A Team of Five, Output Multiplied: How a Product Lead Put AI Automation to Work

Leading digital product development through a scale-up phase comes with its own tension. On one side, fresh funding demands that the next product version ship faster. On the other, the company’s bottom line demands careful control over how resources are spent.

That was the real dilemma facing Arief Yunansyah, a Product Lead at a growing technology startup. Including him, there were only five people on the team to execute a workload that kept piling up.

"Most of my time went to technical work — writing PRDs, synthesising research — rather than thinking about product direction. That is when it hit me: this repetitive work should be something AI can automate," Arief says.

Knowing he needed process efficiency without loading up revenue by hiring, Arief made a strategic call: go deep on Data-Driven & AI Decision Making for Leaders, the ITB x RevoU collaboration programme.

So how did Arief use AI and automation frameworks to pick up the pace and make sharper product calls? Here is how it played out.

Time Pressure, and a Solution That Adds No Headcount

As Product Lead, Arief owns the calls that matter — from which features ship to how the roadmap is shaped. But once investors started asking about progress on the latest release, he and his team hit a fork in the road.

"There are only five of us. Adding people with the bottom line where it was would only have put more strain on revenue. The urgency was really about time. We needed a way to automate the repetitive work so the new version could ship faster."

RevoU’s schedule turned out to be the most responsive one, and the best fit for his team’s operating rhythm, so Arief signed up without waiting.

Navigating an Executive Workload Mid-Development

Splitting time between steering the product and executing technical detail is never easy — less so while taking a professional course. More than once, Arief was still at his laptop late into the night.

"Building a product always takes extra hours. Sometimes I was still at my laptop until nine at night, which clashed with class. But it was manageable. I would usually watch the recording on weekends or in spare moments to catch up on what I had missed."

For Arief, committing to learn in the middle of an execution crunch was a price worth paying for long-term efficiency leverage for his team.

Beyond Tools: A Data and Decision Framework That Shifts How You Think

For practitioners already comfortable with AI tools, the real value of a leadership programme is not prompt-writing technique. What stayed with Arief was the thinking framework — how to work data into business decisions.

"What drew me in was that the programme is not just about how to use AI, but how to use AI to support decision-making. The early material — best practices for working with data, being rigorous about AI output, and the decision-making framework — is where I felt the benefit most. I also really enjoyed the A/B testing session and its hypothesis testing."

Beyond the decision framework, the later technical automation material — implementing n8n, for one — added value that mapped directly onto the workflow efficiency his company needed.

Real Use Cases and Team Collaboration

One advantage Arief leaned on throughout the programme was applying real use cases straight from the company he leads.

"With the individual assignments, the good part was that I could use real use cases from my own company. I anonymised some sensitive data, but the cases genuinely happened on the ground."

Arief also highlighted why group simulations matter for leaders. In his view, decision-making at management level does not end with a document; it is about communicating those instructions and that decision framework across a team of people in very different roles.

A Message to Other Leaders: Know the Need, Measure the Efficiency

As an analytical leader, Arief offers a notably level-headed view for managers and business owners weighing up whether to learn AI automation.

"I would always ask what the need is first. AI and automation are not necessarily the right fit for every case. But if the case looks like mine — a Product Lead or Product Manager doing a lot of repetitive work like writing PRDs, analysing research, or drafting documents — then I strongly recommend this programme. Automation can be far more efficient than hiring another Product Manager."

For Arief Yunansyah, AI is not merely an aid for coding or writing. It is a strategic lever that lets a small team land the kind of impact you would expect from a much larger one.