Recruitment at the heart of innovation.
AI is changing how teams are built, how companies operate and innovate, and what a strong candidate looks like. We follow these shifts closely and keep people at the centre of them, so every search reflects how your team will work next.
Smaller teams now take on work that used to need more people or an outside party. Roles merge, new ones appear, and the split of work between people and tools is being redesigned.
The companies that gain most are not just doing the same things faster. They rebuild their processes, try new ideas in shorter cycles, and hire for adaptability as much as for experience.
What a role expects is shifting. Strong people are judged on how they work, not just on what they know, and they choose employers who let them work that way.
For most companies, the question is no longer whether to use AI. It is who will change how the everyday work gets done. That is a people question, and it is where we work.
What changed in an ordinary week
The people who stand out are not always AI specialists. Many are AI-native: a developer, a security architect or a platform engineer whose way of working has been rebuilt around what is now possible, and who still owns every decision.
Hiring for how the work is done now changes what you ask for. A role written for the team you had may not fit the team you need.
- Team shape. A team of six who work this way needs a different shape than a team of ten who do not.
- Which roles to open. Before a search starts, we look at whether the role as written still matches how the work is done.
- What to look for. How someone works, and how they check their own work, says more than a list of tools.
- Who stays. People who work this way leave organisations that stop them from doing so.
Interviews are changing too. More employers want to know how you work, not only where you have worked. We help you show that clearly, and we tell you honestly what a role will expect.
- Method over tools. A long list of subscriptions is not a method. What counts is how you use them, and how you would know if the result were wrong.
- Not a seniority test. It is not about years. It is about whether you can tell good output from bad in your own domain.
- Accountability stays. Someone still signs their name to what ships. That part has not changed.
- You stay in control. You see your profile before a client does, and you can correct it.
Innovation still depends on people.
New tools keep changing what is possible. Whether a company actually innovates still comes down to the people using them: their judgement, their curiosity and their willingness to change how they work. That is what we recruit for.
Judgement. AI can produce an answer in seconds. Knowing whether it is the right one, and taking responsibility for the decision, is still a human skill. We look for people who can tell good work from bad in their own field, and who own the outcome either way.
Curiosity. The people who get the most out of new technology are usually the ones who went looking for it. They try new approaches before they are asked to, learn from what does not work, and share what does.
Willingness to change. Adopting a tool is easy. Changing how the work gets done is harder: dropping steps that are no longer needed, rethinking who does what, and being honest about the result. That is where the real gains are.
Little of this shows on a CV. We find it in conversation, by asking people how they work, what they have changed and how they know their work is right.
Some shifts we have noticed
- “Can you explain every line?”
- Output volume treated as a red flag
- AI use as evidence of weakness
- Years of experience as the proxy for judgement
- “How would you know if this were wrong?”
- What have you built that catches it for you
- What got bigger because of how you work
- What happens when it breaks at 2am