Group 1 - Hacker Houses are emerging as a new living and working model for tech enthusiasts, particularly in the AI sector, blending life, work, and research [2][3][4] - The concept of Hacker Houses dates back to 2013, evolving from informal living arrangements among tech engineers into a recognized collaborative space for innovation [6][8][10] - The recent surge in generative AI has intensified the popularity of Hacker Houses in San Francisco, attracting a high concentration of tech talent from companies like OpenAI and Meta [9][10][12] Group 2 - Hacker Houses serve as cognitive collaboration units, potentially becoming the smallest innovation units in the intelligent era [3][32] - They provide a unique environment that fosters trust and collaboration, essential for early-stage startups, by allowing members to live and work together [35][36] - The presence of venture capitalists in these spaces indicates a shift in investment strategies, with some funds directly supporting the operation of Hacker Houses as incubators for new projects [38][39] Group 3 - Notable examples of Hacker Houses include AGI House, which has become a hub for influential discussions and connections within the AI community [19][27][30] - The structure of these houses allows for informal knowledge sharing and mentorship, contributing to the development of new ideas and projects [40][41] - The rise of Hacker Houses reflects a broader trend in urban innovation, emphasizing the importance of community and collaboration in fostering creativity [46][52]

Core Viewpoint - The emergence of "Software 3.5" signifies a paradigm shift in human-AI interaction, moving from traditional input-output models to cognitive collaboration, where AI acts as a transparent thinking partner rather than a mere tool [1][8][24]. Group 1: Evolution of Software Paradigms - Software 3.0 is considered outdated as it was based on the limitations of earlier AI capabilities, primarily focused on text generation and simple reasoning [6][20]. - The transition to Software 3.5 reflects a generational leap in AI capabilities, enabling true cognitive collaboration where AI understands not just commands but the underlying motivations and context [6][25]. - The new paradigm emphasizes that intelligence emerges from the interaction between humans and AI, rather than being a solitary attribute of either [7][37]. Group 2: Characteristics of Software 3.5 - Software 3.5 introduces a cognitive collaboration model, allowing for real-time interaction and adjustments, where users can intervene at any point in the AI's thought process [24][26]. - This model supports asynchronous collaboration, enabling AI to continue processing and exploring even when the user is offline, enhancing the overall efficiency of human-AI teamwork [26][27]. - The interface requirements for Software 3.5 necessitate a fundamental redesign to accommodate complex cognitive interactions, moving beyond simple Q&A formats [27][28]. Group 3: New Skills for Developers - Developers in the Software 3.5 era must acquire new skills, including cognitive modeling, intent engineering, and context management, to effectively design interactions that leverage AI's cognitive capabilities [28][30]. - Real-time interaction design and asynchronous collaboration architecture are essential skills for creating systems that allow for dynamic user engagement and cognitive transparency [30][31]. - The evolution from traditional programming to cognitive collaboration signifies that anyone can become a cognitive architect, emphasizing the democratization of software development [31][32].