Explore what a mixed human–AI enterprise needs to learn.
Research, concepts & working experiments · LecXie
Evidence
before a claim of competence
These are independent research and development activities. Agent assurance is not represented as established enterprise delivery; concept and prototype pages retain their development status.
What needed to connect.
Model capability, the competence of a deployed agent and permission to perform consequential work are different questions. Organisations need a clearer way to connect evidence, authority, learning and continuing assurance.
The part I led.
I use LecXie to develop and test ideas about capability intelligence, adaptive learning, careers and the mixed human–AI workforce. AyEye is the editorial practice: it examines developments, evidence and practical consequences rather than presenting speculation as delivered client value.
What the work produced.
- Source-linked AyEye publications on AI systems, work, capability and assurance.
- Capability Intelligence and Adaptive Capability concepts, with working demonstrations where identified.
- Agent Competency Assurance: an emerging research proposition distinguishing capability, competence, authorisation and currency.
What I can bring to a similar problem.
I can bring informed AI evaluation and practical questions about use cases, evidence, adoption and governance to a transformation conversation.
What needs to work differently?
A useful first conversation starts with the problem, the decisions it needs and the people who have to make it work.