On April 23, 2025, Modern Requirements hosted a powerful live webinar showcasing Copilot4DevOps V5, focusing on its flagship innovation—AI Chat. With attendees joining from across the globe, the session explored how conversational AI is simplifying work item management, document generation, and backlog analysis directly within Azure DevOps.
Welcome & Introduction: Setting the Stage
Shihan Fernando, SVP of Global Sales, opened the session by highlighting Modern Requirements’ long-standing collaboration with Microsoft and the evolution of Copilot4DevOps from prompt-based AI to a fully conversational experience in V5.
He emphasized that with V5, teams can now:
- Ask questions directly inside Azure DevOps,
- Manage work items using natural language,
- Create diagrams, and
- Eliminate the need to switch between tools.
Fireside Chat: AI’s Next Leap in DevOps
Asif Sharif, Founder & CEO, joined Shihan for an insightful conversation on how V5 bridges the gap between users and their DevOps data. They reflected on customer feedback and the shift from static AI prompts to real-time, natural language interactions that mimic how team members speak and collaborate.
Key themes included:
- Making DevOps workflows more intuitive,
- Reducing rework through smarter planning,
- Empowering non-technical stakeholders with accessible AI tools.
💡 Feature Highlights Through Live Demos
The heart of the session was a series of 5–7 minute demos by different team members, each showcasing a core use case of AI Chat and other V5 capabilities.
Demo 1: Conversational Chat + Diagramming
Asif demonstrated how AI Chat can turn a simple conversation into structured work items. He described a domain, had Copilot4DevOps generate a feature and user stories, and visualized them as a process diagram—all within Azure DevOps.
Key takeaway: No more jumping between planning tools and whiteboards. One chat, many deliverables.
Demo 2: Document Ingestion
Denesh uploaded a document and showed how Copilot4DevOps could ingest the content and generate relevant features and requirements directly into the backlog.
Key takeaway: Teams can now leverage legacy specs, PDFs, or meeting notes to build actionable work items—automatically.
Demo 3: Data-Driven Work Items
Aiesha walked attendees through analyzing work items against a chosen framework (like INVEST), letting the AI assess quality and make suggested updates in bulk.
Key takeaway: Raise the bar for requirements quality without manual reviews or spreadsheets.
Demo 4: QA Assistant Use Case
Although the feature is still evolving, Hira touched on how the AI can support QA by generating relevant test questions, acceptance criteria, and even highlighting edge cases based on existing stories.
Key takeaway: Copilot4DevOps is not just for BAs—QA teams benefit too.
Poll Results & Audience Insights
During the session, two live polls captured the audience’s pulse:
- Opening Poll: Most attendees were still early in their AI journey—either exploring or just getting familiar.
- Closing Poll: When asked about their favorite AI Chat use case, “All of the above” dominated—showing the versatility and wide appeal of Copilot4DevOps V5.
Closing Thoughts: This Is Just the Beginning
Asif closed with a vision for the future—where AI becomes not just an assistant but a collaborative partner in every stage of DevOps. With V5 now live, users can harness Copilot4DevOps to reduce manual effort, improve accuracy, and turn conversations into deliverables.
Ready to Experience It Yourself?
Copilot4DevOps V5 is now available in the Azure DevOps Marketplace.
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