Every software team encounters technical issues. Some are simple and easy to identify, such as broken links, missing permissions, or incorrect calculations. Others are far more complex. Integration failures, performance slowdowns, or user interface issues may only appear under specific conditions, on certain devices, or after a particular sequence of actions. These problems can range from minor disruptions to critical failures that affect customers, revenue, and trust.

In these situations, clear documentation becomes the difference between a fast fix and a prolonged investigation. Without accurate context, teams spend time trying to reproduce the problem, asking follow‑up questions, and making assumptions about what went wrong. Written bug reports often fall short. Describing a technical issue in text usually turns into long explanations of what was clicked, what was expected to happen, and what actually happened. Even then, key details are often missing or misunderstood.

This gap creates friction between teams. Product managers, QA engineers, support teams, and developers exchange messages trying to clarify the issue. Engineers attempt to recreate the bug based on partial information. Each round of clarification delays resolution and increases frustration. In fast‑moving environments, this back‑and‑forth can slow releases and pull teams away from higher‑value work.

Audiovisual reporting helps solve this problem by removing ambiguity. Instead of explaining an issue after the fact, teams can capture it as it happens. A screen recording shows the exact steps taken, the environment, the error messages, and the unexpected behavior in real time. This provides engineers with the full context they need to diagnose the issue quickly and accurately, without guesswork.

Loom makes this approach practical and easy to adopt. With Loom, anyone can record their screen, camera, or both while reproducing a technical issue. The recording captures visual context and narration, creating a clear and complete account of the problem. Loom automatically generates a shareable video link, which can be embedded directly into Jira work items, Confluence pages, or shared with engineering teams. This turns vague bug reports into clear, actionable evidence.

By using Loom to record and share technical issues, teams improve communication, reduce time spent clarifying problems, and speed up troubleshooting. Engineers receive the information they need upfront, fewer meetings are required to explain issues, and bugs are resolved faster.

The steps below show how to use Loom to document technical issues clearly and share them in a way that speeds up investigation and resolution. These practices focus on capturing full context, reducing manual effort, and keeping communication tied to your existing Atlassian workflows.

Engineering team collaborating to debug and fix code on a shared screen.

Step 1: Record the issue as it happens

Start by opening Loom and selecting Screen + Webcam (or screen only if preferred). This setup captures exactly what is happening on your screen while you explain the issue in real time. Seeing the issue unfold removes ambiguity and gives engineers direct insight into the environment where the problem occurs.

As you record, walk through the steps that led to the issue. Narrate your actions, point out error messages, highlight unexpected behavior, and explain what you expected to happen instead. If the issue depends on timing, permissions, or a specific sequence of actions, make that clear during the recording. This real‑time explanation helps your team understand both the symptom and the impact without needing follow‑up questions.

The goal is to capture the issue once, clearly, with enough context that someone else can understand it without trying to reproduce it blindly.

Step 2: Generate a structured bug report from the video

After recording, use Loom’s AI workflows to turn the video into a structured bug report or Jira work item. Instead of manually writing long descriptions, Loom can extract key details from the recording and format them into a ticket that includes reproduction steps, observed behavior, and expected outcomes.

This approach reduces manual work and improves consistency across bug reports. Engineers receive the same type of information for every issue, which makes triage easier and faster. Because the report is generated directly from the video, important context is less likely to be missed or misinterpreted.

By connecting Loom with Jira, teams can move from “issue observed” to “issue logged and ready for investigation” in minutes, not hours.

Step 3: Share the video where the work happens

Once the bug report is created, share the Loom video directly inside Jira work items, Confluence pages, or support tickets. Embedding the video keeps visual context tied to the work item, so anyone reviewing the issue can immediately see what went wrong without searching for attachments or external links.

Loom videos can also be shared via link or email, with access controls applied for sensitive technical information. This ensures the right people can view the recording while maintaining security and privacy standards. For distributed teams, this approach keeps everyone aligned without adding meetings or long message threads.

For faster communication, Loom can also generate short, clear summaries when sharing videos in tools like Slack or email, helping recipients understand the issue before they even press play.

