About the Project
Inspiration
This project was inspired by a recurring problem observed across agile teams: work items often enter a sprint appearing ready, yet issues such as unclear scope, hidden dependencies, or mismatched complexity emerge only after the sprint has started. These problems reduce predictability, increase rework, and place unnecessary pressure on teams.
Rather than focusing on fixing issues during sprint execution, this project explores how teams can be supported earlier, at ticket creation and backlog refinement time, when changes are cheaper and clarity has the greatest impact.
What the Project Does
Know+ is a backlog readiness and sprint confidence coach for Jira. It assists teams in writing effective tickets that align with their delivery capabilities by learning from how the same team has delivered work in previous sprints.
The tool evaluates work items across multiple dimensions, including clarity, scope signals, delivery risk, and team compatibility. Team compatibility focuses on how well a ticket’s complexity, expectations, and structure align with the historical delivery patterns of the team.
Based on these signals, Know+ provides practical guidance to help authors refine tickets before sprint commitment. Where refinement is needed, Rovo is used to generate contextual improvement suggestions grounded in the team’s historical delivery context. The intent is not to block work, but to coach teams toward clearer, more achievable tickets.
Team Compatibility and Scoring
A key aspect of Know+ is team compatibility assessment. Rather than assuming one definition of a “good” ticket, Know+ recognises that teams differ in experience, velocity, and delivery patterns.
Team compatibility metrics are derived from aggregated sprint outcomes and ticket characteristics, such as scope size, refinement quality, completion consistency, and delivery trends observed across previous sprints. These signals are used to assess whether a ticket, as written, is well matched to how the team has historically delivered work.
This allows Know+ to provide guidance that is tailored to the team, rather than applying generic quality rules.
Data and Privacy
Know+ is designed to assess ticket quality and team alignment without relying on personal user data. It does not profile, score, or evaluate individual contributors.
All team compatibility insights are derived from aggregated sprint outcomes and ticket level characteristics, not from individual performance metrics. Rovo assisted suggestions operate on the current ticket content and aggregated team delivery signals only.
No personal user attributes are required or stored to generate scores or recommendations.
How It Was Built
The project was built as a modular system with a clear separation between user experience and scoring logic.
A React and TypeScript interface was used to model how the tool would appear within Jira backlog and issue views. Scoring logic was implemented using structured heuristics that assess scope clarity, delivery risk, and team compatibility metrics derived from historical sprint outcomes.
The architecture is designed for integration as a Forge Custom UI app, with adapters intended to consume live Jira context such as issue data, sprint history, and team level delivery signals. Rovo is leveraged as a guidance layer to generate contextual suggestions when ticket refinement is required.
Challenges Faced
The primary challenge was working within Forge runtime and tunneling constraints during local development. While these limitations prevented full end to end wiring during the development window, they did not affect the core logic or user experience design.
To address this, the Forge bridge was stubbed for demo purposes, allowing the complete scoring logic and interaction flows to be demonstrated in a standalone interface that mirrors the intended Jira placement.
Another challenge was balancing guidance with autonomy. The design intentionally avoids hard blocking or enforcement, instead focusing on explainable signals and actionable suggestions that teams can choose to apply.
What I Learned
This project reinforced the importance of addressing delivery problems at their source. Improving ticket quality before sprint commitment has a disproportionate impact on predictability and team confidence.
From a technical perspective, the project highlighted the value of decoupling domain logic from platform integration, making it possible to continue meaningful development even when tooling constraints arise.
Most importantly, it demonstrated that effective agile tooling should behave like a coach alongside the team, not a gatekeeper in front of them.
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