Map the patterns.
See which UI patterns exist, where they appear, and where they diverge.
Avarlo carries approved product patterns into Claude Code, Codex, and pull requests—so designers shape the system and frontend teams build from it.
Avarlo maps the patterns in your repo, records the direction design chooses, and makes it available wherever your team builds and reviews.
See which UI patterns exist, where they appear, and where they diverge.
A designer chooses the intended pattern, behavior, and meaningful exceptions.
Give Claude Code and Codex the approved pattern before they write the UI.
Use the approved CustomCombobox. This one-off menu is missing keyboard navigation and role labels.
When a pull request diverges, surface one focused suggestion grounded in the approved decision.
I moved more of my design work from Figma into a React prototype repo. With coding agents, I could explore real interactions and product patterns instead of handing off static screens. The work moved faster.
Soon PMs and engineers were building product UI directly. Shipping accelerated, but the intent behind existing patterns did not travel with the code. Design direction needed to scale with the work.
Design needed a way to lead beyond individual screens.
I started turning repeated review comments into rules. That exposed a boundary: frequency can reveal a pattern, but it cannot choose the direction. Some decisions can be automated. Others still need human taste.
Frequency is evidence. Direction is a decision.
Designers choose the intended pattern, behavior, and meaningful exceptions. Avarlo records that decision with its source, then carries it into coding agents and pull requests as the product evolves.
Human taste decides. The system remembers.
Designers can shape the system instead of redrawing every screen. Frontend teams build from trusted direction, and the product stays coherent as more people contribute.
Hyunghwan Byun
Founder & designer
We’ll map the patterns already in code, capture the direction your design team approves, and prepare it for your team’s next AI-assisted build.