Blog
Over the last eighteen months we've seen a familiar pattern across government and enterprise clients: a flurry of AI experiments, a handful of impressive demos, and very little that lasts beyond the pilot funding window.
The teams that break out of that pattern share three habits. First, they pick use cases where the value is measurable in dollars or hours saved — not just "productivity uplift." Second, they invest in the boring scaffolding: identity, data access, evaluation harnesses, and audit trails. Third, they staff delivery with a mix of engineers, change leads and domain experts from day one.
Production-grade AI is less about the model and more about the operating model. Treat each use case like a piece of software your organisation will depend on, because that's exactly what it becomes.
More from the blog
Architecture decisions that survive turnover
Lightweight decision records are the highest-leverage artefact an architect can produce. Here's the format we use.
Legacy modernisation without the big bang
Strangler-fig patterns, AI-assisted discovery, and tight feedback loops turn legacy modernisation from a five-year bet into a continuous delivery program.