Fine-Tuning Gemma for Personality - Part 2: Building the Training Dataset
One hundred eleven conversations. That's what it took to demonstrate personality-style learning. Not thousands—just 111 AI-generated examples of how she talks, thinks, and helps.
Building an Agentic Personal Trainer - Part 9: Lessons Learned
Nine posts later, what actually worked? What would I do differently? Here's my retrospective.
Building an Agentic Personal Trainer - Part 3: The System Prompt
Tools give the agent capabilities but the system prompt gives the agent its personality. Getting the tone right—in this case "coach, not drill sergeant"—requires iteration, opinion, and intuition, not just correct syntax.
Building an Agentic Personal Trainer - Part 2: The Tool System
An LLM without tools is just a chatbot. To make a real coaching agent, I needed to give it hands—ways to check injuries, recall workouts, and manage schedules.
Building an Agentic Personal Trainer - Part 1: Architecture and Philosophy
After building an [autonomous stock trading system](https://www.mosaicmeshai.com/blog/building-an-mcp-agentic-stock-trading-system-part-1-the-architecture) with custom MCP servers, I wanted something different: a conversational AI that collaborates rather than executes. Something that asks "how are you feeling?" before suggesting a workout.