It all starts in a meeting room. Teams share ideas, debate solutions, and align on goals, but too often, they leave behind chaos instead of clarity—hours of discussion result in lengthy transcripts filled with valuable insights that are never revisited.
The result?
- Project managers asking, “What are the action items?”
- Functional teams wondering, “What exactly were the requirements?”
- Developers waiting for structured backlog items that never seem to arrive.
Every digital transformation journey encounters this challenge: information scattered across meeting transcripts with no clear path to action.
As a Solution Engineer at Mazik Global, I identified the problem and wanted to fix it in a way that ensures we don’t lose anything important. So, I put Copilot and specifically GitHub Copilot to the test in a new way.
What is GitHub Copilot?
GitHub Copilot is an AI coding assistant developed by GitHub. It helps developers write code faster, allowing them to focus more on problem-solving, innovation, and collaboration.
It’s like having an intelligent partner that understands context and suggests what comes next, whether that’s a line of code, a function, or even documentation.
Across industries, GitHub Copilot has been shown to boost developer productivity and accelerate the pace of software development. But beyond coding, its potential goes much further. With the right prompts, it can understand context, summarize complex information, and generate structured outputs just like the kind we need in fast-paced project environments.
Prerequisites:
Before we begin, ensure you have the following:
- Account in GitHub.
- Sign up with GitHub Copilot.
- Students and Educators get FREE GitHub Copilot access
Experimenting Beyond Code
That’s where the idea took shape. We wanted to see if Copilot could go beyond assisting in coding and help make sense of unstructured meeting transcripts.
To test this, our team at Mazik Global ran an internal experiment.
We uploaded a 40-page workshop transcript into Copilot and prompted it with the following instruction:
“You’re a consultant. Using this meeting transcript, generate a structured summary that helps the functional team clearly capture requirements, progress, and next actions. Using this summary, the Functional team will develop a user story. Present each requirement as: who it’s for, what is required, and why.”
Within seconds, Copilot transformed the lengthy transcript into a concise, structured summary highlighting:
- Key topics with timestamps
- Requirements in a clear Who / What / Why format
- Follow-up actions with assigned owners
What was once an unmanageable document became a two-page blueprint for project success.
From Summary to Action: Turning AI Output into Backlog Items
Summaries are only the first step — execution is where impact happens.
To test Copilot’s limits, we went a step further:
“Create a separate issue for each in-progress and next items and assign it to XYZ project manager.”
Copilot didn’t just stop at summarization. It drafted GitHub Issues automatically, each representing a backlog item derived directly from the conversation.
Here’s the streamlined workflow our teams now follow:
- Generate issue drafts: Copilot identifies and structures backlog items from the summary.
- Review and refine: Teams validate details, adjust priorities, and assign owners.
- Add to GitHub Project Boards: Items are categorized by projects from Provider Portal to Data Migration.
- Publish to backlog: With one click, the draft issues become part of the active project backlog.
This process has reduced hours of backlog grooming into minutes — transforming how we move from discussion to delivery.
Note:
Copilot isn’t perfect, it's still evolving. It may:
- Not always get every detail right.
- Confuse roles or simplify complex requirements.
- Sometimes misses details that only a human expert can interpret.
That’s why human review remains essential. We treat Copilot as a smart assistant; it completes 70% of the work, while we add the remaining 30% through domain knowledge and context.
The result is a partnership where AI handles the heavy lifting, and humans ensure precision and quality. It’s not about replacing professionals; it’s about enhancing collaboration so teams can focus on strategy, creativity, and decision-making, the work that truly drives value.
Empowering Every Role in the Project Lifecycle
This AI-assisted workflow has improved collaboration across our teams:
- Functional Consultants capture requirements more efficiently.
- Project Managers gain instant visibility into deliverables and ownership.
- Developers receive ready-to-use backlog items with meeting context.
Every issue is traceable back to its source conversation — ensuring transparency, accountability, and continuous improvement.
From Internal Experiment to Industry Insight
Our experiment began internally, but the outcome resonates far beyond a single project.
Across industries, teams face the same challenge: hours of discussions that rarely turn into structured actions.
This approach can create impact across sectors like:
- Information Technology: Converting sprint discussions, requirement workshops, and architecture reviews into ready-to-execute backlog items.
- Healthcare: Summarizing clinical workflow discussions into transformation tasks.
- Education: Turning curriculum meetings into structured learning backlogs.
- Manufacturing: Translating operational discussions into process optimization items.
No matter the industry, the principle remains the same:
AI helps us turn conversations into clarity.
Journey as an AI Frontier Firm
At Mazik Global, we are committed to establishing ourselves as an AI Frontier Firm, where every team member, beyond just developers, is empowered to work confidently with AI.
AI isn’t just about coding faster.
It’s about transforming how we collaborate, capture knowledge, and deliver impact.
Sometimes, the most powerful innovations begin with a simple question:
“What if AI could turn our messy transcripts into a backlog we can actually use?”
Conclusion
The first time we watched Copilot transform a raw transcript into structured backlog items, one thing became clear:
AI is not just about automation; it’s about alignment.
It bridges the gap between what we discuss in meetings and what we deliver.
In an era where every organization is striving for speed and clarity, this is not just a productivity boost; it’s a new way of working.
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