Step 4: Make the issue searchable and easy to track

After recording and sharing the Loom, enable automatic transcription and summaries. Loom AI generates a full text transcript and a concise summary of the video, which allows team members to understand the issue quickly without watching the entire recording. Engineers can scan the summary to grasp the problem, then jump directly to specific moments in the video when they need more detail.

Searchable transcripts also make technical issues easier to revisit later. Team members can search for specific error messages, system behaviors, or reproduction steps and be taken directly to the relevant section of the recording. This saves time during triage and prevents the same questions from being asked repeatedly.

To improve long‑term usability, organize Loom recordings by project, product, or issue type. When videos are grouped logically, they form a growing library of real technical examples. Over time, this becomes a practical knowledge base that teams can reference when similar issues occur, reducing duplicate investigation and speeding up future fixes.

Step 5: Collaborate asynchronously across teams and time zones

Loom supports asynchronous collaboration by allowing viewers to leave timestamped comments and reactions directly on the video. Instead of scheduling meetings or exchanging long message threads, team members can review the recording on their own schedule and comment at the exact moment where they have a question or insight.

This approach is especially effective for distributed teams. A developer in a different time zone can watch the Loom hours later, leave a comment tied to a specific action or error, and receive a response without delaying progress. Follow‑up Loom recordings or replies can be added to clarify details or confirm fixes, keeping the discussion focused and documented.

By enabling asynchronous review and discussion, Loom helps teams maintain momentum on issue resolution while reducing meeting overhead. Technical problems move forward continuously, even when team members are not online at the same time.

Step 6: Final review and handoff to engineering

Once the issue is documented, the Loom video and the auto‑generated details in Jira provide engineers with a complete, shared view of the problem. They can see the exact steps that triggered the issue, review error messages or unexpected behavior, and reference structured data such as reproduction steps and environment details. This combination of visual evidence and written context allows engineers to begin troubleshooting immediately, without asking for additional clarification.

During investigation, engineers, support teams, and stakeholders can add timestamped comments directly to the video to ask questions or share findings. These comments stay tied to specific moments in the recording, keeping discussions focused and easy to follow. Keeping the Loom embedded in the related Jira work item or Confluence page ensures all context remains in one place until the issue is resolved.

This approach creates a clear record of how the issue was identified, reviewed, and addressed. When the fix is complete, the Loom serves as a traceable reference for future audits, retrospectives, or process improvements.

Step 7: Store and reuse the recording for future reference

After resolution, store the Loom recording in a shared project or team library. Over time, these recordings become a valuable source of institutional knowledge, capturing real examples of technical issues and how they were resolved. This is especially helpful as teams grow or change, since knowledge remains accessible even when individuals move on.

Past Loom recordings can also be reused when similar issues appear again. Instead of starting investigations from scratch, teams can reference earlier recordings to recognize patterns, confirm root causes, and apply proven fixes more quickly. This reduces repeated effort and shortens resolution cycles.

For QA and testing teams, these videos provide concrete examples of past bugs and edge cases. They can be used to improve test coverage, validate fixes, and prevent regressions. By storing and reusing Loom recordings, organizations turn one‑time issue reports into long‑term assets that continue to deliver value.

Why Teams Should Use Loom for Technical Issue Reporting

Clear communication is critical when technical issues arise. Traditional text‑based bug reports often leave room for interpretation, which slows down troubleshooting and leads to unnecessary back‑and‑forth. Loom addresses this gap by letting teams show exactly what went wrong, providing shared context that speeds up understanding and resolution.

Below are the key reasons teams should use Loom to report and document technical issues.

1. Eliminates ambiguity in bug reports

Written descriptions rely on assumptions. Even detailed reports can miss steps, UI states, or timing issues that matter when diagnosing a problem. Loom removes this uncertainty by capturing the issue as it happens. Engineers can see the screen, follow the exact sequence of actions, and hear the context explained in real time.

This shared visual reference reduces misunderstandings and ensures everyone is aligned on what the problem actually is.

2. Reduces time spent reproducing issues

One of the biggest delays in bug resolution is reproducing the issue. With Loom, teams no longer need to guess how a problem occurred. The recording shows the environment, inputs, and system behavior, allowing engineers to focus on diagnosis and fixes instead of trial‑and‑error reproduction.

