The work behind AI output.

The research

FreQNC explored 17 concepts over five testing rounds with 25 senior leaders accountable for AI-assisted work, across Europe and the UK, during September and October 2026.

The work explored responses to early diagnostic concepts. It was not a test of a deployed product. Participants were not customers or current pilot partners, and the sample was not limited to engineering buyers.

Fieldwork: September and October 2026 · Across Europe and the UK.

Source: FreQNC Discovery Report

Handovers mattered within this sample

The way work passed between people was important to how participants responded to the concepts. Their responses pointed to questions about what happened between creating work, checking it and making a decision. This informs the pilot's focus on queues and handovers; it is not a claim about how common a particular workflow is across the market.

Participants described their own safeguards

Within this sample, participants described safeguards they had already introduced. These checks had context and intended purposes that a record of activity alone would not explain. That shaped a pilot question: what is an existing check meant to preserve, and what waiting happens around it?

Who could see an assessment mattered

Who would be able to see an assessment materially affected participants' reactions in this research. This informs the need to agree visibility and data handling before any pilot starts. It does not establish consent from the people doing the work, nor permission to assess individuals.

What remains unvalidated

This was qualitative concept research across engineering and non-engineering roles. The concepts and testing procedure changed between rounds. It informs the pilot; it does not establish the diagnostic's accuracy or business outcomes.

The findings describe this sample, not universal facts. Changes between rounds limit direct comparison. They do not show market prevalence, willingness to pay, code safety or improvements to delivery. The validation pilot will test whether examining workflow evidence alongside a team's context produces useful priorities.

The next question is practical.

Does the proposed diagnostic add something useful beyond existing GitHub reports and an internal review? Bring a real review problem to the pilot and help test that question.