VIEW RECORDING - 169 mins (No highlights) Key Takeaways - RAG (Retrieval Augmented Generation) applications are currently the most in-demand and monetizable AI projects - Context 7 is a powerful tool for accessing up-to-date documentation for various libraries and frameworks - LinkedIn growth strategies: Summarize others' content, create and give away valuable assets to followers - Pricing AI projects: Focus on the value delivered to the client rather than hourly rates Topics AI Project Updates - AK demonstrated a grant proposal generation MVP using an orchestrator agent, research agent, rendering agent, parser, and language match agent - Juan Torres developed an Agentex system for vendor name extraction using a hybrid of LLMs and machine learning models - Neel More showcased an app for running machine learning pipelines with data analysis and drift detection - Bastian presented a real-time multimodal agent using Gemini and Google search capabilities AI Development Tools and Techniques - Discussion on the use of Langchain, LangGraph, and Google ADK for different project requirements - Comparison of various AI models and subscriptions (GPT-4.5, Gemini, Supergrok, etc.) - Introduction to Context 7 for accessing up-to-date documentation in AI development - Exploration of agentic development using Cursor AI and other tools