Comparison
Jira tracks work. Glue tracks whether that work actually fixed the problem. See how codebase intelligence complements your existing project management workflow.
By the Glue Team
Jira is the world's most widely used project management tool. Glue is a codebase intelligence platform. These are not the same category of software, and in most cases teams use both — but understanding what each does, and critically what each cannot do, is essential for any product or engineering team trying to improve how they work.
Jira is built for work coordination: tracking the state of tasks across a distributed team, managing sprint backlogs, and reporting on delivery progress. It is excellent at telling you what is being worked on, who owns it, and whether it is done. These are coordination questions, and Jira answers them at scale better than most alternatives.
Glue is built for codebase intelligence: reading your actual code and translating what it finds into strategic insight for product managers, engineering leaders, and CTOs. It answers questions that Jira cannot, because Jira has no connection to the codebase.
The overlap between the two tools exists at the engineering leadership layer. An engineering manager might use Jira to track sprint progress and Glue to understand whether that sprint progress actually resolved the underlying codebase issues that prompted the tickets. But their primary audiences, data models, and value propositions are distinct.
| Capability | Glue | Jira |
|---|---|---|
| Track ticket status (To Do / In Progress / Done) | No | Yes |
| Sprint planning and backlog management | No | Yes |
| Understand what the codebase contains | Yes | No |
| Detect technical debt in the codebase | Yes | No |
| Verify a fix actually resolved the underlying problem | Yes | No |
| Answer "how does our billing system work?" | Yes | No |
| Map feature gaps vs. competitors | Yes | No |
| Show knowledge concentration risk (bus factor) | Yes | No |
| Connect sprint work to codebase outcomes | Yes | No |
| Time tracking and reporting | No | Yes |
| Roadmap visualization | No | Yes |
Jira is excellent at what it was built for. It tells you what tickets exist, who they are assigned to, what sprint they are in, and whether they have been completed. For coordination across a large engineering organization — making sure the right people are working on the right things at the right time — Jira is the industry standard for good reason.
Jira's workflow customization, integration ecosystem, and reporting capabilities are mature. If you need to know the velocity of your team over the last six sprints, or which epics are on track for the quarter, Jira can tell you. Reporting on activity is where Jira excels.
Jira's fundamental limitation is that it has no connection to the codebase. It knows what work was done — what tickets were created, assigned, and closed — but has no way to know whether the work resolved the underlying technical problem. A ticket titled "Fix technical debt in the payment service" can move from In Progress to Done without the payment service's code health improving at all. Jira has no way to detect this mismatch.
Glue operates one layer deeper: it reads the codebase. When Glue detects a high-risk module — one with a single owner, declining test coverage, and high change frequency — it can connect that detection to a sprint ticket, track the work done, and then verify against the actual codebase whether the risk has been reduced. This is the difference between tracking activity and tracking outcomes.
Glue also answers questions that Jira fundamentally cannot. "What features do we have?" "How does our checkout flow work?" "Which files would need to change if we add a new payment method?" These are product intelligence questions. And 95% of product managers (airfocus/Gitnux, 2024) cannot answer them without interrupting engineers, regardless of how organized their Jira board is.
For more on why ticket systems miss codebase context, see Why Your Ticket System Has No Idea What Problem It's Actually Fixing.
Jira is the right choice for any team that needs to coordinate work across multiple people, track sprint commitments, manage backlogs, and report progress to stakeholders. If your primary need is knowing what work is in flight and who owns it, Jira does this better than almost anything else at scale.
Glue is the right choice when your team needs to understand what is in the codebase, not just what is on the board. Specifically, Glue adds the most value when product managers spend significant time asking engineers questions about the system, when technical debt work is not visibly reducing technical debt, and when engineering managers need to demonstrate the business impact of technical investment to leadership.
See Glue for Technical Debt Management for how outcome verification works in practice.
Yes — and most teams that use Glue also use Jira. They are complementary tools. Jira manages the coordination layer: sprint planning, ticket assignment, progress tracking. Glue manages the intelligence layer: what is in the codebase, what risks exist, and whether sprint work is resolving those risks.
The integration pattern: Glue detects a codebase problem and surfaces it as intelligence. That intelligence informs a Jira ticket. The Jira ticket tracks the work. Glue verifies the outcome. This is closed-loop engineering intelligence — and it requires both tools working together.
No. Glue is a codebase intelligence platform, not a project management tool. It does not replace Jira's sprint planning, backlog management, or work tracking capabilities. Most teams use Glue alongside Jira — Jira handles coordination, Glue handles codebase intelligence and outcome verification.
Glue can tell you what features exist in your codebase, which code modules have high bus factor risk, whether technical debt work actually reduced debt, how your system architecture works, and which files would need to change for a given feature request. Jira knows none of this — it only knows the state of tickets.
Glue connects to your Git repository (GitHub, GitLab, or Bitbucket) to analyze the codebase. Detected issues surface as work items that connect to your sprint workflow. The intelligence Glue generates informs what goes into Jira, and Glue's outcome verification tells you whether what came out of Jira actually worked.
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