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).
Auto Learning Agents
Self-hosted AI agent OS with memory that actually learns
Auto Learning Agents is a free, open source OS for AI agents. Deep internal memory plus dynamic, session-less context: agents find the right context each turn, pick up where they left off, and get better at recurring work. Web UI for Claude, OpenAI, Gemini, or fully local with Ollama, with a file browser, code editor, and 40+ built-in tools. Background agents run while you are away. Built on Elixir/OTP, every agent is a supervised process that recovers from crashes. One Docker command and go.
Auto Learning Agents was originally my own internal tool, which became prebuilt Agent systems that I sold monthly, but as a solo developer I am done trying to sell things to people, the trust factor makes sense, plus sales is not something I enjoy so I streamlined it more, made it AGPL license (free to use, to distribute it you need a commercial license, such as hosting companies).
I vibe code everyday, from free software, new tools, web games, I am all over the place and like it this way (everyone wants to correct me lol). I run about 50 of my own sessions per day, most in the background so this tool lets you do that on your own server/computer, using your subscriptions since you are hosting it on your own machine.
Lots of tools, I had a lot that I removed as there were too many, so I have more I can add. Started with about 40, including a web browser bot, where claude can take over a headless browser for you, good for automation and extremely helpful in live website debugging. Screenshots are eyes for AI.
Internal memory system, local embeddings server but does more than vector searches. Automated task agents with structured scheduler, memory files and permissions settings. Full UI with file / coding editor, lets you read and edit files as claude/codex is editing them. Longer list of features, see https://www.autolearningagents.com/ for docs, articles and setup pages.
Please star on github, follow on X/FB (AIAppsAPI handles) to support my efforts. Thank you all!
The OTP supervision per agent is such a thoughtful call. Most agent frameworks just hope nothing crashes mid-run, but treating each one as a supervised process that actually recovers feels like the kind of foundational decision that will make this hold up once people build real things on it.
Some of you beat me to first comment haha, thank you for the support I have already received, its only been 3 hours and I got about 50 messages I woke up to on various social media so catching up now.
I built Auto Learning Agents because my agents kept forgetting everything between sessions. It is a self-hosted agent OS built on Elixir/OTP: deep internal memory, session-less dynamic context so agents find the right context each turn, a web UI for Claude, OpenAI, Gemini or fully local Ollama, plus a file browser, code editor, 40+ built-in tools, and background agents that keep working while you sleep. Free and open source, one Docker command to run. I would love honest feedback, especially from anyone self-hosting their AI stack, and I will be around all day answering everything.
How does the deep internal memory actually work across sessions, do agents truly retain learnings between runs or is it more like scoped context retrieval each turn?
About Auto Learning Agents on Product Hunt
“Self-hosted AI agent OS with memory that actually learns”
Auto Learning Agents was submitted on Product Hunt and earned 5 upvotes and 6 comments, placing #84 on the daily leaderboard. Auto Learning Agents is a free, open source OS for AI agents. Deep internal memory plus dynamic, session-less context: agents find the right context each turn, pick up where they left off, and get better at recurring work. Web UI for Claude, OpenAI, Gemini, or fully local with Ollama, with a file browser, code editor, and 40+ built-in tools. Background agents run while you are away. Built on Elixir/OTP, every agent is a supervised process that recovers from crashes. One Docker command and go.
Auto Learning Agents was featured in Open Source (68.6k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 218k products, making this a competitive space to launch in.
Who hunted Auto Learning Agents?
Auto Learning Agents was hunted by Paul Crinigan. 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 Auto Learning Agents stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Paul Crinigan