Introduction For several years, I adopted Conventional Commits across my software projects. The premise was straightforward: write commit messages in a structured, machine-readable format, then leverage tooling to generate changelogs and release notes automatically. For example: feat: add user login fix: resolve payment retry issue docs: update API usage guide This approach served me well. Tools like Conventional Changelog could parse commit history and produce structured release notes with minimal manual effort.

Sometimes people look at my profile and wonder: “How can you keep learning so many things? What is your secret?” The truth is, there is no magic. My approach is simple: I write things down, practise important skills repeatedly, and choose technologies carefully after real hands-on exploration. 1. I Write Down What I Learn Whenever I learn something useful, I try to capture it. Sometimes I write it as a blog post.

What is GEPA? GEPA stands for Graph-based Evolutionary Program Adaptation — a DSPy optimizer that automatically improves the prompts/instructions of a multi-module LLM program through evolutionary search. It iteratively mutates module instructions, evaluates the changes, and keeps the best-performing candidates on a Pareto front. What’s Happening in This Run This file captures a GEPA optimization run on a financial news extraction system that classifies M&A (merger/acquisition) articles and extracts structured data from them.