Summary The group discussed organizational restructuring alongside strategies for autonomous artificial intelligence ownership and corporate business infrastructure implementation. Community Mentorship and Strategy The leadership decided to implement a new organizational structure focused on accountability. This shift prioritizes professional development over previous free-access models. Local AI Infrastructure Implementation Technical demonstrations illustrated how local language models replace expensive cloud services to reduce costs. This approach ensures data privacy and enables the scaling of autonomous business agents. High Ticket Sales Strategy The group analyzed positioning artificial intelligence infrastructure as a premium corporate service. This strategy targets businesses seeking to automate workflows and replace traditional manual labor costs. - Addressing Criticism and Public Perception: The participants discussed the persistent challenge of dealing with "haters" and individuals who publicly accuse them of being disingenuous or not supportive of the community. They reached a consensus that engaging directly with these individuals or providing them with a platform is unproductive, referencing mentors like EL, Derek, and Keys who avoid elevating critics. - Leadership and Value Extraction: Sebastian emphasized the necessity for leaders to set clear boundaries, specifically advising against allowing others to "pick their brain for free" or extract value without proper consultation. They identified a pattern where individuals demand attention, such as text responses or DMs, without providing value in return, leading to emotional, reactive behavior from those individuals. - Mentorship and Accountability: Sebastian addressed TC directly, highlighting a critical gap between possessing high-level ideas and the "execution" required to be successful. The group defined mentorship as a form of accountability, where the mentor pushes their mentees to take concrete action on their projects, such as launching an assistant app or growing a coaching business, rather than merely holding onto unexecuted ideas. - Spirituality and Personal Growth: The group shared personal experiences regarding spiritual development and indigenous heritage, noting that as they deepen these connections, they often face increased scrutiny and hostility from others. They concluded that this negative attention is a natural byproduct of their success and that they remain focused on their own path, as their character is known to their genuine community. - Evaluating Character and Integrity: Sebastian introduced a framework for evaluating a man's character by observing their relationships with the mothers of their children. They argued that these long-term relationships provide the most authentic assessment of an individual's integrity and whether they are genuinely living their life or "faking" their success, serving as a reliable benchmark for authenticity. - Business Scaling and Vision: Sebastian outlined strategic objectives for the organization, including the goal of taking their software company, New Aminti, public as an IPO. They emphasized the importance of preparing the community to take on more responsibility, such as teaching and managing, to allow leadership to focus on new ventures like a robotics company and private investing. - Meeting Structure and Organizational Restructuring: Sebastian announced a new organizational structure for the "Ascended Masters," moving away from a free academy model. The new schedule features a monthly three-hour "Master class," a monthly homework session led by Kyree, and a monthly guest session. They assigned Kyree the role of leading teaching sessions and tasked TC with helping organize, digitize, and align classes using software to build internal infrastructure. - Community Empowerment and Challenges: To foster growth, Sebastian mandated that members use affiliate links for shared revenue and announced the implementation of monthly challenges. These challenges, developed by Kyree, will focus on practical achievements—such as creating an AI agent or an automated email funnel—to help students build, sell, and market their skills. - Introduction of D Hud (EntreMotivator): Sebastian introduced D Hud, an Atlanta-based roboticist and systems architect, who shared their background of 20 years in technology, including early work with Python and automation bots. D Hud highlighted a focus on "unsupervised agents"—systems designed to perform tasks independently 24/7 without requiring active user attendance. - Shift to AI Ownership: D Hud explained the concept of moving from a "consumer" mindset to an "owner" mindset by hosting AI models locally. They argued that relying on services like ChatGPT is akin to using a "temp service," whereas owning one's system allows for the creation of independent "AI employees" without the recurring costs of API token consumption. - Mentorship Confirmation: Following a brief logistical discussion about attendance, Sebastian reaffirmed their commitment to the mentorship program for all mentees, noting that regular coaching and "belt" (correction) sessions would continue on Sundays to ensure progress on launching books and funnels. - Profitability in High-Ticket AI Sales: Sebastian inquired how to maximize profits in high-ticket AI sales for large corporations while reducing API costs. D Hud recommended a "cloud stack and local stack" approach, utilizing local hosting to eliminate ongoing token expenses, which would otherwise erode profit margins in enterprise-level contracts. - Technical Strategy: Local Hosting with Ollama: D Hud demonstrated using Ollama to download and run language models locally, which allows functionality even without an internet connection. They discussed combining this with N8N for workflow automation, explaining that using local models instead of paid APIs allows for the creation of sophisticated workflows capable of supporting multimillion-dollar business teams with zero-dollar token costs. - Privacy and Uncensored Models: D Hud highlighted the advantages of "uncensored" models—language models that have not been restricted by corporate moderation policies. They explained that these models are essential for security and providing robust, private advice for legal or complex business tasks that mainstream AI services might refuse to process. - Remote Access and Scalability: D Hud explained "tunneling" tools, such as Ngrok, which allow for remote access to local AI systems. They described scaling this into a "Company GPT" model, where an entire organization can access a centralized, private medical or legal assistant securely from any location, ensuring data remains under the company's control. - LLM Stacking and Expert Routing: D Hud introduced the concept of "LLM stacking" and using an "LLM Selector" to route queries to the most appropriate specialized model (e.g., using a vision model for images and a coding model for development). By treating these models as a group of experts, the system automatically chooses the best tool for the specific task, significantly improving performance