InfoQ has initiated enrollment for its new InfoQ Certified High-Performing Teams Program. This five-week live online program is facilitated by Olimpiu Pop, InfoQ Java Editor and InfoQ Podcast co-host. The first cohort is scheduled from November 17 to December 17, 2026, with sessions held on Tuesdays and Thursdays from 4:00 PM to 6:00 PM CET. The enrollment fee for the program is $1,470.
The program examines the interdependencies between engineering team structure, delivery flow, ownership, AI-enabled work, and performance metrics. Participants will work towards developing a target operating model for an engineering team over the five weeks.
Topics covered include team design, delivery bottlenecks, workflow patterns, self-sustaining delivery, and managing dependencies. It also addresses the integration of AI agents into software delivery, including delegation of work, human judgment, and necessary controls.
A significant portion of the program is dedicated to engineering metrics, particularly how they change when AI shifts delivery bottlenecks. Participants will compare measurement frameworks and identify metric anti-patterns, focusing on which measures remain useful as output increases.
The final week integrates all previous topics into the team operating model, emphasizing responsible AI. This includes discussions on the ethical and environmental implications of AI-enabled delivery, culminating in capstone presentations from each group.
The program is designed for a small cohort of senior engineers and architects from various companies. It utilizes selected QCon talks and technical materials as starting points for weekly discussions. Participants apply the material to current team, delivery, or operating-model decisions through time-boxed exercises, then share their findings and adaptations with the cohort.
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InfoQ has opened enrollment for its new five-week live online certification program, the InfoQ Certified High-Performing Teams Program. The program, led by Olimpiu Pop, focuses on how engineering team structure, delivery flow, ownership, AI-enabled work, and metrics interact to develop a target operating model for engineering teams.