AI agents need a fixed, shared meaning for business data before they can be trusted to reason over it. This piece looks at what Fabric IQ and Ontology actually are, how they differ from a semantic model, what preparing your data for them involves, and where the platform trade-offs sit against alternatives from Databricks and Snowflake.

Legacy systems often don't come with a specification, with their behaviour living in code nobody documented and workarounds nobody wrote down. This piece looks at why conventional testing breaks down in modernisation projects, how characterisation testing captures undocumented behaviour before it's changed, and how to measure whether your testing strategy is actually working.

The gap between a proof of concept and a production system is where a significant proportion of AI initiatives fail to progress. Understanding what that transition involves, and planning for it from the outset, is one of the more important things a technology leader can do before committing investment. This blog draws on Episode 1 of Audacia's podcast Technically Speaking and covers the lessons our guests have taken from productionising AI.

This blog captures the key themes from the launch event of Technically Speaking, Audacia's new podcast - held as part of Leeds Digital Mini Festival. Technology and security leaders from financial services, government and software came together to explore the 'Human Problem' in cybersecurity.