The team began by understanding the broader challenges surrounding bug reporting in web applications. Through literature review, secondary research, and observations from prior experience with software teams, they identified a recurring pattern: many bugs go unreported, many reported bugs lack sufficient context, and the resulting inefficiencies create both technical and business costs. These findings helped the team recognize that bug reporting was not only a usability issue, but also a workflow and communication problem affecting both developers and end users.

This early understanding was further reinforced through informal conversations with software practitioners in the startup and engineering ecosystem. Engagements at events such as Google DevFest, AIMX Singapore, D:NEXA, and Figma Maker Collective helped validate that these frustrations were experienced across real teams and products. Together, these research inputs gave the team a grounded understanding of the pain points that would shape the project’s next stages.

The team synthesized findings from the previous phase into a clearer and more focused understanding of the problem space. Drawing from the literature review, informal practitioner conversations, user personas, and journey mapping, they identified that the issue was not simply that bugs occur, but that many bugs are either left unreported or reported without the technical context needed for efficient diagnosis and resolution. This allowed the team to move from broad observations into a more precise articulation of the design challenge.

To support this process, the team evaluated and prioritized recurring concerns based on both their frequency and intensity of pain, as shown in the concern-mapping exercise. This helped highlight the most critical issues affecting current workflows, such as irreproducibility, missing environment and log data, messy or overwhelming logs, and the time lost in repeated clarification loops. From this synthesis, the team defined a focused problem statement and design objective: to create a bug reporting process that reduces friction for users while ensuring developers receive complete, clear, and actionable reports.

In response to the defined problem, the team developed qage.dev, an AI-assisted bug reporting platform designed to make issue reporting more effortless for users and more actionable for developers. The solution combined a lightweight embeddable widget for one-click reporting with a developer dashboard that consolidates screenshots, session replay, reproduction steps, environment data, console logs, and network logs into a single workflow. By pairing low-friction reporting with rich contextual capture, the team aimed to reduce the ambiguity and back-and-forth that typically slow down debugging.

The solution was refined through iterative prototyping, MVP development, onboarding sessions, and walkthroughs with prospective users. These activities allowed the team to observe how the product was understood and used in realistic settings, while also surfacing areas for improvement in usability, workflow clarity, and feature prioritisation. As the report notes, later iterations incorporated enhancements such as client-side redaction, cybersecurity improvements, and MCP integration, reflecting how the solution evolved in response to user feedback and real-world validation efforts.