RequestHunt is a community-driven platform that collects and curates feature requests from X (Twitter), Reddit, and GitHub. We help product teams discover what features real users are asking for, making it easier to validate product ideas and prioritize feature development based on actual user demand.

How does RequestHunt collect feature requests?

RequestHunt uses AI-powered extraction to automatically collect feature requests from social media platforms including X, Reddit, and GitHub. The platform monitors discussions, issues, and posts to identify genuine user feature requests, extracting key information like the requested feature, product mentioned, and user sentiment.

Who uses RequestHunt?

RequestHunt is used by product managers, founders, developers, and product teams who want to discover what features real users are requesting. It's particularly valuable for startups looking to validate ideas, established companies prioritizing their roadmap, and developers building products that solve real user problems.

Is RequestHunt free to use?

Yes, browsing and searching feature requests on RequestHunt is completely free. We also offer API access for developers who want to integrate feature request data into their own applications. Check our pricing page for API plan details.

How often is RequestHunt data updated?

RequestHunt continuously collects feature requests from Reddit, X (Twitter), GitHub, YouTube, LinkedIn, and Amazon. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

Enable AI agents to work natively within enterprise systems for secure insights and real-time compli

The user expresses excitement for orchestration capabilities that allow AI agents to operate natively within existing enterprise systems. This would enable secure surfacing of insights and real-time streamlining of compliance, addressing a key need for enterprise adoption.

Original Source

@Melissa Gordon | 69 pts

You’ve probably heard a lot about AI agent orchestration, but it’s not always easy to contextualize it. Alan Nichol and our PMM team have launched a blog series to simplify how to think about orchestration and how Rasa is tackling this. The first post explains Rasa’s role as an orchestrator, coordinating multiple systems and skills while maintaining context. It illustrates how properly working with MCP (Model Context Protocol) and A2A (Agent2Agent) protocols enable this by showing a banking agent that can help someone find, buy, and finance a car. This highlights the importance of designing conversations where users feel like they are interacting with a single agent in one, ongoing conversation. It’s not just about creating intelligent agents anymore, but also bringing them together to deliver a cohesive and consistent experience. Link found in the comments. You can also sign up for our MCP webinar on September 25 by following the link in the article.

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