Launching today
Mindstone Rebel
AI workspace for agents that know your work and ask first
82 followers
AI workspace for agents that know your work and ask first
82 followers
Rebel is a desktop AI workspace for agentic work. It connects your memory, meetings, files, actions, automations, and tools so AI agents can help with real work — while keeping sensitive actions behind approval checks. Built Fair Source, with portable workflows and model choice.
Mindstone Rebel
Hey Product Hunt, I’m Melissanthi, Senior Product Engineer at Mindstone.
We’re launching Rebel as a Fair Source AI desktop app for agentic work.
The reason we’re doing this now is simple: AI work shouldn’t be trapped inside one closed platform or one model provider. Rebel is built as a desktop workspace that people can download, run locally, inspect, customise, and connect to their own tools through MCP.
Fair Source means the code is available, but with practical restrictions that let us keep building the product sustainably. Small teams and individuals can use and adapt Rebel freely, while larger organisations need a commercial licence.
This release is also part of a broader push toward more portable AI workflows: model choice, local-first files, MCP connectors, and workflows that teams can actually understand and adapt.
We’d love feedback from makers, developers, operators, and AI teams on:
• what you’d want from a Fair Source AI workspace
• how you think about model choice and local-first AI tools
• what would make Rebel useful in your own workflow
where exactly do you draw the line between what a small team can adapt freely vs what needs a commercial licence? Asking because that clarity is usually what makes or breaks adoption for us.
Mindstone
@thomas_wright2 Anyone can adapt freely. Up to 100 users within the same group don't require a license. More than 100 would, but we like to think you'd get a ton of extra value around AI transformation of the entire organisation alongside of it (an impact dashboard measuring your ROI, clear analysis of where things are working and where not, etc.) as well as direct support from our team.
Mindstone
A bit of personal context on why I care about this so much.
I don't use Rebel as a demo environment. I run a large part of my work through it.
Most days, that means speaking rather than typing: meeting prep before important calls, catching the follow-ups I would otherwise delay, pulling together context from email, calendar, Slack, docs and old conversations, drafting things in my voice, and challenging assumptions before something goes to a customer, investor or the team.
The shift for me has not just been "the same work faster", but more that I can now do work at the level I always wanted, but often did not have the time or attention for. Better prep. Better follow-through. More context. Less living out of my head.
This is also why fair source matters to me.
If an agent is going to sit this close to my actual work (memory, tools, approvals, the messy context of their day) trust cannot just be a brand promise. People should be able to inspect it, run it themselves, and understand the boundaries.
Rebel started as my own operating system for work, and I wouldn't be able to do my job without it today. Opening it up feels like the right next step.
Mindstone Rebel
My favourite thing about Rebel is the way the memory works - learns as you go, and shares its memories with other Rebels (e.g. throughout your company).
The interesting part is how it works to judge which memories should be shared and with whom, and which should be kept private. And it asks if it's unsure.
@greg_detre The shared-memory model is the most interesting part to me ! But how does it make that call in practice: is shareability classified by content, set by the user, or learned over time? And what's the recovery path if something goes wrong?