

Rack-Scale AI Design: The End of Component Scaling
We have hit the physical limits of what a single chip can do. The new unit of compute for AI infrastructure isn't the GPU; it's the fully integrated rack.


We have hit the physical limits of what a single chip can do. The new unit of compute for AI infrastructure isn't the GPU; it's the fully integrated rack.


TTFT reveals the real bottleneck in LLM inference. Learn why Time To First Token matters more than average latency, and how to separate prefill vs decode.


How to manage the shared state size in complex reasoning loops to prevent context window overflow without losing critical history.


Class-based chains are a legacy pattern. Discover why Google ADK and its open Agent Protocol are the future of interoperable, production-grade multi-agent systems.


Agents are stateless. Their memory is not. Scaling the LLM reasoning loop is trivial compared to solving the transactional concurrency of agent memory on Kubernetes.


Why Agent-to-Agent (A2A) interactions and Side Effects require a 'Two-Phase Commit' for safety.