Breaking the Bandwidth Wall: Why AI Clusters are Shifting to Ultra Ethernet
To scale past 100k GPUs, the industry is replacing proprietary InfiniBand with AI-optimized Ultra Ethernet.
From the Front Lines of Tech
Sharing strategic insights and lessons from over 20 years of building scalable systems, leading high-performing teams, and navigating complex technology shifts.
Model Distillation: Why a 7B Model Beats a Frontier Model
The fastest way to slash latency is right-sizing models for production classification.
· StrategyThe End of "Tooling": Re-engineering Workflows
Adding AI to existing processes fails; ROI requires embedding AI into the core workflow.
KV Cache Quantization: Fitting Larger Context Windows on Single GPUs
The bottleneck for long-context agents is memory, not compute. Learn how to implement FP8 or INT8 KV caching to double your context length and survive inference at scale.
Context Bloat: Implementing Progressive Discovery in Agent Memory
Using progressive discovery and smart tool-search to keep agents lean. Learn how to prevent context window overflow and infinite reasoning loops in multi-agent systems.
Multi-Cloud GPU Arbitrage: Routing Workloads Between Hyperscalers and Neoclouds
Don't lock into one vendor. Learn how to use an abstraction layer to route training and inference workloads to the cheapest available capacity across hyperscalers and neoclouds.