From Tutorials to Production: Architecting Reliable AI Systems

The gap between hello-world-level AI tutorials and production systems is vast and often underestimated until the first incident occurs. Successful LLM production systems demand upfront investment in architectural foundations—context versioning, prompt tracking, asymmetric failure mode design, and audit trails—not as optional safety measures but as essential design decisions. Teams that defer these choices face operational crises at 2am and months of costly remediation.