and efficiency. - 3D Environments and Agentic Dashboards: D Hud demonstrated their 3D AI environment where agents are organized into virtual rooms, creating a visual dashboard for various business functions. They emphasized that true scalability is achieved through "agentic dashboards" and unsupervised agents that execute tasks, such as grant searching or email drafting, independently of whether the user is actively logged in. - Unsupervised Agent Concept: D Hud EntreMotivator introduces the concept of unsupervised agents navigating an "AI city." The core challenge discussed is shifting from active monitoring to maintaining autonomous, 24/7 agents, and the financial sustainability of running these systems using local open-source models like Ollama rather than relying on recurring token-based costs. - Business Ownership and High-Ticket Sales: Sebastian emphasizes the value of teaching clients to own their AI infrastructure rather than renting it from third parties. The consensus among the group is that providing clients with proprietary, internal agent cities offers significantly higher value for high-ticket service offerings compared to traditional cloud-based solutions. - Technical Call Stability: Participants, including Sebastian, D Hud EntreMotivator, and christina cotto, experience technical lagging and freezing issues during the call. The resolution involves D Hud EntreMotivator resetting their local machine to stabilize the connection. - Implementing AI for Corporations: Sebastian and christina cotto discuss the potential for selling AI infrastructure to businesses. The proposed strategy involves positioning clients as directors of their own AI systems, which allows them to leverage advanced capabilities similar to ChatGPT while maintaining full control, privacy, and data security. - Second Brain Concepts: D Hud EntreMotivator and christina cotto discuss the implementation of "second brain" systems. christina cotto notes that they are already taking notes on how to integrate this concept into their service offers, viewing it as a tangible, marketable solution for clients. - Memory Architecture and Graph RAG: D Hud EntreMotivator explains the evolution of AI memory from standard Retrieval-Augmented Generation (RAG) to "Graph RAG." They argue that while basic RAG uses a single vector database, graph-based systems enable agents to manage complex, multi-layered memory across various datasets—such as separate medical or legal records—without needing to merge them into a single, less organized database. - Local AI and Multimedia Generation: D Hud EntreMotivator advocates for avoiding third-party dependencies like ElevenLabs by utilizing local voice cloning, music generation, and video models. By leveraging tools like Stable Diffusion and utilizing local computer hardware, they argue that users can generate content for free while maintaining full ownership. - Edge Computing and Mixture of Experts: D Hud EntreMotivator illustrates the utility of "brain on board" technology through drones and smart home devices that operate autonomously without internet access. They introduce the "Mixture of Experts" method, inspired by DeepSeek, which involves running multiple specialized language models in unison to handle tasks efficiently without requiring a single, massive, and expensive model. - Model Fine-Tuning and Claiming Ownership: D Hud EntreMotivator explains that fine-tuning models using Ollama allows users to create and rename their own foundational models. This process serves as a practical, lower-cost alternative to building a foundational GPT from scratch, providing participants with a clear path to technological independence. - Community Integration and Mentorship: Sebastian invites D Hud EntreMotivator to participate in the "Ascended Masters" community and contribute to the school's educational material. The consensus is to continue collaboration, with D Hud EntreMotivator agreeing to share insights into digital real estate and AI ownership for the community. - Scaling Agentic Systems and Digital Land: D Hud EntreMotivator highlights the distinction between using cloud agents and owning "digital land." They propose that selling the functionality of autonomous employees to corporations, while maintaining the underlying infrastructure on the client's own digital land, represents a significant high-ticket opportunity. - Simulation Tools: D Hud EntreMotivator introduces "Murofish" as a tool for simulating agentic workflows, such as calculating the number of robots needed to perform physical tasks like lawn mowing. The benefit of these simulations is the ability to project labor and time savings before investing in hardware. - Hardware Requirements for Local AI: D Hud EntreMotivator clarifies that while more RAM and compute power are beneficial, users can begin with their existing computers as servers. Even if performance varies, local hosting allows users to download and run various open-source models, bypassing the high costs of commercial API usage. - Technical Implementation of Ollama: KAIREE OPHARROW asks about the installation process for local AI hosting. D Hud EntreMotivator instructs the group to use Ollama.com, comparing the process to simple file downloads, and notes that once the base tool is installed, users can experiment with different models similar to browsing movies on a streaming service. - Benchmarking and Quality Control: D Hud EntreMotivator emphasizes the importance of "benchmarking" by comparing local model performance against top-tier services like OpenAI’s. The goal is to achieve comparable results in email drafting and task completion without recurring token costs, ensuring that quality is not sacrificed for price. - Agent Hierarchy and Management: D Hud EntreMotivator discusses the necessity of organizational structures for agents, similar to managing physical employees. They recommend using N8n workflows to coordinate tasks, where a "general" agent manages a workforce of specialized "soldier" agents, avoiding the inefficiencies of managing every individual process manually. - Hardware-Centric Building and Educational Potential: D Hud EntreMotivator and KAIREE OPHARROW discuss the potential of using Raspberry Pi and Arduino for building custom AI-powered hardware, from smart mirrors to autonomous toy cars. D Hud EntreMotivator argues that teaching these skills to children moves them from passive consumers to active producers of technology. - Interdependence and Community Building: KAIREE OPHARROW and D Hud EntreMotivator reflect on the value of collective expertise. They conclude that while "building from scratch" is a worthy goal, the true power lies in community interdependence, where members contribute specialized skills—such as front-end or back-end development—to support each other's projects. - Personal Development and Leverage: KAIREE OPHARROW shares that their recent focus on personal development and structural thinking acts as "leverage" for business success. By mastering organization and completing tasks systematically, they argue that one can more effectively lead and teach others in a business context.