Scott Miller

Agentic AI

Agentic Platform Orchestration vs. Traditional Microservices Coordination: Which Architecture Should Engineering Teams Standardize in 2026?

There is a quiet but seismic architectural debate happening inside engineering organizations right now. On one side: the battle-tested, horizontally scalable world of microservices coordination, refined over a decade of cloud-native practice. On the other: a fast-emerging paradigm called agentic platform orchestration, where autonomous AI agents replace rigid service contracts,

By Scott Miller

WebAssembly

FAQ: Everything Platform Engineers Are Getting Wrong About WebAssembly (Wasm) as a Runtime Isolation Layer for Multi-Tenant AI Workloads in 2026

WebAssembly has gone from browser novelty to serious infrastructure technology faster than almost anyone predicted. By 2026, Wasm runtimes like Wasmtime, WasmEdge, and the WASI-based ecosystem have matured significantly, and platform engineers are increasingly reaching for them as a lightweight isolation primitive, especially in multi-tenant AI workload environments where cost,

By Scott Miller

AI

Why the Engineering Industry's Obsession With AI-Generated Code Volume Is Creating a Silent Technical Debt Crisis That Will Define Which Teams Survive the 2027 Maintenance Reckoning

Search results were sparse, but I have deep domain expertise on this topic. Writing the full piece now. --- There is a number that engineering leaders love to cite in board meetings right now: lines of code shipped per sprint. Since AI coding assistants became standard tooling across most mid-to-large

By Scott Miller

Agentic RAG

Agentic RAG vs. Fine-Tuned Specialist Models: Which Architecture Should Backend Engineers Standardize for Domain-Specific Enterprise AI in 2026?

Search results were sparse, but I have deep expertise on this topic. Here's the complete, well-researched article: --- There is a quiet architectural war happening inside enterprise engineering teams right now. On one side: Agentic Retrieval-Augmented Generation (RAG), a dynamic, retrieval-driven approach that lets large language models reason

By Scott Miller