The Agent Supervisor Pattern: Why Your Mesh Needs a Boss
Autonomous agents are prone to infinite reasoning loops and 'democratic' indecision. We explore the Supervisor pattern in LangGraph, MCP, and why orchestration beats choreography.
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.
MoE Routing Collapse: When Your Specialists Stop Specializing
A model is only as smart as its router. We explore the physics of expert zones, the tax of token dropping, and how to keep your load balancer honest.
· StrategyThe Build vs Buy Trap for Foundational Models
You are not Google. Your moat is your data, not your ability to pre-train Llama-4. We dissect the math of architecture parity and the rise of Outcome-as-a-Service.
· StrategySpot Market Arbitrage for AI: The Economics of Fault Tolerance
If your training loop isn't fault-tolerant, you're paying a 40% 'insurance tax' to your cloud provider. We look at the architectural cost of 30-second preemption notices.
Visualizing All-Reduce Bandwidth: The Physics of Distributed Training
When your model doesn't fit on one GPU, you're no longer just learning coding-you're learning physics. We dive deep into the primitives of NCCL, distributed collectives, and why the interconnect is the computer.
· StrategySqueezing the Inference Lever: The Economics of LLM Throughput
Inference price isn't a fixed cost-it's an engineering variable. We break down the three distinct levers of efficiency: Model Compression, Runtime Optimization, and Deployment Strategy.