How Citation’s engineering leaders turned AI adoption into faster delivery

Many engineering teams have adopted AI tools—but few are seeing real gains. In this webinar, leaders from Citation share how they uncovered and removed the hidden constraints limiting productivity, offering a practical path from AI experimentation to measurable delivery impact.

Overview

Most engineering organizations have invested in AI tools. Many are still struggling to see meaningful improvements in productivity, delivery speed, or predictability.

In this facilitated discussion, engineering leaders from Citation share how they identified and resolved the constraints limiting productivity, even after adopting AI tools. They’ll walk through the process they used, the barriers they uncovered, and the measurable results they achieved.

Joined by Plandek, this session focuses on how to move beyond AI experimentation and into real, sustained delivery impact.

What You’ll Learn

The most common constraints that prevent AI tools from delivering productivity gains
Why tracking constraints is critical to improving engineering performance
A step-by-step approach to identifying and eliminating delivery bottlenecks
How Citation applied this approach in practice
What changed once constraints were addressed
Lessons learned and what they would do differently next time

Key Takeaways

Why AI adoption without fixing underlying process issues rarely moves the needle
Practical ways to track constraints inside your engineering system
Proven techniques for removing bottlenecks without disrupting delivery
How to measure productivity improvements as constraints are eliminated

Who This Webinar Is For

VPs and Directors of Engineering
Engineering Leadership

Organizations

Companies already investing in AI tools
Teams actively exploring AI adoption and impact

Hosted by

Pranav Lakhotia

Head of Professional Services

Pranav has over 9 years of experience in consulting and advisory services. He has spent his career helping software delivery teams enhance efficiency, predictability, and overall performance. Having joined Plandek from Deloitte in November 2023, he has worked closely with engineering leaders and teams to identify bottlenecks, refine delivery processes, and drive continuous improvement through data-driven decision-making. He specializes in helping organizations measure and optimize key delivery metrics, enabling teams to deliver value faster while maintaining high-quality outcomes. His insights and hands-on approach make him a trusted advisor to technology leaders seeking to build high-performing engineering teams.