Two facilitators asked a room full of Atlassian professionals to raise their hands. Who uses AI at work? Every hand went up. Did it make you faster? Every hand stayed up. Then came the question that changed the mood. Keep your hand up if AI made you not only faster, but better, better at thinking, deciding, and collaborating with other people. Hands wavered and dropped. That gap, between working faster and actually growing, is the whole subject Alisa Popa and Oana Popescu came to Work Evolution Summit to explore.
Alisa is the founder of Agile Learning and has spent more than 14 years building learning and development programs for managers, leaders, and teams. Oana brings around 20 years in HR, mostly inside IT companies. Rather than present slides at you, they ran a workshop, and their framing question is worth carrying into your own week. The tool is the engine, and you are the driver. So what part of you is actually doing the driving?
Faster Is Not the Same as Better
Alisa put her own work on the table to make the point. She built the session’s presentation with AI in one hour instead of five days. A real gain in speed. But she was honest that she is no more capable at making presentations than she was before. The tool did the work. Her skill stayed flat.
Hold that distinction, because it runs through everything. A faster decision is not automatically a better decision. Moving quickly on a project in the wrong direction does not deliver you somewhere better, it just gets you to the wrong place sooner.
“faster doesn’t mean better”
The encouraging part of their message is that speed and growth are not a trade-off. You can work in a way that is both faster and more capable at the same time. The workshop was designed to show you the difference between the two.
The Scenario Every Team Recognizes
Alisa and Oana handed the room a situation you have probably lived. Six months ago your team adopted a new project management tool. It has boards, workflows, and automations. When you look at the dashboard, everything appears in order and on track. In real life, people forget to update their tickets, statuses go stale, and work still misses deadlines. Everyone is using the tool, and nothing has actually changed.
Then they split the room into small groups and gave them three minutes and one instruction. How would you normally fix this?
Round One: How You Would Normally Fix It
They called this round busy fixing, and the answers came fast because the instinct is familiar. Add more automation. Run training. Push people harder. A few groups reached for fire and hire. Others took a gentler line, talking to people and trying to understand what blocks them. One group, only half joking, suggested training an LLM to update the tickets for them.
Afterward the facilitators asked how the round felt, and the room agreed it was easy. That is the tell. It was easy because you have seen the problem before and you answer it on autopilot, from an existing mindset and a familiar set of moves. Easy answers are the ones that do not require you to think.
Round Two: The Questions That Made People Stop
Same scenario, but now two harder questions. First, what outcome do you actually want, and how would you measure it, with a real number? Second, what mindset or behavior, if it changed, would fix this?
This round was hard, and everyone felt it. The difference showed up in what people produced. Instead of jumping to fixes, groups started asking why the behavior happens, what the tool means for the team, how to earn genuine buy-in, and how the team would even look and function differently. The questions generated more questions, and those questions clarified the purpose behind the work. As one group put it, the second scenario forced them to think about the team rather than the task.
The Two Traps
Alisa and Oana named the two patterns the exercise exposes, and both are worth pinning up.
The first is the outcome trap. Faced with a problem, you rush straight to actions, we should do this, then that, then that, without ever defining where you want to end up, how you will measure success, or how you will know it worked. As trainers, they were quick to admit that even training, their own product, is not always the answer. Deciding the outcome comes first.
The second is behavior blindness. Tools and AI let you move faster, but if you never grow your own capabilities, competencies, and mindset alongside them, the same problem returns, and you meet it with the same limited response. Grow the mindset and the problem might not recur at all, or you will solve it more efficiently next time. They reached for the idea often attributed to Einstein, that given a problem, he would spend the bulk of his time working out the right question and only a little finding the answer. Root cause analysis, they noted, is where the real solution usually hides.
Stop Tuning the Engine
Their close reframes what a problem even is: “every problem that you’ll face, finally it has two solutions hidden within”
One solution is the outcome, the goal you want to reach and the measure that proves you reached it. The other is the chance to grow your own capability on the way there. Choose to pursue both and your behavior compounds over time, your teams get sharper, and improvement becomes continuous rather than a one-off fix. That is the choice the facilitators kept returning to, and they made it a single line.
“Stop tuning the engine and start growing the driver”
You are the driver, and you decide whether you stay the same or get better with every problem you face. Alisa and Oana pointed the room to a five-step framework they built for running this kind of facilitated question session, along with a free app for discovery and root cause analysis. But the takeaway costs nothing to start using. The next time something breaks on your team and your first instinct is to reach for another automation or another tool, pause and ask the two questions instead. What outcome do you actually want, and what would you have to become to get there?
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About Life in Codes
Life in Codes is on a mission: to support organizations of all kinds to work in a more productive way. That means smart tools, healthy practices, and training the people. As an Atlassian Solutions Partner active in Romania, Estonia, Belgium, UK and the UAE, with our team spread across Europe.
Our client roster includes start-ups, SMEs, large financial institutions like SWIFT, government organizations like the European Commission, and logistics providers such as DHL.Our expertise spans a wide range of solutions, including ITSM, Agile Project Management, Digitalization, Knowledge Management, next-level customer support, DevOps, cloud migration and Rovo AI agents.
We firmly believe that working smart is universal – regardless of industry, company size, or team composition. – our diverse client base is a testament to this philosophy. Whether you’re a tech-focused team or not, Atlassian tools, coupled with our expertise, can significantly enhance your productivity and collaboration.
At the end of the day, we believe in the power of teamwork and we aspire to help people reach their full potential. By partnering with Life in Codes, you’re not just adopting new tools – you’re embracing a more efficient, collaborative, and successful way of working. Schedule an appointment
