Hi Product Hunt 👋 We’re the team behind Offloop. AI made individuals faster, but team progress still breaks at the organizational layer. We built Offloop to turn useful AI results into team progress.
For small AI-native teams, that means:
1）A workspace built for people and Agents. Both are first-class participants: they share Channels, can be @ mentioned, own work, review results, and hand off to the next owner. 2）An org-level harness. Context, files, decisions, tool activity, and artifacts stay attached to the work. Owners, approvals, and next steps remain durable and traceable. 3）Privacy and human control. Workspace-scoped identity, exact access grants, isolated runs, approval gates, and revocable connections govern what each Agent may see and do. 4）Bring your own subscription and choose the right model. Connect a supported model account with no Offloop model-usage markup on BYOP runs, then set a workspace default or choose a different model for a specific Agent. 5）Reusable execution. Turn successful Agents and Flows into repeatable operating capacity across retries, waits, schedules, and handoffs—not just one prompt at a time.
Offloop is live on the web today. Create a workspace, invite your teammates, and your whole team gets free AI credits for the first 30 days.
If AI already helps individuals on your team, what still breaks when their work needs to become team progress?
PH 用户
Congrats on the Product Hunt launch! What kind of team will get the most value from Offloop on day one? I’d be interested to hear how this works in practice.
PH 用户
Congrats on today’s launch! Can you walk us through a real Offloop workflow from request to handoff? Curious how you’d explain this to a new team.
PH 用户
Are you gonna apply for Fall 2026 YC funding? :) They wanna support this section. :)
PH 用户
Excited to hunt Offloop today.
Offloop is an AI-native workspace where humans and AI agents can work together, share context, and move work forward without everything turning into another endless chat.
Instead of manually assigning agents one task at a time, Offloop lets you describe what needs to get done, break it into tasks, delegate work across agents and people, and review the results in one shared workspace.
What stands out:Coordinate multiple AI agents from one workspaceTurn one request into delegated tasks and actual workKeep agents, people, files, and context connectedCreate reusable agents for recurring rolesReview agent work before accepting the result
For small AI-native teams, that means:
1）A workspace built for people and Agents. Both are first-class participants: they share Channels, can be @ mentioned, own work, review results, and hand off to the next owner.
2）An org-level harness. Context, files, decisions, tool activity, and artifacts stay attached to the work. Owners, approvals, and next steps remain durable and traceable.
3）Privacy and human control. Workspace-scoped identity, exact access grants, isolated runs, approval gates, and revocable connections govern what each Agent may see and do.
4）Bring your own subscription and choose the right model. Connect a supported model account with no Offloop model-usage markup on BYOP runs, then set a workspace default or choose a different model for a specific Agent.
5）Reusable execution. Turn successful Agents and Flows into repeatable operating capacity across retries, waits, schedules, and handoffs—not just one prompt at a time.
Offloop is live on the web today. Create a workspace, invite your teammates, and your whole team gets free AI credits for the first 30 days.
If AI already helps individuals on your team, what still breaks when their work needs to become team progress?
Offloop is an AI-native workspace where humans and AI agents can work together, share context, and move work forward without everything turning into another endless chat.
Instead of manually assigning agents one task at a time, Offloop lets you describe what needs to get done, break it into tasks, delegate work across agents and people, and review the results in one shared workspace.
What stands out:Coordinate multiple AI agents from one workspaceTurn one request into delegated tasks and actual workKeep agents, people, files, and context connectedCreate reusable agents for recurring rolesReview agent work before accepting the result