Today’s agents are one-off, task-driven tools — isolated, slow, costly, and hard to build — failing to unlock the full potential of AI models.LobeHub changes that. We build long-term agent teammates that grow with you. Anyone can easily create and collaborate with agent teams to deliver complex, end-to-end work. With multi-model support, LobeHub is faster, more cost-effective, and goes beyond single-agent systems.
I noticed the LobeChat project shortly after it was open-sourced. I'm not a programmer, but this was indeed the first open-source application I deployed on a server.
Initially, it was to take advantage of the free quotas offered by various platforms, as many large language model (LLM) providers offer generous free credits upon registration. I used all of these through LobeChat.
Later, I found that LobeChat's design philosophy greatly helped me in understanding "how to interact with AI" and "how to use AI" in the early stages. I even shared my deployed LobeChat with colleagues and friends, which was truly a wonderful memory.
Although I rarely use it now, I'm delighted to see them introduce a new generation of AI interaction methods!
I noticed the LobeChat project shortly after it was open-sourced. I'm not a programmer, but this was indeed the first open-source application I deployed on a server.
Initially, it was to take advantage of the free quotas offered by various platforms, as many large language model (LLM) providers offer generous free credits upon registration. I used all of these through LobeChat.
Later, I found that LobeChat's design philosophy greatly helped me in understanding "how to interact with AI" and "how to use AI" in the early stages. I even shared my deployed LobeChat with colleagues and friends, which was truly a wonderful memory.
Although I rarely use it now, I'm delighted to see them introduce a new generation of AI interaction methods!