
Software Development Redmond, Washington
The YouTube episode, produced by Microsoft, features Hitachi’s Power Platform solution architect Ramiro Melgoza explaining how Generative Pages reshape app creation. In this installment of the "Keeping It Real" series, Melgoza traces his path from early programming and SharePoint work to building impactful, low-code solutions for organizations. He demonstrates how natural language prompts combine with code to generate and refine user interfaces, and he highlights a live multiplayer demo to show real-time collaboration. Overall, the episode frames the technology as a practical tool that brings creativity and speed to Power Platform builders.
Moreover, the presentation balances a demo-driven approach with design thinking, emphasizing outcomes over novelty. The host, Leon Welicki, guides the conversation to surface both the mechanics and the strategic choices behind using AI-generated pages. Consequently, viewers get a blend of hands-on examples and higher-level guidance on when to apply these tools. This positions the episode as useful both to developers new to the space and to architects who evaluate tradeoffs in enterprise projects.
Melgoza demonstrates how a developer can create a working app by describing desired behavior in natural language and then refining generated components with traditional tooling. The demo shows that Power Apps components, data bindings, and UI elements can be scaffolded rapidly, which reduces initial development time and lowers the barrier for prototyping. He also highlights how edits and iterations are straightforward, since generated pages remain editable and link back to standard Power Platform artifacts. As a result, teams can iterate faster while retaining the option to add custom logic where needed.
Importantly, the episode showcases built-in primitives for real-time collaboration, such as cursor sharing and state synchronization, that support multiplayer interactions without heavy custom infrastructure. These features make it possible to build shared canvases, checklists, and dashboards where multiple users see and act on the same state in near real time. However, Melgoza notes that some scenarios will still require backend tuning for scale and resilience. Therefore, while the tools accelerate development, planners must still design for concurrency and persistence.
The live multiplayer demo stands out because it highlights both technical possibilities and user experience considerations. During the demo, multiple participants edit a shared app simultaneously and observe changes in real time, illustrating how Generative Pages can support collaborative workflows that previously needed bespoke engineering. Furthermore, the example shows pragmatic handling of user sessions and simple conflict resolution strategies, which are essential for a smooth experience. This demo underlines that generative approaches can power interactive applications used by teams rather than only single-user tools.
Nonetheless, real-time features bring tradeoffs around performance and complexity, especially when many users interact on the same resource. Architects must weigh the benefit of immediate synchronization against added costs for infrastructure, data throughput, and testing under load. In practice, this means prioritizing where live collaboration adds measurable value and implementing progressive enhancement so less-demanding users avoid unnecessary overhead. Consequently, teams should prototype with realistic concurrency levels to uncover scaling challenges early.
While AI-assisted generation speeds up prototyping, it introduces new risks that teams must manage, including possible inaccuracies in generated logic and the need for governance. Melgoza stresses starting from the business value rather than from the technology itself, because over-reliance on automated generation can lead to brittle solutions if the underlying assumptions differ from reality. Additionally, integrating AI agents into existing apps requires careful attention to data privacy, permission models, and operational ownership. Therefore, organizations must balance automation gains with rigorous review processes and clear accountability.
Another key challenge is debugging and maintainability: generated code can be harder to trace back to original intent if teams skip documentation or testing. To mitigate this, developers should treat generated artifacts as first-class code: add comments, include tests, and instrument telemetry for user behavior and errors. Moreover, real-time features call for robust session handling and conflict resolution, which often demand explicit design choices rather than default behaviors. Ultimately, the most sustainable approach combines the speed of generation with disciplined engineering practices.
For teams exploring Generative Pages, Melgoza recommends starting with small, value-focused pilots that demonstrate the business impact of collaboration features. He advises iterating quickly on prototypes to gather real user feedback, and then hardening the most valuable scenarios with conventional engineering controls. In addition, using AI agents as assistants — to suggest UI changes or automate repetitive tasks — can improve productivity when paired with human review and domain expertise. Thus, builders should view these agents as amplifiers of human skill rather than replacements.
Finally, the episode encourages community involvement and continuous learning, since patterns for effective use are still emerging across organizations. By combining hands-on experimentation with governance, monitoring, and clear success criteria, teams can capture the speed advantages of AI-assisted design while managing the technical and organizational tradeoffs. In short, the video from Microsoft offers a pragmatic roadmap: focus first on measurable value, then scale responsibly as systems and teams mature.
Ramiro Melgoza, Generative Pages, multiplayer experiences, multiplayer game development, real-time multiplayer web, generative AI for games, web multiplayer architecture, Keeping It Real podcast