According to God of Prompt on Twitter, LobeHub’s agent marketplace now enables users to enhance People Search agents for advanced talent sourcing. By remixing existing prompts and swapping tools, users can extract all authors from arXiv papers, locate their contact information, and draft outreach emails automatically. This workflow is specifically built for venture capital, recruiting, and talent acquisition, highlighting significant practical applications of AI-driven automation in streamlining candidate discovery and communications, as reported by God of Prompt.

According to God of Prompt on Twitter, LobeHub has introduced its L4 agent harness, marking a significant advancement in collaborative AI. The platform enables users to build and coordinate teams of agent coworkers for complex tasks, signaling the end of L3 agents and the emergence of L4 capabilities. As reported by the official LobeHub announcement, the service is currently invite-only, offering incentives such as credits for new users and referrals. This launch highlights evolving trends in multi-agent systems and presents new business opportunities for organizations seeking scalable AI-driven workflows.

According to God of Prompt on Twitter, a recent comparison of AI-driven paper analysis tools reveals that LobeHub significantly outperforms Manus in both speed and cost. LobeHub completes paper analysis in just 2 minutes and 58 seconds at a cost of $0.46, while Manus takes 9 minutes and 1 second and costs $2.98. The key difference, as reported by God of Prompt, is that LobeHub leverages agent groups with supervisor orchestration, enabling more efficient task execution, whereas Manus relies on single-agent systems requiring step-by-step user oversight. This highlights the business opportunity for scalable, orchestrated agent-based AI platforms in research and enterprise workflows.

According to God of Prompt on Twitter, recent developments in AI agent orchestration reveal that LobeHub has advanced its agents to Level 4 (L4) autonomy, surpassing platforms like Manus and Claude Cowork, which operate at Level 3 (L3). At L3, agents require continuous user guidance and intervention, keeping humans in an active supervisory role. In contrast, LobeHub's L4 agents operate in parallel, with a supervisor agent managing orchestration and the human user only approving final outputs. The Knight Institute's published framework identifies L4 agents as optimal for tasks involving numerous low-stakes decisions. This move to L4 autonomy suggests increased efficiency and scalability in AI-driven workflows, creating new business opportunities for enterprises requiring high-volume task automation, as reported by God of Prompt.

According to God of Prompt on Twitter, Lobehub has introduced a new multi-agent AI system that surpasses Manus and Claude Cowork in both performance and sophistication. The platform features multi-agent teams, supervisor orchestration, and parallel execution, all activated with a single prompt for end-to-end task delivery. This innovation enables users to leverage coordinated AI agents for complex workflows, offering substantial efficiency improvements and advanced automation capabilities. As reported by God of Prompt, the release demonstrates the mathematical advantages of this approach and highlights why many users are still reliant on less capable L3 agents.

According to God of Prompt on Twitter, LobeHub is pioneering a new approach in AI agent design by providing dedicated memory per agent, rather than relying on a global memory system that can lead to hallucinations and loss of context. This approach ensures that each AI agent maintains its own context isolation, resulting in more reliable and useful interactions over time. As reported by LobeHub, their solution enables long-term agent teammates to evolve with users and supports clear reinforcement learning signals and continual learning environments. The platform also facilitates multi-agent collaboration, allowing groups of agents to operate in parallel for faster and more cost-effective results. By supporting multiple AI models, LobeHub increases cost efficiency and adapts to diverse user scenarios, offering significant business opportunities in workflow automation and team augmentation.