As a result, teams move faster from discovery to resolution.

3. Communicates more information in less time

A short video can convey what dozens of written messages cannot. Visual documentation captures interface state, error messages, system responses, and timing without requiring the reporter to remember or describe every detail. Important context that might be overlooked in text is naturally included in the recording.

This makes Loom especially effective for complex or intermittent issues.

4. Improves collaboration across roles and teams

Loom creates a shared understanding between product, QA, support, and engineering teams. Everyone reviews the same source of truth instead of interpreting written descriptions differently. Timestamped comments allow focused discussions directly on the recording, keeping feedback organized and relevant.

This reduces meetings and keeps issue resolution moving forward asynchronously.

5. Fits naturally into existing Jira and Confluence workflows

Loom integrates directly with Jira and Confluence, so teams do not need to change how they work. Videos can be embedded in jira work items and confluence pages, making them searchable, traceable, and tied to the work being done. Bug reports become more actionable without introducing new tools or processes.

This integration ensures visual documentation enhances existing workflows instead of complicating them.

6. Creates lasting technical knowledge

Recorded issues don’t lose value once a bug is fixed. Loom videos can be reused as references for future incidents, onboarding, and QA testing. Over time, teams build a library of real examples that help prevent repeat issues and improve overall software quality.

Using Loom for technical issue reporting leads to clearer communication, faster fixes, and stronger collaboration. By replacing guesswork with visual context, teams spend less time explaining problems and more time solving them.

Turn Technical Issue Reporting into a Faster, Clearer Process

Technical issues are unavoidable, but slow and unclear reporting does not have to be. When teams rely only on written descriptions, valuable time is lost clarifying details, reproducing problems, and aligning on what actually went wrong. This friction compounds as teams grow, tools multiply, and work becomes more distributed.

Loom changes how teams capture and communicate technical issues by making context visible from the start. Screen recordings, narration, searchable transcripts, and direct integration with Jira and Confluence create a single source of truth that everyone can understand. Engineers get what they need to act quickly, stakeholders stay informed, and teams spend less time explaining and more time fixing.

By adopting Loom as part of your technical reporting workflow, you move from reactive troubleshooting to efficient problem solving. Issues are documented once, understood clearly, and resolved faster, while the recordings themselves become long‑term knowledge that continues to deliver value well beyond the initial fix.

The Role of Atlas Bench

Tools alone do not fix process problems. Most teams already have strong Atlassian products, but they do not always use them to their full potential. This is where Atlassian Bench comes in.

As an Atlassian Platinum Solution Partner with deep Cloud specialization, Atlassian Bench helps teams use Atlassian Cloud tools the right way, based on how they actually work. That includes Loom, Jira, and Confluence, and how these tools connect in day‑to‑day technical workflows. We also support broader Atlassian Cloud initiatives, including migrations, tool consolidation, permission models, and performance optimization. Our focus is practical outcomes: less friction, faster resolution, and tools that support the team instead of slowing it down.

If your team is using Atlassian Cloud but feels like you are only scratching the surface, Atlassian Bench helps turn tools like Loom into part of a clear, effective, and scalable way of working.

Interested in learning more? Contact Atlas Bench to book a complimentary consultation with our Certified Atlassian Experts.

Try Atlassian + Loom now – and manage technical issues better

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Atlas Bench is an Atlassian Platinum Solution Partner with deep Cloud Specialization, helping Data Center customers move beyond migration and fully transform on the Atlassian Cloud Platform. We deliver Atlassian’s System of Work end to end through four collections: Strategy, Teamwork, Service, and Software, connecting planning to execution, aligning teams around outcomes, modernizing service delivery, and accelerating software development.

We are also recognized as an Atlassian World Class Software Development Partner of the Year (Americas), and we bring AI leadership to every engagement. By leveraging Rovo for automation and purpose built agents, we reduce manual work, unlock knowledge across tools, and speed up decision making so organizations realize measurable value faster in cloud.

How to Record and Share Technical Issues Using Loom