Glass turns AI anomalies into automated improvements through an infinite feedback loop that detects misbehaviors and feeds them into continuous evaluations to refine your agent.
Hey! Alex building Glass here. I've built LLM solutions and AI Agents for the last 3 years and every singe project, even on every different markets, always had the same issues : some crazy issues would happen in prod when interacting with real users, which I'd have never imagined during development, so I had to do this back-and-forth between monitoring and evals all the time. With the team at Glass, we're now fixing this problem. Glass catches your AI anomalies in production and automatically turns them into evaluations. We also added Signals in other platforms than Slack; because we never understood why existing tools only support this. Open to all feedback!
Glass started from a frustration we kept running into while building AI agents. At first everything looked fine: we had logs, traces, dashboards, metrics. The system was “observable.”
But whenever something went wrong, we still had to manually dig through thousands of traces trying to understand things like:
Why did the agent hallucinate here?
Why is it so confidently wrong?
Is this a new issue or something that’s been happening for weeks?
Traditional observability tells you what happened. With AI systems, the real question is whether the behavior was correct. So we built Glass. Glass is the full flywheel for AI agents. Instead of just collecting traces, it analyzes them and helps you understand where and why your agent failed.
With Glass you can:
Have all your anomalies detected in real time: behavioral drifts, hallucinations, loops, jailbreaking etc
Get insights on how your users are actually interacting with your agents
Receive daily digests to help you iterate and fix fast!
Turn all this knowledge into autonomous evaluations to constantly refine your product
The reality of AI today is that building the agent is the easy part. The hard part is making sure it behaves correctly in production.
Glass is built to help with exactly that.
Excited to get your feedback!!
It's finally out!
You can use Glass to fix your AI agents and ensure seamless, high-quality client interactions
About Glass on Product Hunt
“Continuous Improvement for your AI Agent”
Glass launched on Product Hunt on March 12th, 2026 and earned 91 upvotes and 6 comments, placing #36 on the daily leaderboard. Glass turns AI anomalies into automated improvements through an infinite feedback loop that detects misbehaviors and feeds them into continuous evaluations to refine your agent.
Glass was featured in Analytics (171.5k followers), Developer Tools (511.4k followers), Maker Tools (2.7k followers) and YC Application (31 followers) on Product Hunt. Together, these topics include over 83.3k products, making this a competitive space to launch in.
Who hunted Glass?
Glass was hunted by Alexandre Fournier. 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.
Want to see how Glass stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Alexandre Fournier
Hey! Alex building Glass here.
I've built LLM solutions and AI Agents for the last 3 years and every singe project, even on every different markets, always had the same issues : some crazy issues would happen in prod when interacting with real users, which I'd have never imagined during development, so I had to do this back-and-forth between monitoring and evals all the time.
With the team at Glass, we're now fixing this problem. Glass catches your AI anomalies in production and automatically turns them into evaluations.
We also added Signals in other platforms than Slack; because we never understood why existing tools only support this.
Open to all feedback!