A Q&A with Michelle Lee, Engineering Manager
Deep learning gives advertisers more time to focus on new challenges, more chances to think up new ideas, and more ways to grow their business. Cognitiv’s recent brand campaign highlights the incredible outcomes possible when you “reclaim your brain.” Many of the outcomes showcased, such as Invention, Collaboration, Reflection, Transformation, and Inclusion are also part of the fabric of our brand values. In this series, we look inward, with team leaders highlighting how these words and outcomes are brought to life within our own walls.
The Technical Product Management (TPM) team, led by Michelle Lee, is truly transforming our operations at Cognitiv, particularly in the realm of the engineering workflow. As a women-led team with a huge impact, I wanted to sit down with Michelle to discuss how she and her new team are making major waves at Cognitiv, helping us to be “More Transformativ” than ever before.
How does the engineering workflow impact our company’s ability to innovate?
Our engineering workflow is crucial for our innovation. As a startup, we thrive on being agile and flexible, which means our engineers wear many hats. And while we’re quick to address issues, the rapid switch-ups can interrupt our focus on tasks. The influx of feature requests and bug reports further complicates matters, often leading to inefficiency in workflow.
That’s where my team comes in! We support our engineers by managing communications and organizing requests, allowing them to focus purely on innovation. This empowers our team to pursue meaningful, creative solutions, driving a culture of problem-solving throughout the entire organization.
Can you share more about your background and your observations from your previous experiences? How does this inform your approach at Cognitiv?
Absolutely. My journey from software engineering at Radiant Vision Systems to my current role as Engineering Manager and TPM leader at Cognitiv has been extremely transformative. Because I started at Cognitiv as a software engineer, I observed firsthand the challenges our engineering team faced, prompting me to pivot toward improving processes.
Recognizing the need for dedicated focus, we created the TPM team earlier this year to bring fresh perspectives to drive efficiency. Our efforts, like implementing intake and ticketing systems, have already made a tangible impact, providing clarity and accountability for our teams.
I believe that my background and observations have empowered me to create meaningful change, fostering a culture of efficiency and collaboration at Cognitiv.
How did this team come into existence, and why now?
Our team’s inception was rooted in the evolving needs of Cognitiv as we continue to grow. When I first joined three years ago, our company was smaller, with around 60 employees and a handful of clients. Back then, the idea of introducing a new team would have seemed excessive. Collaboration was more organic with fewer engineers, and the need for formal organization wasn’t as pressing.
However, the landscape changed as we expanded, especially with us recently surpassing 100 employees and acquiring numerous clients and campaigns. The increased workload made it clear that the initial process of individual responses from engineering was not sustainable. We needed a structured interface for handling queries and requests from various teams.
Enter our team. We serve as the first point of contact for other teams, including Client Success, Operations, and Data Science. By centralizing these interactions, we enable the engineering team to concentrate on their core tasks, ultimately enhancing our overall efficiency and effectiveness in serving clients.
As the leader of a new team, what achievement are you most proud of, and why?
One accomplishment that stands out is the successful implementation of our intake system. This achievement is particularly significant as it aligns with our goal of enhancing the usage of our Luna tool, which engineering launched in December. Luna serves as our internal platform for campaign management of our Curation and Contextual products. One notable aspect packaged within Luna is the capability to generate reports crucial for our Client Success Managers.
What makes this noteworthy is the collaborative effort between our team and the rest of engineering. This implementation not only enhanced our internal processes but also fostered trust and synergy between engineering and the teams they serve.
What fuels your passion for working in AI, particularly in the realm of deep learning?
I am really excited about the thought of diving into AI, especially deep learning. While the field itself isn’t entirely new, the rapid advancements and the numerous possibilities it presents make it feel like uncharted territory. Deep learning, in particular, is the hot topic of the moment, and it feels like we’ve only just scratched the surface of its potential.
