Feature Requests

Enhancing AI Collaboration with Advanced Control Mechanisms
For professionals and organizations seeking to optimize AI-driven collaboration, introducing advanced control mechanisms for AI Helpers can significantly enhance operational efficiency. Imagine an AI interface where users can specify the exact number of ideas they wish to generate, predefine the context or domain of intelligence—such as marketing strategy, technical documentation, or data analysis—and enable a specialized “vacation mode” that pauses or throttles AI interactions during high-priority human workflows. By integrating machine learning and natural language processing, the system could adapt dynamically to user behavior. For example, if a project manager frequently requests three to five strategic suggestions for product launches, the AI could learn this pattern and proactively adjust idea generation without manual input. Similarly, context filters could leverage semantic understanding to ensure that AI outputs remain domain-relevant, minimizing irrelevant suggestions in enterprise environments. Vacation mode could further extend AI utility by intelligently deferring non-critical insights, aggregating them into digestible summaries, or scheduling idea delivery during periods of lower cognitive load. Over time, predictive analytics could identify when the user is most receptive to input, personalizing engagement schedules while reducing distractions. This specialized approach empowers organizations to harness AI capabilities for high-value tasks, streamline communication in crowded digital workspaces, and create a framework for human-centric AI collaboration that prioritizes relevance, timing, and productivity.
0
·
Automations
Enhancing Sintra’s Brain AI: Key Steps for Auditability and Efficiency
There needs to be a way to audit the brain AI in Sintra. I’ve been receiving daily questions from the AI Helpers that repeatedly revolve around the same topic. Unfortunately, there’s no rulebook outlining how the brain AI operates, nor are there any parameters to set or agentic workflows. Implementing these features would greatly help users manage their tasks effectively. Additionally, the AI Helpers should be responsible for creating tasks, reminders, notes, and memos for all other helpers. Furthermore, they should be able to communicate with one another both individually and automatically. I’m concerned that we’re not making progress with this platform. To address these concerns with the brain AI in Sintra, several steps should be implemented: Auditability: Establish a formal auditing mechanism for the brain AI. This includes detailed logging of interactions, decision-making processes, and task-handling behavior. Operational Guidelines: Develop a rulebook that defines how the brain AI operates, including its parameters, boundaries, and expected agentic workflows. This will help ensure consistency and transparency in its actions. Expanded AI Helper Capabilities: Enable AI Helpers to autonomously create and manage tasks, reminders, notes, and memos for other helpers. Allow them to communicate with one another both individually and automatically to streamline coordination. Progress Monitoring: Implement dashboards or regular reports to track performance, identify bottlenecks, and measure progress in task completion. User Empowerment: Provide users with tools to manage, customize, and override AI behavior when necessary, improving their overall experience and trust in the platform. By following these steps, Sintra can improve its AI ecosystem, enhance productivity, and ensure the platform evolves more effectively toward its intended goals.
0
·
Automations
Load More