1. Context

In modern software organizations, QA engineers and developers operate under increasing pressure to ship faster, maintain high quality, and reduce regression risk. However, the tools and workflows supporting bug reporting and debugging have not evolved at the same pace as development methodologies like Continuous Delivery, feature flags, multi-environment testing, and parallel sprint teams.

QA teams still rely heavily on:

• Screenshots

• Manual screen recordings

• Browser DevTools

• Slack messages

• Handwritten reproduction steps

• Spreadsheets

• Incomplete Jira tickets

Developers, on the other hand, pull together fragmented information across:

• Console logs

• Network traces

• Local environment setups

• Remote environment differences

• Slack DMs

• Incomplete bug reports

This results in time wasted, slow development cycles, dropped quality, miscommunication, and friction across teams.

The gap is clear: while tech has evolved, bug reporting has not.

2. Brief

The assignment was to design a web application that allows QA engineers and developers to capture, report, reproduce, and resolve bugs efficiently, with minimal manual effort and maximum technical clarity.

The solution must:

• Integrate with Jira, Trello, Asana

• Improve QA speed

• Improve developer debugging experience

• Reduce communication overhead

• Capture complete context automatically

• Fit naturally into existing workflows

• Be scalable, modern, and intuitive

The output expected: research → insights → IA → flows → wireframes → high-fidelity design → prototype → impact.

3. Design Process

I followed a modified Double Diamond + Product Thinking approach.

Discover

• Competitive analysis

• Domain understanding (QA workflows, developer debugging workflows)

• User interviews

• Process observation

• Pain analysis

Define

• Key insights

• Problem reframing

• Personas

• Current journey mapping

• Task identification

• Opportunity mapping

Ideate

• Concept sketches

• Whiteboarding

• Explorations: modals vs right-panel, auto-capture strategies, reproduction flows

• Multiple approaches evaluated

Design

• Information architecture

• Low-fidelity wireframes

• Mid-fidelity layouts

• High-fidelity SaaS UI using Linear/Vercel/Notion aesthetics

• Motion and interaction pattern design

Validate

• Usability testing with QA + developers

• Revisions to layout hierarchy

• Improved clarity in bug detail view

• Updates to capture modal UX

Deliver

• Final prototype

• Design system foundation

• Case study narrative

4. Background

For decades, QA teams have relied on a variety of disjointed tools:

• Browser-based testing (physical devices or cloud)

• Screenshots captured manually

• Long video recordings

• Manually written reproduction steps in Word/Notion

• Copy/pasting DevTools logs

• Creating Jira tickets by hand

• Slack conversations for missing context

• Google Sheets for tracking issues

Developers have their own workflow:

• Reading limited Jira descriptions

• Asking for logs

• Trying to recreate the bug locally

• Attempting to match QA environment

• Investigating API calls manually

• Re-asking QA for details

• Debugging through trial and error

This fragmentation leads to:

• Inconsistent bug reports

• Missing logs

• Vague steps

• Environment mismatch

• High “Cannot Reproduce” rate

• Slow developer throughput

• Increased QA workload

We needed a unified solution that automates, simplifies, and connects the entire cycle.

5. Why?

Delivering high-quality products demands:

1. Speed

Faster bug resolution directly accelerates sprint velocity and release cycles.

2. Accuracy

Developers need complete context — logs, steps, failures — without spending hours chasing details.

3. Alignment

QA and developers often have asymmetric information. This creates friction, errors, and rework.

4. Efficiency

Manual bug reporting consumes 30–40% of a QA engineer’s time.

5. Cost Reduction

Efficient debugging reduces operational costs across engineering.

The vision:
Create a seamless QA → Dev pipeline where every bug is instantly captured, fully understood, and quickly fixed.

6. Key Needs

QA Needs

• Quick, effortless bug capture

• Automatic logs and steps

• Less documentation overhead

• Single place to manage bugs

• Seamless Jira/Trello integration

Developer Needs

• Complete context for every bug

• Accurate reproduction environment

• Clear logs and network failures

• Visual replay of user steps

• Reduction in Slack follow-ups

Business Needs

• Faster releases

• Higher product quality

• Improved team trust

• Reduced rework and delays

• Better cross-functional visibility

7. Current Process (Before Solution)

QA’s Reality:

1. Open staging/dev environment

2. Manually test features

3. Notice bug

4. Screenshot the issue

5. Record screen manually

6. Copy console logs

7. Capture network logs

8. Write reproduction steps

9. Create Jira ticket

10. Answer 3–15 developer questions

11. Re-test after fix

12. Update ticket

Developer’s Reality:

1. Read vague bug description

2. Cannot reproduce

3. Ping QA for logs

4. Ask for steps again

5. Request browser/device/environment details

6. Reproduce locally

7. Debug

8. Deploy fix

9. Wait for QA

10. Bug reopens from missing context

This cycle repeats. It is inefficient and costly.

8. User Interviews

I conducted interviews with two detailed personas.

Persona 1 — Riya Sharma (QA Engineer, 4 years experience)

Pain Points:

• Writing steps takes too long

• Forgot to capture logs

• Missed reproduction conditions

• Jira ticket creation is time-consuming

• Too many Slack pings

Quote:

“Most bugs fail because I can’t capture everything. Logs, steps, screenshots — something is always missing.”

Persona 2 — Arjun Verma (Frontend Developer, 6 years experience)

Pain Points:

• Incomplete bug context

• “Cannot Reproduce” frustration

• Logs missing or truncated

• Environment mismatch

• Slack threads break flow

Quote:

“If every bug gave me full logs and steps, I would fix everything twice as fast.”

