Core Viewpoint - The article emphasizes that 2026 is set to be a pivotal year for AI agents, with intense competition emerging in the market, particularly highlighted by the launch of MiniMax Agent 2.0, which aims to enhance productivity through advanced AI capabilities [1][2]. Group 1: MiniMax Agent 2.0 Features - MiniMax Agent 2.0 is introduced as an "AI-native Workspace," significantly restructuring its product capabilities to provide a more integrated and efficient user experience [2][5]. - The new desktop application allows seamless interaction with local files and cloud tasks, liberating users from repetitive tasks like switching between windows and manual data entry [2][9]. - The introduction of "Expert Agents" enhances the system's reliability and expertise, improving the quality of outputs from a score of 70 to potentially 95 or 100 [3][5]. Group 2: User Experience and Performance - Users can currently experience the Expert Agents feature for free on both desktop and web platforms, facilitating easier access to advanced functionalities [4]. - The article showcases practical tests where MiniMax Agent successfully completed complex tasks, such as summarizing news and analyzing technical documents, demonstrating its efficiency and capability [11][18]. - The ability to process multiple documents and generate presentations in a fraction of the time previously required illustrates the significant productivity gains offered by MiniMax Agent [18][20]. Group 3: Technological Advancements - MiniMax's continuous model upgrades, including the implementation of Lightning Attention and the M2 architecture, have enhanced the agent's capabilities, allowing it to handle complex tasks more effectively [32][33]. - The integration of these advanced models into MiniMax's internal processes has created a feedback loop that continuously refines the system based on real-world usage [32][33]. - The shift in interaction logic from users adapting to agents to agents adapting to users marks a significant evolution in how AI can assist in high-complexity tasks [33].