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), and GitHub. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

Prompt library with version history for managing prompts at scale

User highlights the difficulty of managing a large number of prompts (e.g., 200+), leading to confusion about versions, changes, and storage. They suggest that 'building a prompt library with version history' is crucial for advanced prompt engineering and implicitly request a feature or tool to organize and manage prompts at scale.

Original Source

@@promptmanager_tech | 1 pts

Great breakdown! These 21 prompts are a solid foundation, especially for anyone just getting started with GPT-5. One thing I'd add from personal experience — the real challenge doesn't hit at prompt #20, it hits at prompt #200. That's when the chaos starts: which version of this prompt actually worked? What changed after the last model update? Which tab did I save it in? Building a prompt library with version history is the next level after mastering prompt engineering itself. Are you planning a video on organizing and managing prompts at scale?

Discussion

Loading comments...