5.3K members. The best post we have captured here reached 21 upvotes, which works out to 4 per 1,000 members.
The mix of post types among everything we have captured. Posting a link where almost nothing but images lands is wasted effort, and this is the fastest way to see it.
Flairs are the community's own categories, and the closest thing a subreddit has to telling you what it wants.
The biggest posts we have captured here. Links go to the original on Reddit.
Anyone maintaining a real agent regression suite, not just eval prompts in a spreadsheet?.
my friend used Claude to rank 200 resumes. the top candidate bombed the first call.
How big does an eval dataset actually need to be?
Best AI Agent Evaluation Tools in 2025 - What I Learned Testing 6 Platforms
Bifrost: An LLM Gateway built for enterprise-grade reliability, governance, and scale(50x Faster than LiteLLM)
How are AI product managers looking at evals (specifically post-evals) and solving for customer outcomes?
Who are the developlers here who care about AI quality?
Ran the same question 3 ways against a knowledge graph. Retrieved the same 90 entities and triples each time. LLM output still varied. That's the fin…
How do you evaluate an AI agent that gives fuzzy, probabilistic outputs?
Our evals were green for a month straight while real users were quietly getting worse answers
Within four times the member count either way, so the comparison is fair. Sorted by upside.
ViralHunt tracks Reddit and eight other networks, records how every post grows, and puts what is taking off in front of your team in one list.
Start free →Every figure here is what ViralHunt has captured from r/AIQuality, not everything the community has ever posted. We deliberately do not publish an average score: our sample is weighted toward a community's best posts, so an average would be flattering and wrong. Peak per 1,000 members is computed the same way for every community listed. See how we measure.