This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Agenlus
Watch a neural net learn to fight, race and drive wrong way
Agenlus is a browser-based RL training platform — no install, no setup, just open and train. Watch your neural net stumble, backtrack, and finally figure it out. Then throw it into battle against someone else's. What you can do: Train agents on CartPole, MountainCar, and battle environments — powered by WebGPU, running fully in your browser Compete on the global leaderboard Build your own environments with the Env Builder IDE No PhD required. No GPU bill. Just a browser.
Hey PH!
I'm Youngseong, an independent AI researcher who built Agenlus solo.
I got tired of RL being stuck behind expensive GPUs and complex setups. So I built a platform where anyone can train neural nets directly in the browser — powered by WebGPU and Pyodide, zero install required.
The fun part? You can watch your agent fail spectacularly at first, then slowly figure things out. Then challenge someone else's trained agent to a battle.
Would love brutal feedback — what environments do you want to see next?
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About Agenlus on Product Hunt
“Watch a neural net learn to fight, race and drive wrong way”
Agenlus was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #129 on the daily leaderboard. Agenlus is a browser-based RL training platform — no install, no setup, just open and train. Watch your neural net stumble, backtrack, and finally figure it out. Then throw it into battle against someone else's. What you can do: Train agents on CartPole, MountainCar, and battle environments — powered by WebGPU, running fully in your browser Compete on the global leaderboard Build your own environments with the Env Builder IDE No PhD required. No GPU bill. Just a browser.
Agenlus was featured in Education (78.7k followers), Developer Tools (514k followers) and Artificial Intelligence (470.9k followers) on Product Hunt. Together, these topics include over 200.8k products, making this a competitive space to launch in.
Who hunted Agenlus?
Agenlus was hunted by YoungSeong Kim. 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 Agenlus stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
YoungSeong Kim