Architecture and Retrieval
The patterns that distinguish production AI from demos.
Topic
How enterprise AI systems are actually built, patterns, anti-patterns, and reference architectures observed in production.
The patterns that distinguish production AI from demos.
By 2026, enterprise AI systems are no longer differentiated primarily by which large language model they use. The frontier models, Anthropic's Claude Opus 4.7, OpenAI's GPT-5.2, Google's Gemini 3 Pro, are converging on capability for the median enterprise workload. What separates production-grade s
The most consequential layer of the AI buildout is not the foundation models themselves but what sits between them and the organizations that deploy them: architecture, integration, evaluation, and governance. The public record has clarified the picture rather than settled it. The applied layer is
The editorial spine of the publication. What production AI actually looks like, and how the discipline matures over time.