Rethinking How Teams Plan, Make Decisions And Work Together
Deniz Gezgin is CEO of Eightpoint, a global technology company building & scaling consumer digital products across mobile & desktop.
gettyWhen I became CEO of Eightpoint in July 2024, I joined a company with experienced teams and strong technical capabilities across desktop and mobile software. I saw an opportunity to connect that expertise more closely and build a company where teams could make decisions with a clearer understanding of the broader business.
We’ve spent much of the past two years working through that change. Bringing different functions together around shared priorities has required us to revisit how information moves through the organization and how decisions are made.
That experience has shaped my perspective on AI. As new tools make development, analysis and testing more efficient, the way a company operates becomes increasingly important.
One of the first things I noticed was how much time could be lost between capable teams working toward different priorities. Engineering, product, analytics and marketing each had valuable expertise. When information stayed within individual departments, teams sometimes approached similar problems independently or made decisions without the full context.
We’ve worked to bring shared capabilities—including data, platform and design—closer to our product teams. This gives people access to expertise across the company and helps reduce duplicated effort.
I believe leaders introducing AI should pay close attention to these existing workflows. Understanding where decisions slow down can reveal opportunities to improve how the organization works as a whole.
Annual and quarterly planning remain useful for establishing direction and allocating resources. At the same time, product teams often receive meaningful feedback long before the next formal planning review.
I’ve become more interested in organizing execution around shorter learning cycles while keeping longer-term business priorities consistent. A team can work toward an annual objective while using two-week sprints to evaluate specific assumptions, make improvements and determine where to focus next. Our product development approach emphasizes defining a problem, testing an idea and using the results to guide additional investment.
There are limits to how frequently a company can change direction. Teams need enough stability to complete meaningful work, and some decisions require more time to evaluate.
As a CEO, I’ve learned that the way leaders make decisions has a significant influence on how quickly the rest of the company can move. During periods of change, it’s natural to want greater visibility into what’s happening across the business. I’ve had to think carefully about where my involvement is useful and where it can slow people down.
We’ve been working toward clearer ownership across our teams. I want leaders to understand the outcomes they’re responsible for, have access to the information they need and feel confident making decisions within their areas. That comes with expectations around accountability. People need to explain their reasoning, make results visible and raise issues early enough for the organization to respond.
When an experiment produces an unexpected result, I want to understand how the team approached the decision and what it recommends doing next.
AI’s creating opportunities for teams to produce more work in less time. As that happens, I think leaders need to become more thoughtful about how they evaluate progress. Traditional measures such as features delivered, campaigns launched and projects completed remain useful, but they provide only part of the picture.
I’m interested in how quickly teams can validate assumptions, identify problems and apply what they’ve learned.
In consumer software, the results of an experiment can be difficult to interpret. A change might improve engagement among one group of users while having little effect elsewhere. Teams need time to understand those differences and determine whether the improvement supports the broader product.
This requires a culture where people can discuss disappointing results openly. I’ve found that the way leadership responds in those moments has a lasting influence on how teams approach future decisions.
Culture becomes visible in the everyday decisions people make. One of our priorities has been creating stronger connections between the teams responsible for developing products, understanding users and growing the business.
For example, bringing Spigot and Eightpoint Technologies together under the Eightpoint brand gave us a shared identity. The more involved work has been making that identity meaningful through clearer priorities, stronger ownership and better collaboration.
I’ve learned that encouraging people to work together only goes so far. They also need shared information, aligned objectives and a clear understanding of who’s responsible for moving decisions forward. The relationships between people and the trust required to make decisions together still need attention from leadership.
I’m encouraged by the practical ways AI is already supporting our work. Our desktop team is using AI-assisted tools for browser upgrades and automated testing, with human approval remaining part of the development and release process.
As these capabilities develop, I expect companies will have more opportunities to experiment and respond to changing user needs. Leaders will need to think carefully about how they organize teams, allocate resources and create room for learning.
I’m proud of the progress we’ve made, particularly the broader ownership our leaders have taken and the way teams are becoming more connected.
For me, the opportunity ahead is to build a company that can keep improving its products, its decisions and the way people work together. The progress we make will depend on how thoughtfully we put those capabilities to work.
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