Key insights

• ⚙️ Building AI agents over 18 months emphasizes AI's potential to transform businesses by providing leverage at a fraction of the cost of hiring employees.
• 🤖 Discussing AI agents as llms, with the ability to take actions, and highlighting various AI agent frameworks and platforms available for building AI agents.
• 📊 Different AI platforms like Vector Ai, relevance AI, my studio, and inatein are emphasized, highlighting the importance of data for AI agents and recommending using Vector databases like pine cone.
• 📈 Emphasizing the significance of data collection and retrieval for AI applications, especially from the vector database, and recommending the use of structured prompt engineering for effective agent behavior.
• 🔧 Understanding that using examples and tools are key to training and empowering AI agents, with Naden allowing for building custom workflows and integrating AI agent capabilities.
• 🏗️ Integrating platforms and data to enable AI agents to efficiently complete tasks, thinking of agents as human beings needing access to platforms and data, and adopting an architectural approach to building agents for lead generation AI team.
• 💼 Transcending AI's passive tool status to active task performance, highlighting AI's role in transforming business operations, and emphasizing the future of AI in businesses involving building teams of AI agents for increased efficiency and cost savings.

Q&A

• In what way is AI transforming business operations?

  AI is transforming business operations by taking over various job functions through specialized agents, enabling significant leverage and cost reduction. The future of AI in business involves building teams of AI agents to fulfill roles traditionally carried out by human employees, leading to increased operational efficiency and cost savings.

• How does the video suggest thinking of AI agents?

  The video suggests thinking of AI agents as human beings needing access to platforms and data, and highlights the importance of integrating platforms and data for efficient task completion. It also talks about an architectural approach to building agents for lead generation AI teams.

• How are examples and tools important for training AI agents?

  Examples are crucial for improving AI agent performance, while tools are essential for giving AI agents the ability to perform tasks efficiently. The video also mentions Naden, which allows for building custom workflows and integrating AI agent capabilities.

• What is highlighted as crucial for building effective AI agents?

  The video emphasizes that data collection from the vector database is crucial for keeping AI agents contextually aware and up to date. It also points out that structured prompt engineering, including clear objectives, context, detailed instructions, output requirements, and examples, is vital for effective agent behavior.

• Which AI platforms are discussed in the video?

  The video discusses various AI platforms including Vector Ai, relevance AI, my studio, and inatein for building AI agents. It also emphasizes the importance of data for AI agents and recommends using Vector databases like pine cone for hosting AI information.

• What is the video about?

  The video discusses the speaker's experience of building AI agents over 18 months, emphasizing AI's potential to transform businesses by providing leverage at a fraction of the cost of hiring employees. It also highlights the concept of AI agents as llms with the ability to take actions, various AI agent frameworks and platforms available for building AI agents, and their essential components.

• 00:00 The speaker shares their experience of building AI agents over the last 18 months, emphasizing the potential of AI to transform businesses by providing leverage at a fraction of the cost of hiring employees. They discuss the concept of AI agents as llms with the ability to take actions, and highlight various AI agent frameworks and platforms available for building AI agents.
• 06:56 The speaker discusses several AI platforms including Vector Ai, relevance AI, my studio, and inatein. They emphasize the importance of data for AI agents and recommend using Vector databases like pine cone. Data collection and retrieval are also crucial for AI applications.
• 13:42 Data collection and prompt engineering are crucial for building effective AI agents, with structured prompts, context, detailed instructions, output requirements, and examples being essential components.
• 20:17 Using examples and tools are key to training and empowering AI agents. Tools give the agent the ability to perform tasks, and examples enhance its understanding. Naden allows for building custom workflows and integrating AI agent capabilities.
• 27:45 Thinking of agents as human beings with access to platforms and data. Integrating platforms and data to enable agents to complete tasks efficiently. Architectural approach to building agents for lead generation AI team.
• 34:59 AI is transforming business operations by taking over various job functions through specialized agents, enabling significant leverage and cost reduction. The future of AI in business involves building teams of AI agents to fulfill roles traditionally carried out by human employees, leading to increased operational efficiency and cost savings.