Behavioral learning that makes AI agents better over time
Reflexio makes AI agents better with every interaction. When users correct an agent, a path fails, or something works particularly well, Reflexio turns that experience into behavior the agent can reuse next time. Instead of leaving valuable lessons buried in logs, your agent continuously learns what to repeat and what to avoid — with every learning visible, testable, and reversible. Reduce task failure rate by more than 30%, while saving tokens by more than 60%.
Hey Product Hunt 👋 I'm Yi, co-founder of Reflexio. Before starting Reflexio, I was tech lead in Meta and adjunct professor at University of Washington teaching ML and business applications.
Today we're launching Reflexio: a learning platform that makes your AI agents fail less and burn fewer tokens, by learning from what actually happens in production.
Here's what got us started: people use AI agents every day, but agents never actually get better with use. Even with memory, an agent that failed a task yesterday will fail the same way today, across different users — because nothing connects what happened in production back to how the agent behaves next time. The online learning loop just isn't there.
We learned firsthand that closing that loop manually — reading traces, spotting failures, rewriting prompts — is a painful, never-ending job. Reflexio autonomously observes your agent's live traces, learns from successes, failures, and user corrections, and continuously optimizes behavior. No manual tuning.
The results? In our case studies, agents with Reflexio:
🎯 Cut task failure rate by 36%
💸 Reduced token usage by 57%
📈 Improved response quality in 47% of interactions, with negligible regressions
Try it today: sign up free at reflexio.ai and get 30 days of Pro on us.
About Reflexio on Product Hunt
“Behavioral learning that makes AI agents better over time”
Reflexio launched on Product Hunt on September 5th, 2026 and earned 142 upvotes and 23 comments, earning #2 Product of the Day. Reflexio makes AI agents better with every interaction. When users correct an agent, a path fails, or something works particularly well, Reflexio turns that experience into behavior the agent can reuse next time. Instead of leaving valuable lessons buried in logs, your agent continuously learns what to repeat and what to avoid — with every learning visible, testable, and reversible. Reduce task failure rate by more than 30%, while saving tokens by more than 60%.
On the analytics side, Reflexio competes within SaaS, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Reflexio performed against the three products that launched closest to it on the same day.
Who hunted Reflexio?
Reflexio was hunted by fmerian. 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 Reflexio including community comment highlights and product details, visit the product overview.
fmerian
Hey Product Hunt 👋
I'm Yi, co-founder of Reflexio. Before starting Reflexio, I was tech lead in Meta and adjunct professor at University of Washington teaching ML and business applications.
Today we're launching Reflexio: a learning platform that makes your AI agents fail less and burn fewer tokens, by learning from what actually happens in production.
Here's what got us started: people use AI agents every day, but agents never actually get better with use. Even with memory, an agent that failed a task yesterday will fail the same way today, across different users — because nothing connects what happened in production back to how the agent behaves next time. The online learning loop just isn't there.
We learned firsthand that closing that loop manually — reading traces, spotting failures, rewriting prompts — is a painful, never-ending job.
Reflexio autonomously observes your agent's live traces, learns from successes, failures, and user corrections, and continuously optimizes behavior. No manual tuning.
The results? In our case studies, agents with Reflexio:
🎯 Cut task failure rate by 36%
💸 Reduced token usage by 57%
📈 Improved response quality in 47% of interactions, with negligible regressions
Try it today: sign up free at reflexio.ai and get 30 days of Pro on us.