Stop tracking experiments as Linear tickets.

If you are searching for "Linear A/B testing" or wondering whether to track product experiments in Linear, this comparison is for you. Many product engineering teams reach for Linear when they need a place to manage hypotheses, run tests, and document outcomes. It works for about a quarter. Then the project archives, the closed tickets disappear from active views, and the cross-test pattern recognition that should have compounded into smarter decisions just stops happening. This guide covers exactly why Linear is the wrong shape for an experiment workflow, what it does brilliantly, the recommended pattern that combines both tools, and how a structured experiment journal handles the work Linear was never built to do.

Linear answers what the team is building. Blazeway answers what the team has learned. The two questions look adjacent and behave oppositely. A Linear ticket lives until it ships, then disappears from the active view. An experiment has the opposite shape: the value compounds over time, the closed ones are the asset, the timeline of past insights is what makes the next test smarter. Forcing experiments into a tracker built around closing tickets is solving the wrong half of the problem.

A Linear ticket is a unit of execution. It exists to be completed and removed from the queue. An experiment is a unit of learning. It exists to be completed and kept accessible forever, because the insight from a closed test is the asset that makes the next test smarter. These two shapes are opposites. Forcing one into the container built for the other costs you the part you most want to keep.

Every team that runs experiments tries this first. A project called "Q3 Experiments." Each test is a ticket with a hypothesis in the description, expected outcome in a comment, observed outcome in a follow-up comment, lessons learned eventually pasted into the description before the ticket closes. It works for a quarter.

Then the project archives. The closed tickets stop appearing in the team's default views. Three quarters later, a new engineer joins and asks "have we tested this pricing change before?" The answer is "I think so, somewhere." The project still exists in Linear. It just no longer informs the team's decisions.

This is the underlying problem with using Linear for experiments: Linear is optimized to remove closed work from your attention. That is exactly what you want for shipped features. That is exactly what you do not want for completed experiments. Closed experiments are the asset. The tool treats them as noise.

Hypothesis structure is the first casualty. A ticket has a description; an experiment needs Observation, Mechanism, Prediction. Free-form descriptions decay into "test new headline" within two weeks. There is nothing in Linear that forces a hypothesis to be testable. By month three, your "Experiments" project is mostly tickets with vague descriptions and no clear win criteria.

Post-mortem insight is the second loss. Tickets close. Closed tickets become noise. The insight from a closed test is the most valuable part of the entire workflow, because it is the only thing that makes the next test smarter. In Linear, that insight either lives in a comment that nobody re-reads, or in a description that gets updated minutes before close and then archived.

Cross-test pattern recognition is the third. You cannot pipe your closed Linear tickets into an LLM and ask "what have we learned about pricing pages over the past two years." The data shape is wrong. Tickets are atomic units of execution; they do not aggregate into a cross-cutting learning archive. An experiment journal does. That is the design difference.

This page is not an argument that Linear is bad. Linear is excellent. It is the best issue tracker available for product engineering teams. The issue model, the keyboard-driven workflow, the integration depth with GitHub and Slack, the project planning and cycle structure: all of it works. Nothing in Blazeway competes with any of that.

The argument is narrower: a tool optimized to close issues and archive completed work is the wrong shape for storing the most important artifact in an experiment workflow, which is the closed test. Two different problems, two different tools.

Linear stays. It is the best at what it does. Blazeway lives next to it. The pattern is straightforward:

A Linear issue says "Implement experiment X (link)." The link points to a Blazeway test. The test holds the hypothesis, the variants, the result, the insight. When the engineer ships the implementation, the Linear issue closes. The experiment continues in Blazeway, runs to completion, and the documented insight stays alive in the experiment archive. New tests can be designed against the entire history of past learnings.

Two tools, two verbs, no overlap. Linear handles the engineering execution. Blazeway handles the learning archive. The link between them is a URL. Most teams settle into this pattern within the first month of using both.

If your team currently tracks experiments as Linear tickets, the migration is straightforward and incremental. Existing tickets stay in Linear as the historical record of what was built. New experiments get created in Blazeway with the hypothesis schema, and the Linear issue for the implementation work links to the Blazeway test.

You do not need to back-fill historical experiments. The point of the migration is to stop losing future insights, not to reconstruct a perfect archive of past ones. Most teams complete the transition within the first two sprints.