“I've used GEPA successfully in the context of pretraining data curation at Microsoft AI, so I thought I'd give a brief overview of why I reach for this tool :)”
An open-source declarative framework for building modular AI software. Programming—not prompting—LLMs via higher-level abstractions & optimizers.
Joined April 2025
- “In a way, Machine Learning asks how a system can improve from data when we have a precise objective to optimize. Machine Studying asks what an agent should do when it’s given a declarative corpus and no downstream task.”Continual learning is widely discussed right now, but mostly as improving on the job or avoiding catastrophic forgetting. But it has a different, difficult, and already urgent form: Given nothing but a corpus of documents, how should AI systems develop expertise in a new,
- a crisper operationalization of continual learning that matches problems that are inaccurately treated as "RAG" or "RL" read the thread below from @jacobli99 or the blog post at jacobxli.com/blog/2026/mach…Continual learning is widely discussed right now, but mostly as improving on the job or avoiding catastrophic forgetting. But it has a different, difficult, and already urgent form: Given nothing but a corpus of documents, how should AI systems develop expertise in a new,
- "the real opportunity is not in picking the best model but instead in building a learning loop on top of the model [and allowing them to] grow stronger on real traces from inside the organization" the only framework for doing nothing but this since 2022 is right here😁






