🌷OpenRose

  For years, product teams have joked that “nobody reads long requirements documents.” But with the arrival of generative AI in every role — product, engineering, QA, design — the question “Who will read long requirements documents?” has changed completely. Today, the most consistent, reliable, and detail-oriented reader on your team is no longer a person. It’s AI .

  Managing requirements effectively is one of the most important aspects of project success. OpenRose, a free and open-source requirements management tool, makes this process easier by allowing you to export structured data along with traceability matrix  and visualize it using Mermaid diagrams . In this blog, we’ll walk through how to: Export requirements data from OpenRose Convert it into Mermaid flowcharts Include traceability links between requirements Use tools like Mermaid.live  or draw.io  or diagrams.net to create beautiful, shareable diagrams Step 1: Getting Started with OpenRose OpenRose is available at github.com/openrose . For this demo, we’ll use a Charity Fundraising Project as an example. The project contains three main item types: Pre-Fundraising Preparation Fundraising Event Execution Post-Fundraising Activities Each item type contains sub-items, and many of them are interlinked through traceability . For example: ...

  Welcome to OpenRose —a free and open-source requirements management tool available at github.com/openrose   In this blog, we’ll explore how OpenRose’s latest feature empowers users to collaborate with AI platforms like ChatGPT, especially when managing complex projects such as a Charity Fundraising initiative. Why Context Matters in AI Collaboration When working with AI—whether it's ChatGPT or any other platform—setting the right context is crucial. This process is known as context engineering or context provisioning , and it’s closely related to what many refer to as prompt engineering . Rather than overwhelming the AI with excessive or irrelevant data, context engineering ensures the AI receives just the right amount of information—no more, no less. This allows the AI to generate more accurate, relevant, and actionable responses. As AI systems evolve from simple prompt-based tools into sophisticated autonomous agents, context engineering becomes essential. It helps r...

In today’s fast-paced world of innovation, many projects don’t fail because of poor execution—they fail because they solved the wrong problem. Deadlines were met. Deliverables checked out. Yet users still shrugged. Why? Because traditional Requirements Management—though essential—often overlooks the context , empathy , and iteration needed to ensure solutions are relevant and resonant . It’s time to shift our mindset. To move from “building what was asked for” to “building what truly matters.” Reclaiming the Power of Requirements: Beyond the Checklist Requirements shouldn’t be treated as static checklists (or even a simple 3 liner "User Story"). They’re opportunities to: Clarify stakeholder intent Challenge assumptions early Set the stage for meaningful outcomes Capture decisions taken along the way When paired with principles from design thinking , Requirements Management becomes a dynamic, insight-driven practice. It’s not about adding red tape—it’s about unde...