Beyond the Model
The foundation study for the five-pillar programme — why the applied layer decides enterprise AI outcomes, and what the evidence proves, falsifies, and leaves open.
Monthly to bi-monthly
Research Reports are the publication's flagship output. Each report is a definitive reference on a specific question enterprise technical leaders are trying to answer, typically 4,000 to 10,000 words, with sections, figures, and references.
The foundation study for the five-pillar programme — why the applied layer decides enterprise AI outcomes, and what the evidence proves, falsifies, and leaves open.
Patterns that distinguish production from demo — why the architecture wrapped around the model, not the model itself, decides enterprise AI outcomes.
Why the operating model — not the technology choice — decides enterprise AI outcomes, and how to choose the structure that fits.
The headline cost of model inference is a small and shrinking fraction of what enterprises actually spend to run generative AI in production. The production evidence reviewed here consistently shows inference accounting for 20–40% of run-rate cost for mature deployments. Retrieval, evaluation, observability, governance, and human review consume the remainder — and are largely invisible at planning time.
Evaluation as practice, governance as delivery — the two disciplines that decide whether enterprise AI earns operational trust