9. Insights

From interviews, patterns emerged:

Insight 1 — Missing Context Is the Core Problem

Most bugs lack:

• steps

• logs

• environment metadata

• exact API failure

• user actions leading to bug

Insight 2 — Environment Mismatch Kills Debugging

Most non-reproducible bugs are caused by:

• wrong build

• wrong URL

• wrong data

• wrong browser version

Insight 3 — Manual Effort Is the Enemy

Both QA and devs spend more time collecting information than fixing issues.

Insight 4 — QA & Dev Workflows Are Unaligned

QA thinks visually.
Developers think technically.

Bug reports need to serve both.

Insight 5 — Tools Are Fragmented

5–7 tools used for one bug.

10. Redefining the Problem

“Design a unified platform that eliminates manual effort in bug capture and ensures developers always receive complete, reproducible, and structured bug context—without additional work from QA.”

11. User Journey (QA)

Stages

• Preparation

• Testing

• Bug encounter

• Capture

• Review

• Submit

• Track

• Retest

Each stage has tasks, pain points, and opportunities.

12. Customer Journey Mapping (QA + Dev)

StageQA ExperienceDev ExperienceOpportunityDiscoverTests manuallyNo involvementAuto-captureCaptureManual screenshotsMissing logsAutomated loggingReportManual JiraVague ticketsAuto-ticket creationDebugSlow responseLacks contextLogs-first layoutFixVersion mismatchNo confirmationBuild trackingRetestManual stepsReopensBefore/after diff

13. Task Identification

QA Tasks

• Start Testing Session

• Perform exploratory tests

• Capture bug when seen

• Add minimal info

• Send to Jira

Developer Tasks

• Open bug

• Analyze logs

• Reproduce

• Debug

• Fix & deploy

• Notify QA

System Tasks

• Auto-capture logs, network, metadata

• Auto-generate reproduction steps

• Auto-capture video

• Auto-create bug bundle

• Auto-send to Jira

• Auto-detect environment mismatches

14. Solution Approach

Four foundational pillars:

1. Automated Context Capture

• Logs

• Network

• Steps

• Metadata

• Video

• Errors

• Device

2. One-Click Bug Reporting

Auto-create bug reports with everything included.

3. Developer-Optimized Debug View

Logs-first hierarchy.
Timeline replay.
Reproduce button.

4. Integrated Workflow

Seamless flow into Jira, Trello, Slack.

15. Sketches

Early explorations included:

• Bug modal vs right sidebar

• Floating capture button

• Step timeline structure

• Screen replay styling

• Multi-panel debug layout

Decisions driven by clarity + speed.

16. Design Whiteboarding

Explored alternate flows:

• Session recording modes

• Metadata exposure levels

• Figma-like timeline scrubber

• Logs grouped by severity

• Auto-debug hints

Settled on tri-panel (steps/video/logs) layout.

17. Information Architecture (V1)

Dashboard Testing Session - Start Session - Active Session - Timeline Replay Bug Reports - My Bugs - Team Bugs - Bug Detail (QA) - Bug Detail (Dev) Integrations Settings Analytics (Future)

18. Usability Testing

Tested flow with 3 engineers.

Key Learnings:

• QA wanted minimal UI during testing → reduced clutter

• Developers wanted logs on top → changed hierarchy

• Jira export needed confirmation → added success modal

• Timeline replay needed clear labels → added timestamps

19. Card Sorting

Grouped features into:

• Testing

• Capture

• Reporting

• Debugging

• Collaboration

• Settings

Validated nav structure.

20. Updated IA (V2)

QA Mode - Dashboard - Start Session - Active Recorder Developer Mode - Bug List - Bug Detail - Timeline Replay - Environment Compare System - Integrations - Settings

21. Design – Wireframes

Mid-fi wires established:

• Dashboard

• Session setup

• Recorder

• Bug modal

• Bug detail

• Timeline replay

22. Design – Low Fidelity

Block-level UI provided:

• Layout

• Relative sizing

• User flows

• Component placement

23. Design – High Fidelity

Clean SaaS aesthetic:

• Lots of white space

• Soft shadows

• Grey neutrals

• Linear-style crisp typography

• Minimal visual noise

Screens designed:

• Dashboard

• Start session

• Recorder

• Bug modal

• Jira success

• Timeline replay

• Bug list

• Bug detail

• Developer logs

• Network inspector

24. Design – Prototype

Clickable prototype covering:

• Starting session

• Capturing bug

• Reviewing auto-generated content

• Sending to Jira

• Developer debug flow

• Timeline replay

• Fix workflow

• QA verification

25. Outcomes

Quantitative Results (Projected)

• 70% faster QA bug reports

• 80% faster developer reproduction

• 50% fewer communication loops

• 90% reduction in non-reproducible bugs

Qualitative Results

• QA feels empowered

• Developers feel respected

• PMs feel informed

• Engineering pipeline becomes predictable

26. Impacts

Team Impact

• Shared understanding

• Clear bug ownership

• Higher confidence

Business Impact

• Lower cost of QA

• Faster development

• Higher-quality releases

• Fewer regressions

27. Learnings

• Automation drastically improves QA productivity

• Developers prefer logs-first design decisions

• Unified workflows reduce emotional friction

• Context depth matters more than visuals

• Small UX decisions (like environment labels) have big impact

28. Feedback

QA Feedback

“This saves me hours every week. Steps and logs being automatic is a dream.”

Developer Feedback

“Every bug finally makes sense. This is what we always needed.”

Product Manager Feedback

“This closes the QA ↔ Dev gap beautifully.”