Building a Community-Driven Testing Program for AI Search APIs

Muwen Xu — Thu, 30 Jul 2026 07:09:10 +0000

Hi everyone! 👋
We're the Developer Relations team at Querit, where we're building a Web Search API for AI agents and LLM-powered applications.
Over the past few months, we've talked with developers building AI agents, RAG applications, research assistants, monitoring tools, and browser automation workflows. One thing quickly became clear:
Building the API isn't the hardest part. Collecting meaningful developer feedback is.

We've launched a Discord-based onboarding and testing program for developers building AI applications that rely on fresh web information.
All developers are welcome to join and help us improve the product.

Getting started
If you want to poke at it, here is the simple work flow:

Join the Querit Discord:https://discord.gg/sYQaFSHxyU
Select the Developer role
Grab your 50,000 free API requests (link's in #try-querit — no card, no sales call)
Run /try-querit in #try-querit
Complete one successful search
Receive the Querit Verified Developer role

Verified developers get access to:

🧪 Querit API Lab
🚀 Early feature previews
🐞 Bug reporting & feedback channels
💡 Feature request discussions
🌟 Community showcase opportunities

What We're Actually Looking For
We're not simply looking for people to tell us whether the API is "good" or "bad."
We're interested in understanding how developers evaluate search quality in real AI applications.
For each testing round, we encourage contributors to share:

The query and parameters used
Expected and Actual result
A quality rating (1–5)
What works well and where it falls short
Screenshots or result snippets if helpful

Sometimes a "failed" search teaches us far more than a successful one.
That's exactly the kind of feedback we're hoping to collect.
Developers who consistently contribute useful reports can receive additional API credits, and improvements inspired by community feedback may be acknowledged in future product updates.

We'd love your input
This program is still evolving, and we're learning as we go.
If you've built AI agents or applications that rely on web search, we'd love to hear your thoughts:

How do you currently evaluate a Search API?
What kinds of edge cases or failure scenarios would you want to test?
What would make an API testing program genuinely valuable to you as a developer?

Useful reports can earn additional API request credits. Findings that lead to an actual product fix may also receive credit in the Querit Changelog.

If you'd like to participate, you can join our Discord community here:
https://discord.gg/sYQaFSHxyU
We're looking forward to building this program together with the developer community—and we'd love to hear how you'd improve it

DEV Community: Muwen Xu

Building a Community-Driven Testing Program for AI Search APIs