LinearB Strawberry

Your AI companion for LinearB.

Engineering metrics are more useful when they lead back to the pull requests, work items, and operating decisions that created them. Strawberry can work from the LinearB workspace you are signed into and the relevant engineering tabs to investigate delivery signals and prepare planning briefs. It can trace blocked work and document evidence for a team review.

Explain the movement before treating the metric as a verdict.

A cycle-time change can come from review load, batch size, an incident, holiday coverage, or a shift in what the team is building. Strawberry can connect the selected LinearB views to the underlying work context and prepare questions before anyone assigns blame.

Find the work waiting in the handoff, not just the aggregate.

An average can hide the small set of pull requests or tickets that are genuinely stuck.

Strawberry can organise the selected LinearB data into an actionable queue with the owner, wait point, and source context visible.

Prepare a planning conversation around trade-offs.

Planning is better when the team can see capacity signals alongside commitments, recent interruption work, and delivery risk. Strawberry can prepare a discussion brief from the material you select without claiming that a metric alone decides the plan.

Review delivery patterns after the sprint has enough evidence.

A biweekly pass after the sprint closes can compare the completed period with the one before it. It can then prepare a small set of evidence-backed operating questions for the retrospective. The cadence avoids reacting to partial in-flight work every morning.

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Frequently asked questions

It can use the authenticated LinearB tab and the related tabs, files, or notes you provide for a clearly scoped task.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents