2025-12-11 –, Machine Learning & AI
In this talk I will cover frequent AI system problems caused by using prompts and opaque frameworks instead of a descriptive programmatic approach, using DSPy.
Most LLM frameworks are too opaque and obscure what they are doing. New state of the art models are released every week and different models respond differently to the same prompts. These framework's hardcoded prompts within the library make it difficult to debug, update and improve the system. Also, walls of text are a terrible way to program, and hardly maintainable. DSPy is a better way, using abstractions to code your intent into the LLM without defining the prompt, making it future proof. Changing one line, you can change models, tasks or inference strategy.
ML engineer, Data Scientist and author with over a decade in total experience, specially in Finance and Bitcoin industries. I translated several books from English to Portuguese, won prizes in several hackathons with LLM solutions and have been interviewed in dozens of podcasts and newspapers.