MOST Important AGENTIC Application - Speech to Text to AI Agents (TTS, STT, LLM Router)

What comes next after AI Agents? What's the most useful workflow for your agents? The answer is pretty clear, the best way to use your growing collection of AI Agents is in the form of a personal AI assistant. Not just 'a' personal AI assistant, YOUR personal AI assistant. Imagine a tool so powerful, it feels like an extension of your mind. In this video, we dive into the creation of the most important agentic application we can build and use: Your Personal AI assistant. This tool will be limited only by your imagination, and your ability to hop in your python or typescript code and COOK up great agentic workflows, AI Agents, prompt chains, and individual prompts. Your personal assistant can code for you, research for you, and organizing your digital life. BUT in order to get to that vision we have to take small, incremental steps. Here we look an EARLY prototype of what future personal AI assistants (the next level of VAs) will look like through ADA. ADA is the name of my, personal AI assistant. It's a prototype to show what this technology will be able to do for you. In order to make use of your AI Agents and prompt chains in the form of your personal AI assistant, we need a framework for prompting your agents. In this video we introduce two critical frameworks for building your personal AI assistant: the PAR framework, and the simple keyword AI Agent Router (LLM Router). The PAR framework sets an a clean loop for you and your personal AI assistant. First you speak in natural language, we run text-to-speech (TTS) to capture your prompt and convert it into text which becomes your nlp/prompt (natural language prompt). Next we use an LLM Router called the simple keyword AI Agent Router which takes your prompt and decides which AI Agents to run. Your agents run their individual, isolated workflows, and finally your personal ai assistant (ai va) responds to you using speech-to-text (STT) completed the PAR framework. The beauty of this framework is that it doesn