Coding sessions: environments, browser use, and updated pricing
Linear Agent now supports configurable environments for setting up and testing code before returning work, includes browser testing to catch visual regressions and broken interactions, and introduces transparent pricing with lower costs based on model usage tokens and sandbox runtime charges.
Linear Agent can now set up, run, and test your code before returning its work. That means fewer handoffs and changes that are further along when they come back to you.
We’re also introducing lower, more transparent pricing, making AI credit usage easier to understand and control.
Configurable environments
Coding sessions now automatically adapt to each codebase's configuration, with broader out-of-the-box support for Python, Ruby, Go, and more.
During a session, Linear detects and installs the toolchains and dependencies it needs to complete the task. Teams can go further by pinning runtime versions, adding setup scripts, and defining environment variables.
To get started, create an environment in settings. Visit the docs for more details.
Browser testing
Once the application is running, Linear Agent tests its work where users experience it: in the browser.
The agent opens the app, navigates through a flow, and verifies its implementation. It also captures before-and-after screenshots, making visual changes easier to review alongside the code.
Browser testing can catch broken interactions and visual regressions that code review alone might miss. If the agent finds a problem, it can make a fix, rerun the test, and return the work with that validation complete.
Transparent pricing
As coding sessions take on more work, costs need to be easy to understand and easy to control.
Starting today, coding sessions use a lower-cost pricing model with two components:
Model usage: Tokens are charged at the provider’s published rates, with no markup
Sandbox runtime: Charged at $0.25 per 20-minute block
Together, model usage and runtime determine the AI credit cost of a session. The usage dashboard shows the breakdown, along with token usage and cost by model.
Admins can also set workspace-wide and per-user spend limits that reset daily, weekly, or monthly. When a limit is reached, additional AI credit usage is paused until the limit resets or an admin increases it.
Learn more about AI credits in the docs.
Linear now displays stacked pull requests in Diffs with review and CI status, updates diffs in real-time as code changes, and provides admins with AI credit usage tracking and spend limit controls to manage costs.
Linear Agent now offers adaptive routing to optimize model selection by task complexity, environment secrets support for secure dependency access, and open-weight model options including GLM. Teams can define custom project labels and statuses, assign project leads, use durable IDs for projects and initiatives, and automate workflows with new team-based triggers for onboarding and reassignment.
Loops, Linear's recurring agent workflows, now respond to more workspace activity including project, initiative, and cycle changes, can edit Linear documents and post updates to Slack. This helps teams automate coordination tasks like updating docs and keeping stakeholders informed when plans change.