LinearB is a platform for understanding and improving how engineering organizations work.
It connects data from across the software development lifecycle to help teams analyze productivity, delivery performance, workflows, and developer experience.
As engineering increasingly incorporates AI, LinearB also provides tools for understanding how AI is being used and what impact it has on the way software is built.
The engineering productivity platform
From Data
to Decisions
Across these projects, the recurring challenge has been remarkably similar: LinearB has access to an enormous amount of engineering data, but data alone is not useful.
My work has increasingly focused on the layer between data and decisions — designing ways to help users find the right information, understand its meaning, explore the underlying context, and ultimately know what to do next.
The Design System
A growing product needs a shared language.
I contributed to the evolution of LinearB’s design system, working closely with engineering to create reusable patterns and components that improve consistency across the platform and make both design and development more scalable.
AI Impact
& Productivity Insights
AI Insights
A new entry point into AI analytics, designed to help engineering leaders understand how AI tools are being adopted and how they affect the way software is built.
The project eventually exposed a much larger challenge: while we could create a clear high-level view, exploring the data further still meant navigating a legacy analytics experience that had grown increasingly difficult to use.
AI Analytics
What started with AI Insights evolved into a broader rethink of LinearB’s analytics experience.
We redesigned the way users move from high-level signals into deeper analysis, creating a new reporting structure for exploring AI adoption, engineering activity, delivery performance, and the impact of AI across teams and organizations.
AI Assistant
Alongside the analytics redesign, we explored another way of interacting with complex engineering data: conversation.
AI Assistant lets users ask questions about their engineering organization and use AI to move from finding data to understanding what it means — reducing the need to know exactly which dashboard, report, or metric to look for.
