Building a Self-Improving Productivity Coach: Agentic AI With Meta-Reflection, Episodic Memory, and Streamlit

Author(s): Kyle knudson Originally published on Towards AI. Building a Self-Improving Productivity Coach: Agentic AI With Meta-Reflection, Episodic Memory, and Streamlit Most people track their day. Some reflect on it. Very few learn from it and almost no one has an AI agent that learns how to coach them better over time. This agent doesn’t just summarize your workday. It doesn’t just give you goals. It actually evaluates its own performance and rewrites its internal coaching guidelines based on real outcomes.The article outlines the creation of a self-improving productivity coach that utilizes various AI technologies to learn from user interactions. It explains how the agent evaluates its coaching effectiveness, incorporates episodic memory, and maintains structured data of user activities. The author emphasizes the coach’s ability to adapt to the user’s unique work patterns and needs through continuous refinement of its guidelines, ultimately aiming to enhance personal productivity and effectiveness over time. Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI