MuleRun is the world's first self-evolving personal AI — it learns your work habits, decision patterns, and preferences, then keeps getting sharper over time. It runs 24/7 on your dedicated cloud VM, works while you're offline, and proactively prepares what you need before you ask.No coding. No setup. Just raise your AI and watch it evolve.
As one of the early beta testers, so excited for the launch and congrats on hitting #1!
How MuleRun helped me so far:
I had to generate personalised stickers for 200 people for an event I was organising. I just fed MuleRun the social medial handles of each of the attendees + their desired art style, and it did the job!
We agreed on generating 4 designs per person for more diversity; it took care of researching user info, prompting the image gen model, calling the API, organising the outputs in ready-to-print pdfs and bundle it all in a zip file.
All I had to do then was to send that file to the supplier, and I got my stickers the next day!
Can't wait to build more cool stuff with MuleRun.
self-evolving is a game-changer... would love to know the behind the scenes.. the caching etc.. but can't wait to try it
Congrats! Chatting with Mule on TG feels like having a helper in my pocket.
On pricing and packaging: given credits + dedicated VM tiers, what have you learned about which workloads are predictable vs spiky—and how are you designing guardrails so teams can trust cost, performance, and output quality at scale?
Could this be used for iterative optimization research — say, discovering new rendering techniques for 3D games? For example: have it run 100 passes trying to speed up drawing large 3D scenes (culling geometry that doesn't contribute to the final frame, finding cheaper shading paths, etc.), keeping the best results and iterating on them.
Follow-uponsearchstrategy: Is there a way to preserve candidates that aren't immediately faster but might unlock better optimizations downstream? Basically a beam search rather than pure greedy; keeping a pool of "promising but not yet winning" approaches so it can explore paths that pay off after several iterations, not just the next one.
Interesting take on personal AI. If the system really adapts to individual workflows over time, that could be incredibly sticky.
This is genuinely impressive — the idea of agents that evolve from actual workflow patterns rather than static prompts is a big unlock. The always-on dedicated VM approach is smart too; most agent platforms lose context the moment you close the tab.
Quick question: for agents that handle media workflows (video processing, content production pipelines), how does MuleRun handle large file orchestration? We've been building video infrastructure at Vidtreo and the hardest part is always the handoff between "the AI decided what to do" and "the media pipeline actually executes it reliably."
Would love to see a MuleRun agent that can orchestrate end-to-end video workflows — record, transcode, deliver. That combination of autonomous decision-making + specialized infra could be really powerful.
Congrats on the launch!
Congrats on the launch! The self-evolving angle is what makes this stand out; most AI tools are static from day one, and it's on the user to figure out how to get more out of them over time.
How does it handle domain-specific workflows, like financial analysis or structured research tasks? Does it get better with use, or is the learning more behavioral, adapting to how you work rather than what you're working on?
I tried the website and noticed the footer is quite large, which creates a lot of extra scroll on the homepage. Reducing its height might make the page feel tighter and more focused.
The concept looks interesting though. Curious what the main use case you’re seeing from early users is..
Very nice idea, but the demo kind of confused me. Is this only related to coding and making products? Or is it also connected to the various platforms you use while working, to "learn" from you as mentioned?
We're a team of 6 building on GitHub as a shared OS. Agents, skills, finances, communications, content, investor decks, all in one place. Everyone reuses the same agents across tasks. The "learns how you work" part got my attention, but I'm curious whether MuleRun is built for one person or if there's a team layer. When the whole workflow lives in one place and you're sharing agents across contributors, the handoff problem changes. It's not just my memory across sessions, it's shared context across people. Asking because if there's a team model this could actually fit.
Keen yo explore, but the procing page won't render/sidescroll on mobile! I'm equally sure a) it'll be soon fixed, and b) you'd want to know!
How does MuleRun handle the transition when you switch between very different types of workflows, like going from e-commerce operations to content creation? Does it maintain separate context profiles or blend everything into one evolving model? Really cool concept, congrats on the launch!
Just curious, most AI tools lose context after a session or hit a token limit, forcing you to start fresh each time. Since this AI is meant to 'learn your habits' over time, how does it handle long-term memory? Does it retain what it's learned about you across sessions, or does it reset after each conversation?
This looks cool. Respectfully, you deserve to have someone do some read through on the site, as there are myriad spelling/mechanical errors… “markting”, “creat a pptx”, others. Just a heads up. Congrats on the launch tho, concept is really cool and I’m keen to try it.
This would be a game changer for AI. It seems like a lot of AI eb and flow knowing your working style etc but a dedicated AI would be awesome almost like building your own AI platform.
Nice and proactive approach, guys!
How much control do users have over what the AI learns and automates? Can you audit its decision-
making, override patterns, or set boundaries like "never auto-send emails" or "don't access folder X"?