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Agenomics
Evaluate AI Agents. Build Real-World Evidence.
Agenomics is an open-source methodology and toolkit for evaluating AI agents through structured agent genomes, Trust Score, Compatibility Score, behavioral drift monitoring, and real-world evidence collection. Connect your agents, record observations and incidents, and test whether declared trust actually corresponds to behavior in production.
AI agents are becoming more autonomous — but our ability to measure whether we should trust them hasn't kept up.
We built Agenomics around a simple question:
**Can an AI agent's declared trust level be tested against how it actually behaves in the real world?**
Agenomics gives agents a structured genome, calculates Trust and Compatibility scores, monitors behavioral drift, and — starting with v0.7.0 — provides persistent evidence collection through EvidenceStore.
But there is an important part we cannot manufacture:
**real-world data.**
We are looking for developers running real AI agents who are willing to connect them to Agenomics, collect observations and incidents, and help test whether trust scores actually correspond to production behavior.
No user conversations need to be sent to Agenomics.
Your agent is the experiment.
Your data is the evidence.
Agenomics is the methodology.
I'd love to hear what you think — especially what signals you would use to measure whether an AI agent is actually trustworthy.
About Agenomics on Product Hunt
“Evaluate AI Agents. Build Real-World Evidence.”
Agenomics was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #5 on the daily leaderboard. Agenomics is an open-source methodology and toolkit for evaluating AI agents through structured agent genomes, Trust Score, Compatibility Score, behavioral drift monitoring, and real-world evidence collection. Connect your agents, record observations and incidents, and test whether declared trust actually corresponds to behavior in production.
On the analytics side, Agenomics competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Agenomics performed against the three products that launched closest to it on the same day.
Who hunted Agenomics?
Agenomics was hunted by Дмитрий Андреянов. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Agenomics including community comment highlights and product details, visit the product overview.
Дмитрий Андреянов