Mixture of Experts (MoE) is the architecture that lets models like Kimi K2 (1T total parameters, 32B active) or Qwen3-30B-A3B (30.5B total, 3.3B active) pay only a fraction of the compute per token without sacrificing capacity. Pedagogical explanation: experts, router, total vs active parameters, why it scales, and the real training and inference tradeoffs you need to know before picking an MoE for your SaaS.

Mixture of Experts (MoE): what it is, how it works, and why it matters in 2026

What Model Context Protocol (MCP) is, why it changes AI integration in SaaS, and when to adopt it in your product. No hype, concrete cases.

Articles about Architecture

Mixture of Experts (MoE): what it is, how it works, and why it matters in 2026

Model Context Protocol (MCP) explained for SaaS founders