Forget the perfect CV. Something else matters more when job hunting in the age of AI

In early 2026, six early-career professionals were given six months to explore how AI could help young people find work. Now, as the Impossible? Possible experiment enters its final stretch, it’s a good time to hear what the team has learned along the way and what outcomes it has produced.

When Susanna Auramo and Vera Väänänen join the Teams interview, there is a sense of anticipation and excitement. They already have months of intensive work behind them, including workshops, interviews and building AI agents. One interviewee is still missing.

A moment later, Samuel Nousiainen also appears on screen and apologises for being late. His computer has just decided to launch “the world’s longest update”, complete with error messages. Perhaps that, too, is one of the lessons of working life: technology does not always adapt to our plans quite as quickly as we adapt to it.

Soon, the conversation is in full swing. And no wonder, as there is plenty to talk about.

At the start of the experiment, the team was given no predefined framework. Instead, they had six months to explore, try things out, build and, when necessary, change direction. Now, with the finish line in sight, at least one thing is clear: many things look different from when they started.

The problem was not the CV after all

For Nousiainen, one of the first ideas was very concrete and personal.

“The idea for the CV agent came from my own experience. It’s really frustrating having to tailor your CV to every single job when you’re applying for a lot of roles.”

When you are applying for ten or fifteen positions, each CV needs to be adapted to the specific role. AI could offer very practical help with that.

But as the team began talking to young jobseekers, employers and other stakeholders, their understanding of the problem changed. The CV turned out to be only a small part of the bigger picture.

“A lot of young people are really exhausted by the constant cycle,” says Väänänen.

Application after application. Edit the CV. Send. Wait. And then, often, nothing.
What was particularly striking was how many young people felt that the effort they put into job hunting simply did not lead anywhere. At the same time, an even more fundamental question emerged: before you can tailor your skills to a particular role, you first need to understand what those skills actually are.

And the answer may not necessarily be found in your employment history.

“Life outside work can also play a really important role in shaping your professional identity,” Auramo points out.

A hobby, volunteer work or a study project can reveal skills that someone may never have thought of as professionally relevant. This insight led to the creation of a personal branding agent that helps users find the common thread connecting experiences that might otherwise seem unrelated.

Perhaps the most interesting role for AI in job hunting, then, is not to write a better CV for someone. Perhaps it should first help people understand what they have to say.

Then came the AI slop

The deeper the team delved into the world of jobseekers, the clearer another paradox of the AI era became. Writing a good application has never been easier. The problem is that every applicant is in the same position.

“Recruiters tell us they’re receiving huge amounts of generic AI slop,” Väänänen says.

When applications all start to sound alike, you have to stand out in other ways. Who are you? How do you think? What have you done, and what do you want to learn?

Auramo sees AI primarily as a form of support in this context.

“AI can act as an interpreter, helping you articulate your skills from a professional perspective. It can help you discover something about yourself that you might not otherwise have noticed.”

The role of a good agent is therefore not to produce the most polished possible answer on the user’s behalf, but to help them ask better questions. The more AI is used in job hunting, the more valuable the very thing it should not be used to conceal becomes: your personality.

“I realised I had been living in an AI bubble”

The experiment has also challenged the team members’ own assumptions. For Nousiainen, one of the biggest surprises came during the workshops.

“I realised I was really living in an AI bubble. I thought everyone knew a lot about AI and was interested in it.”

The reality was much more varied. At the same time, feedback from the first workshops confirmed that the team was working on something that genuinely mattered.

“Seeing that people were genuinely excited and interested in learning made me think, hey, this is actually useful. It isn’t just our idea of what might help.”

Auramo’s learning journey has gone in the opposite direction. She had never built AI agents before, and there was a lot of new technical information to take in at the beginning. But by doing the work, something unfamiliar gradually became familiar.

“Once you’ve just got on with building the agents, it starts to feel quite natural. It has been much easier.”

One team member therefore had to take a step back from his own AI bubble, while another discovered that she could quickly take several steps forward.

Three problems, many different agents

The agents have also evolved over the course of the experiment. Gradually, their roles began to crystallise around three questions.

The personal branding agent helps answer the first: who am I and what can I do? The CV agent then helps translate those skills into a form that a particular employer can understand.

In the third stage, the dynamic is reversed. Instead of competing with others for the same advertised vacancies, could a jobseeker identify an opportunity within a company themselves?

The Opportunity Architect, developed by Väänänen and Nousiainen, examines a company’s operating environment in relation to the user’s skills and helps them formulate a proposal: “Here is a problem I could solve for you within a specific timeframe.”

This allows a young person to turn their skills into a clear, ready-made proposition that is easier for a company to engage with.

“Even if it doesn’t lead to a job straight away, your name and the way you approached the company can stick in people’s minds in a completely different way,” Väänänen says.

The agents can also be linked together so that insights generated with one become input for the next. The user does not have to start telling their story from scratch every time.

Without a ready-made map

At the same time, the six professionals have had to develop their own way of working on a project whose outcome nobody defined in advance. This has meant constant prioritisation and discussion, and at times differing views on which direction to take.

While Auramo and Nousiainen describe how the experiment’s wider societal dimension gradually became apparent to them, Väänänen says she started from the bigger picture. Her learning journey has taken her in the opposite direction, towards moving faster and experimenting more.

Bringing together six different backgrounds and ways of working has therefore been part of the experiment itself. At the same time, that very freedom has made the experience exceptional.

“An opportunity like this is incredibly rare in working life. It really is a once-in-a-lifetime experience,” Väänänen says.

What if hiring young people is actually a competitive advantage?

As the experiment has progressed, the team’s focus has increasingly shifted beyond the jobseeker alone. Even if AI can help a young person recognise their skills and discover new opportunities, there still needs to be an employer on the other side that is willing to open the door.

According to Väänänen, hiring young people is often discussed as a matter of corporate responsibility. She would challenge companies to see it as a strategic question too.

“It’s about the ability to evolve and to bring in fresh energy and new ideas.”

Sometimes, a small encounter may be enough. What would happen if a member of the executive team set aside some time for a summer employee or recent graduate and asked: what do you think about our company? For the young person, the conversation could be a meaningful experience. The company, in turn, might hear something that would not have occurred to anyone in its own meeting rooms.

The experiment is ending. What happens next?

As the experiment enters its final stretch, the agents are being refined and the team wants to test them with more users. Auramo has one particular hope.

“The dream would be for a young person to find a job with the help of our agents. That would be the dream outcome.”

At the same time, Väänänen hopes the experiment would spark a broader discussion about what young people are experiencing when looking for work and how working life should respond to it. Because ultimately, the success of the six-month experiment may not be determined by how many agents the team managed to build.

Far more interesting is what happens next with their help.

Meet all six members of the team on the Impossible? Possible experiment website.