OutSystems ODC AI Mentor

OutSystems Mentor marks a significant advancement in the software development landscape, leveraging Generative AI (GenAI) to enhance productivity and innovation.

๐Ÿญ. ๐—”๐—ฐ๐—ฐ๐—ฒ๐—น๐—ฒ๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ ๐—ฃ๐—ฟ๐—ผ๐—ฐ๐—ฒ๐˜€๐˜€
GenAI dramatically speeds up the development lifecycle by automating routine tasks, allowing teams to focus on high-impact work. This not only reduces time-to-market but also enhances overall efficiency in delivering applications.

๐Ÿฎ. ๐—˜๐˜…๐—ฝ๐—ฎ๐—ป๐—ฑ๐—ฒ๐—ฑ ๐—œ๐—ฑ๐—ฒ๐—ฎ ๐—ฃ๐—ผ๐—ผ๐—น
With GenAI, the potential for creative solutions expands beyond human limitations. By generating diverse ideas and prototypes from simple prompts, Mentor fosters innovation, leading to more creative and effective products.

๐Ÿฏ. ๐—›๐—ถ๐—ด๐—ต-๐—ค๐˜‚๐—ฎ๐—น๐—ถ๐˜๐˜† ๐—–๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น
The integration of GenAI ensures that applications meet high standards of quality and compliance. The automation of testing and validation processes contributes to consistent output, minimizing the risk of errors.

๐Ÿฐ. ๐—˜๐—ป๐—ต๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฑ ๐—–๐—ผ๐—น๐—น๐—ฎ๐—ฏ๐—ผ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป
Mentor orchestrates multiple agents that work together seamlessly. This collaborative approach improves communication among development teams and stakeholders, facilitating faster iterations and refinements.

๐Ÿฑ. ๐—š๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ป๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†
OutSystems Mentor addresses governance concerns inherent in AI by maintaining robust oversight throughout the development process. This ensures that applications not only innovate but also adhere to organizational standards and regulations.

๐Ÿฒ. ๐—™๐—ผ๐—ฐ๐˜‚๐˜€ ๐—ผ๐—ป ๐—ฆ๐˜๐—ฟ๐—ฎ๐˜๐—ฒ๐—ด๐—ถ๐—ฐ ๐—ช๐—ผ๐—ฟ๐—ธ
By handling routine tasks and simplifying complex processes, Mentor allows developers to concentrate on strategic aspects of application design and performance optimization, ultimately driving greater business value.

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Further reading

Speed Without the Sprawl

Leveraging OutSystems' rapid development strengths, our team achieves true Agile development, focusing intensely on user requirements. However, requirements are never fixed; they take time to refine within the project's cycle. If a developer simply builds projects based on the initial requirements, it leads to significant rework when those requirements are inevitably revised. This creates serious technical debt that can derail a project's schedule. To combat this, we strictly follow the OutSystems Canvas Design architecture to define each module's usage and content. We generalize logic into foundational modules, optimizing reusability and providing high adaptability when requirements change. This approach allows us to eliminate complicated dependenciesโ€”avoiding the deployment nightmares that plague monolithic systems. The Real-World Challenge: "The Spaghetti Monolith" Weโ€™ve all seen it. A project starts fast. The "Idea-to-App" time is record-breaking. But as sprints pass and requirements evolve, the "interest rate" on technical debt spikes. Suddenly, changing a simple UI element breaks a core business process because the logic was trapped inside the screen. Deployment becomes a "big bang" event where everything must go live at once because of circular dependencies. In our team, we don't just "code fast"; we architect for resilience. Our Solution: The 4 Layer Canvas Strategy We treat the 4 Layer Canvas not just as a suggestion, but as our structural imperative. Here is how we use it to handle volatile requirements:  Isolating Volatility (End-User Layer): We keep our User Interfaces (UI) and interaction logic in the End-User Layer. This layer is highly volatileโ€”it changes constantly based on user feedback. By isolating it, we can redesign a "Customer Portal" without risking regressions in our core business rules.Stabilizing Business Logic (Core Layer): We abstract our entities and business rules into the Core Layer. This is the backbone of our factory. Whether the data is accessed by a Mobile App, a Web Portal, or a Timer, the validation rules remain consistent. This promotes the "Don't Repeat Yourself" (DRY) principle.Enabling Independent Deployments: By using Service Actions (Weak Dependencies) in our Core layer, we decouple our modules. This allows different squads to deploy changes independently without forcing a factory-wide refreshโ€”a critical enabler for our CI/CD pipelines.The Governor: AI-Driven Architecture How do we ensure we stick to these rules when moving at Agile speeds? We don't just rely on manual code reviews; we use the AI Mentor System. This tool acts as our automated architect. It scans our entire factory to detect architectural violations that humans might miss, such as: Upward References: Preventing foundational libraries from depending on business logic.Side References: Ensuring our End-User apps don't tightly couple with one another.Circular Dependencies: Identifying the "deadly embrace" between modules that locks deployments.The AI Mentor System quantifies this debt, allowing us to pay it down proactively before it hinders our release velocity. Join a Team That Values Architecture In our Taiwan office, we believe that low-code doesn't mean "low-architecture." We are building resilient, composable enterprise ecosystems that can scale. If you are a developer who cares about structural integrity, clean code, and mastering the art of OutSystems architecture, we want to hear from you. 

๐—ก๐—ฒ๐˜„ ๐—ฅ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฒ๐˜ƒ๐—ฎ๐—น ๐—”๐˜‚๐—ด๐—บ๐—ฒ๐—ป๐˜๐—ฒ๐—ฑ ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป (๐—ฅ๐—”๐—š) ๐—”๐—œ ๐—š๐˜‚๐—ถ๐—ฑ๐—ฎ๐—ป๐—ฐ๐—ฒ

Germany's Data Protection Conference just released comprehensive guidance on AI systems with Retrieval Augmented Generation (RAG) - a game-changer for organizations implementing AI governance under ISO 42001.Key Compliance Requirements:๐Ÿ”ŽData Accuracy - Enhanced Large Language Model (LLM) responses but error accountability remains๐Ÿ”ŽTransparency - Improved document traceability within RAG knowledge bases๐Ÿ”ŽPurpose Limitation - Technical implementation through client/functional separation๐Ÿ”ŽData Minimization - Strategic vector database content management๐Ÿ”ŽData Subject Rights - Full rights coverage across prompts, outputs, and databases๐Ÿ‘‰ Why This Matters for ISO 42001:RAG systems are becoming mainstream for internal chatbots and enterprise AI. The Data Protection Conference guidance directly aligns with ISO 42001's requirements for AI risk management, data governance, and algorithmic accountability.Organizations deploying RAG technology must now ensure their AI management systems comply with both German data protection standards and international ISO 42001 frameworks.Our cybersecurity and privacy consultation expertise helps organizations navigate these complex requirements, ensuring your RAG implementations meet regulatory standards while maximizing business value.