's AI Gateway optimizes both at the connectivity layer: semantic caching and semantic routing increase token output without adding watts or latency.#Shorts.

What if you did not have to open a dashboard, read the charts, and figure out what the numbers mean? What if you could just ask a question and get the answer in plain English?

LLMs are absorbing the business logic of microservices for agentic use cases — but both patterns will coexist in enterprise infrastructure for a long time. Cloud-native infrastructure (microservices + APIs) keeps powering web and mobile experiences. The agentic layer — LLMs, MCP tool calls, and context traffic — runs in parallel, activating the same APIs and CRUD operations underneath. Kong manages both swim lanes: the API traffic between clients and microservices, and the context traffic flowing between agents and LLMs.#Shorts.