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.

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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.

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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.

Standardize agent communication, validation, and trust mechanisms

User highlights the current issue of teams reinventing basic agent communication, action validation, and trust-building mechanisms in isolation, suggesting a need for standardized approaches within frameworks or the ecosystem.

Original Source

@Alex Cinovoj | 213 pts

Everyone's obsessing over AI agent frameworks. After shipping 27 agents in production, here's the only tech stack that matters. 🧠 Foundation Models Your agent's brain. Pick one. Master it. GPT for reasoning. Claude for writing. Stop model hopping. 📊 Data Storage Vector DBs and memory systems. Get this wrong? Your agent forgets everything or remembers test data in production. (Cost me $3K to learn that one) 🎯 Agent Development Frameworks For orchestration and workflows. But frameworks don't ship products. You do. One for complex flows. That's it. 🔍 Observability When your agent breaks at 3 AM, you need logs. Not philosophy. Logs. Monitor everything. Debug faster. 🔧 Tool Execution APIs, browsers, external systems. Wrap them early. Test everything. Least-privilege access. Always. 💾 Memory Management Short-term: Current task only. Long-term: What actually matters. Expiry and resets: Mandatory. The brutal truth? Most teams build the stack backwards. They start with frameworks, add models, then panic about memory and observability when things break. Start with observability. End with frameworks. Ship what works. My everyday agents Lovable Cursor, Manus AI and Gamma. Thanks Alex Xu and ByteByteGo for amazing visual. What's missing from this stack that you've learned the hard way?

Discussion

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