The PoC-to-Production gap
Introduction
Deterministic software vs. probabilistic AI systems
Introduction
The four enterprise killers - cost, reliability, latency, and security
Introduction
Why an LLM wrapper is not an enterprise architecture
An LLM wrapper is not an enterprise architecture because it treats a non-deterministic, third-party AI model as the entire foundation of the system rather than a single, replaceable component. While a wrapper is sufficient for simple, low-stakes automation, enterprise systems require strict guarantees around reliability, security, compliance, data sovereignty, and predictability—none of which a basic API wrapper can provide.
Technical feasibility vs. production viability
In the lifecycle of artificial intelligence and machine learning engineering, a dangerous conflation often occurs between two fundamentally different milestones Technical Feasibility and Production Viability.
AI Production Readiness Maturity Model
To successfully transition artificial intelligence from a novel technical experiment into a predictable enterprise asset, an organization cannot rely on engineering enthusiasm alone. It requires a systematic evolution of infrastructure, risk management, and operational discipline.
AI PoC-to-Production Readiness Scorecard
Moving a generative AI application from a flashy demonstration to an enterprise-grade production environment requires a fundamental shift in architecture. While a Proof of Concept (PoC) answers the question, "Can the AI do this?" production deployment answers, "Can the enterprise operate this safely, predictably, and economically at scale?" Microsoft Community Hub