Every day, people put their knowledge into AI skills, agents, and workflows: how to research a customer, assess a supplier, analyse a report, or write a useful response.
That expertise becomes part of how an organisation works. It needs ownership, evaluation, and a way to improve.
We’re building the system of record for organisational AI competency: a place to understand what exists, how it performs, and how it changes over time.
Improvement should be testable.
Changes should be reviewable.
People should remain responsible for deciding what deserves their trust.
I started using skills in January 2026, shortly after they became an open standard, and saw a huge shift in the performance of AI. I wanted to understand how they could work and to be at the forefront of that shift. I started experimenting with a team of agents, using skills to rework the code of an old talent management system.
That system was built around a competency framework, which measures each person’s progress against the competencies their role requires. I realised AI needed the same thing. Agents, and the people using skills in tools like Claude, would both need to know which skills were performing and which weren’t. I couldn’t tell for my own, and I knew people everywhere would recognise that pain in time. So I started building.
The old saying goes: you can’t manage what you don’t measure. This is the future of work.
As AI takes on more work, the expertise behind it becomes an increasingly valuable organisational asset. Mensova helps teams give it the care and attention it deserves.