Glue vs LinearB

Engineering leaders evaluating engineering team productivity tools face a crowded market, and LinearB is one of the most recognized names in the space. LinearB focuses on DORA metrics, cycle time optimization, and workflow automation for development teams. Glue takes a broader approach, connecting engineering activity to product context so that leaders understand not just velocity numbers but what those numbers mean for the product. This comparison covers where each tool excels and which problems it solves best.

LinearB has built a focused, mature platform for engineering process metrics. If your primary goal is measuring and improving development velocity, LinearB delivers strong tooling.

DORA metrics with depth. LinearB provides detailed tracking of deployment frequency, lead time for changes, change failure rate, and mean time to recovery. The dashboards include industry benchmarks so you can see how your team compares to peers. For engineering leaders reporting to executives on team performance, this data is immediately useful.

Cycle time breakdown. LinearB decomposes cycle time into granular stages: coding time, pickup time, review time, and deploy time. This lets you pinpoint exactly where work stalls. If PRs sit in review for days, the data shows it clearly and helps you address the bottleneck.

gitStream automation. LinearB's gitStream product lets you define rules that automate PR workflows. You can auto-assign reviewers, label PRs by type, and route reviews based on code ownership. For teams drowning in PR management overhead, this is practical and effective.

Team workload visibility. LinearB shows how work is distributed across the team, highlighting when specific developers are overloaded or when review responsibilities are unevenly spread. This helps managers make better sprint planning decisions.

Investment allocation. LinearB categorizes engineering time into new features, bug fixes, tech debt, and other buckets. This gives leaders a high-level view of where engineering effort is actually going versus where the roadmap says it should go.

Actionable alerts. LinearB can notify engineering managers when metrics cross defined thresholds, such as when a PR has been open for more than 48 hours or when deployment frequency drops below a target. These alerts create a feedback loop that keeps process improvements on track rather than relying on periodic retrospective reviews.

Glue starts from a different premise. Instead of treating engineering as an isolated process to optimize, it connects engineering activity to the product layer, giving leaders context that pure metrics cannot provide.

Metrics with meaning. Glue tracks engineering activity, but it ties that activity to product outcomes. Instead of just showing that cycle time increased by 20%, Glue explains that the increase came from the payments refactor, which involved cross-team dependencies and a complex database migration. The context behind the numbers changes how leaders interpret and act on data.

AI that understands your codebase. Glue indexes your repositories, pull requests, commit history, and ticket discussions. When an engineering leader asks "Why did the auth service deployment fail last week?" Glue provides an answer drawn from actual code changes and CI logs, not just aggregated statistics.

Product-engineering alignment. Glue connects roadmap items to the engineering work that implements them. When a product manager asks about feature progress, the answer comes from real commit and PR data rather than manual status updates. This reduces the back-and-forth between product and engineering that consumes hours every week.

Code health beyond metrics. LinearB shows you numbers about your process. Glue shows you what is happening in your code. It can identify areas of growing complexity, highlight modules with increasing bug rates, and surface technical debt that is slowing delivery. This is qualitative insight that complements quantitative dashboards.

Cross-functional visibility. Glue is designed to be useful for product managers, designers, and other stakeholders alongside engineering leaders. LinearB is primarily an engineering management tool. If your goal is improving collaboration between functions, Glue provides a shared context layer that everyone can access.

Onboarding and knowledge transfer. When new engineers or managers join a team, Glue lets them ask questions about the system architecture, recent changes, and past decisions. Instead of scheduling a series of knowledge transfer sessions with senior engineers, new team members can get immediate, context-rich answers grounded in the actual codebase and its history.

LinearB is the right choice when your focus is specifically on engineering process optimization. Pick LinearB if:

• You need to report DORA metrics to leadership. If your CTO or VP of Engineering wants standardized benchmarks and trend lines for deployment frequency and lead time, LinearB provides these out of the box with industry comparisons.
• PR workflow is your biggest bottleneck. If your team struggles with slow reviews, inconsistent labeling, and manual reviewer assignment, gitStream directly addresses these problems with automation.
• You want a pure engineering management tool. If you are an engineering manager focused on team velocity, workload distribution, and process improvement, LinearB is purpose-built for that job.
• You are benchmarking across multiple teams. LinearB's comparison features let you see how different squads perform on the same metrics, which is valuable for large engineering organizations trying to spread best practices.

Glue is the better fit when engineering metrics alone do not tell you enough. Consider Glue when:

• You care about the "why" behind the numbers. If a dashboard showing that cycle time went up is not enough and you need to know which features, dependencies, or decisions caused the change, Glue provides that context automatically.
• Product-engineering alignment is a pain point. If product managers and engineering leads spend too much time in syncs trying to agree on what shipped, what is blocked, and what is coming next, Glue creates a shared source of truth grounded in actual work.
• You want AI that reasons over your codebase. Glue's AI goes beyond workflow automation. It can answer technical questions, explain architectural decisions, summarize complex PRs, and surface risks that metrics dashboards miss entirely.
• Your audience extends beyond engineering management. If product, design, and business stakeholders also need visibility into engineering work, Glue provides views and summaries tailored to each audience without requiring everyone to learn an engineering-specific dashboard.

Absolutely. LinearB and Glue address overlapping but distinct problems.

LinearB excels at quantitative engineering process measurement. It tells you how fast your team is moving, where the bottlenecks are, and how you compare to benchmarks. Glue excels at contextual understanding. It tells you what your team is building, why certain things are taking longer, and how engineering work connects to product goals.

Teams that use both typically rely on LinearB for engineering-internal process reviews and sprint retrospectives, while using Glue for cross-functional alignment, product-connected status updates, and AI-powered codebase understanding. The combination gives you both the numbers and the narrative, which is what most engineering leaders actually need when making decisions.

A practical split: use LinearB in your weekly engineering standup to review cycle time, PR throughput, and deployment frequency. Use Glue in your cross-functional product sync to explain what shipped, what is blocked, and how the current sprint connects to roadmap objectives. Each tool serves a different meeting and a different audience, which means neither one goes unused.

Does Glue provide DORA metrics like LinearB? Glue tracks core engineering activity metrics including deployment frequency and lead time, but it does not focus on industry benchmarking the way LinearB does. Glue's strength is connecting those metrics to product context, so you understand the story behind the numbers rather than just the numbers themselves.

Can LinearB connect engineering work to product roadmap items? LinearB offers investment allocation categories and can tag work by project, but it does not deeply integrate with product roadmaps or provide AI-powered explanations of how code changes relate to product features. That product-level connection is a core differentiator for Glue.

Is Glue only useful for engineering leaders, or can product teams use it too? Glue is designed for both engineering leaders and product teams. Product managers use Glue to understand feature progress, get codebase context for technical decisions, and generate stakeholder updates. Engineering leaders use it for team visibility, code health monitoring, and cross-functional communication. This shared utility is one of Glue's key advantages over engineering-only tools.