Architecting Uncertainty: Designing Reliable Systems on Top of LLMs (medium.com)

A practical playbook called "Architecting Uncertainty" outlines how teams should design reliable systems on top of LLMs, arguing that unpredictability is the primary architectural dimension to manage—not a bug to paper over. The author frames LLMs as a fundamental shift from deterministic code to a probabilistic, language-driven interface that requires new organizational discipline: treat LLM strategy as a board-level concern, prioritize architecture over model size, and build teams that iterate fast, measure continuously, and govern prompts and outputs as first-class assets. Technically, the guide crystallizes a three-tier blueprint: the Prompt Layer (language-as-API—version, test, and monitor prompts to avoid hallucination, prompt debt, and cost blowups), the Agent Layer (small, auditable modular skills for retrieval, validation, summarization—avoid sprawl, enforce data boundaries), and the Orchestration Layer (adaptive workflows, RAG, state management, and centralized compliance—make orchestration explicit, observable, and testable to prevent workflow/RAG drift and state loss). Practical recommendations include layered validation, prompt/version control, strict agent contracts, robust logging, and continuous upskilling. The bottom line: sustainable LLM products come from engineering for uncertainty—resilience, observability, and governance—not from raw model horsepower.