Business users are increasingly taking ownership of AI tools, monitoring their performance and ensuring they align with business processes, rather than relying solely on IT departments.

Each team manually inputs their key metrics weekly, which ensures they own and understand their performance, rather than relying on automated systems that might lead to disengagement.

Inspecting metrics like adoption, engagement, and retention is essential to understand how users interact with an AI product and its effectiveness.

Maintaining metric hygiene is essential; ensure that all measures on your dashboard are consistent and relevant, which encourages daily engagement from the team.

Enterprise clients often have established metrics and performance indicators, allowing us to track how much time is spent on tasks and the impact of AI adoption.

We're measuring outcomes with metrics that show whether we're moving the needle, rather than just assessing the technology itself.

We learned that sharing real-time metrics with the entire company, even during interviews, creates a culture of accountability and alignment, making everyone feel part of the mission.

Metrics are essential in product development as they provide a numerical representation of the value we deliver to customers. It's important to measure not just internal metrics but also how well customers achieve their goals using our product.

Creating dashboards in the office to display key metrics engages everyone in the company's performance and encourages a shared sense of achievement and accountability.