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AI Requirements Management and Context Setting with OpenRose

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  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...

Lot 01 - Why and What is Requirements Management - Collection of Short Videos!

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  We tend to do things before we read REQUIREMENTS If you like this short clips then we request you to Please Share this page link with others. Distance between Engineer and Customer is too High

Rethinking Requirements: Why Continuous Requirements Management Is Critical for Product Success

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Most teams treat requirements as a one-time task: gather them at the beginning, write them down in a document, and move on to design and development. But in reality, requirements evolve—and if your process doesn’t evolve with them, your product risks becoming unstable, unmaintainable, and misaligned with user needs. Here’s why requirements management—not just requirements capture—is essential. 1. Requirements Are Living Knowledge, Not Static Checklists During development, teams often discover better ways to implement a feature: A developer finds a more efficient algorithm A UX designer improves the user flow An architect refactors the system for scalability These changes modify the original requirement—sometimes subtly, sometimes significantly. If these changes aren’t reflected in the requirements system: Test cases become outdated Maintenance teams lose context Future upgrades risk breaking functionality Requirements must be updated to reflect reality, not just in...

Requirements Management - Import Baseline Snapshot Data

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Welcome back to another hands-on demo of OpenRose, a FREE and Open-Source requirements management application that’s helping teams structure, trace, and manage their requirements with precision and flexibility. In this article, we’ll explore one of OpenRose’s most powerful features: importing baseline data . Using a real-world example from a Charity Fundraising project, we’ll walk through how to export and import baseline records, item types, and individual requirements—while preserving hierarchy, traceability, and scope control. Understanding Baselines in OpenRose Baselines in OpenRose are snapshots of your requirements at a specific point in time. They’re immutable by design, except for the ability to include or exclude specific requirements from the baseline scope. When exporting baseline data, you’re not simply backing up a frozen view—you’re preparing it for re-import into a live project , where it can be reused, reorganized, or archived. Depending on what you export, OpenR...

Requirements Management - Import Data

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Introduction Hello. Today is an exciting day because we now have an import capability to bring requirements data into OpenRose. This is an important addition, as users can now collaborate more effectively by working offline in their own environments, then exporting the required data — including traceability — and sending it to someone else to review, provide feedback on, or incorporate into a centralized repository. Once imported into the repository, the data can be managed further from that point onwards. About the Feature This feature was requested by OpenRose users and is documented on the project’s wiki. If you visit the repository at http://github.com/openrose , you will find the common area where users can download the application or view the source code, along with documentation. In the OpenRose wiki, we have outlined the concept of importing data into OpenRose. The purpose of allowing users to import data is to enable them to restore requirements data that was previousl...

Requirements Management - Export Data from OpenRose

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  Hello again, and thanks a lot for joining this session. Today, we're going to talk about the latest release—version 0.2.0-32 —of OpenRose. In this particular version, we’ve delivered a significant new capability requested by our users: the ability to export data from OpenRose . Here are the release notes. Version 0.2.0-32 is all about supporting the export of data in JSON format , including requirements breakdown structure. Now, we support exporting: Project requirements ItemzType data Requirements Itemz data Baseline data Baseline Requirements ItemzType data Baseline Itemz data All of these are now supported in the latest version. Let me start by showing you the user story we received, visible in the project area. It was a simple one: “As a user of the OpenRose tool or application, I want to be able to export project Requirement ItemzType or Requirement Itemz to the file system so that I can share it with others or import it into another OpenRose repository.”...

Build What Matters: A Human-Centered Path from Requirements to Results

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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...

AI and the Challenge of Context Setting: Are We Helping Them More Than They Help Us?

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  Artificial Intelligence has transformed industries by offering automation, improved efficiency, and intelligent decision-making support. AI-powered assistants are positioned as tools that streamline workflows, providing structured insights, breaking down complex requests, and identifying potential impacts quickly.   However, the reality of working with AI assistants is not always smooth. While AI promises efficiency, using it effectively often requires significant human effort .   The assumption is that AI should eliminate inefficiencies and enhance productivity, but in many cases, businesses find themselves spending considerable time providing AI with the necessary context  to function well. Instead of AI autonomously understanding a situation, users must input structured data every session, feeding AI the same critical details repeatedly. This raises an important question:   Is AI truly helping businesses become more efficient, or are humans s...

From MVP to Market Leader: The Critical Role of Requirements Management

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  MVP - Minimum Viable Product / Minimal Viable Product. Defining Product Requirements: The Backbone of a Strong MVP Too often, MVPs are seen as "quick and dirty" prototypes—something rushed out just to test an idea. But in reality, a well-defined MVP requires a structured approach to product requirements to ensure quality, scalability, and market fit. Without proper requirements management, MVPs can quickly become chaotic, leading to wasted resources and flawed assumptions. Why Product Requirements Matter for MVPs Even at the MVP stage, companies must clearly define: ·           Core functionalities that will be tested. ·          Technical constraints & feasibility—balancing speed with quality. ·          Target audience expectations to ensure meaningful feedback. ·          Regulatory & compliance ...