LobeHub

LobeHub is an AI agent platform for organizing work across agents and people. Its homepage presents a Chief Agent Operator that schedules tasks and reports on an AI team. The product centers on creating agents, arranging them into groups, and giving their work a shared place to live.

Create an agent with a defined role

The Agent Builder starts with a sentence and configures an agent's name, role, skills, and behavior. LobeHub also presents an Agent Marketplace and a Skills Marketplace. These give you ways to begin with an existing agent or connect an agent to tools, alongside building your own.

An agent's assigned role is worth keeping concrete. A paper-summary agent and an agent that prepares a meeting recap have different source material and expected results. Both appear among the publisher's examples. Use those examples to frame a task, then specify the documents and output you need.

Coordinate a group and its workspace

Agent Group supports automatic team formation, parallel collaboration, multiple-task execution, and iterative improvement. The publisher describes the system as assembling agents for a task. This is the central reason to consider LobeHub for work that involves several contributions.

Pages lets multiple agents write and refine content with shared context. Projects organize related work, while a shared Workspace provides ownership and visibility for team collaboration. Scheduled tasks add a way to assign work for later execution. These features put the resulting material and the agents' assignments into the same workflow.

Keep context and review the result

LobeHub describes its White-Box Memory as structured and editable. The homepage also lists personal memory and adaptive behavior. Before using an agent group for repeated work, inspect the context and instructions you want it to carry between tasks.

The homepage offers free-start and download entry points, but its captured text does not establish plan prices or resource allowances. Check those details during signup. Its examples and testimonials also do not establish how a particular agent will perform on your documents. Review summaries against their sources and confirm action items before handing the output to colleagues.