Luiz Mendes

GuaxiCast

Technology EN ↓ 3 episodes

After years in data science — co-founding Hekima (acqui-hired by iFood) and leading Recommendation Data Science there — Luiz Felipe Mendes left a stable job, took a sabbatical, and went back to the keyboard to build the apps he always wished existed. GuaxiCast is the audio companion to his writing: short, candid episodes about building software with AI sitting right next to you. Expect honest field notes on vibe coding, the real cost of AI dev, choosing the right model for the right task, the Skills/Rules/Agents meta-layer, data science, and the messy reality of shipping products solo. It's bu...

Author

Luiz Mendes

Episodes

Beyond the Model: Building Production-Ready Machine Learning Systems 21.06.2026 18:30

In this episode, we explore the reality of taking machine learning out of the classroom and into the real world. While many believe that modeling is the core of AI, it is often the smallest and sometimes the "easiest" component of a successful system. We break down the complete, iterative workflow required for industry success—from Project Setup and Data Pipelines to Modeling and Serving . Drawing...

Beyond the Prompt: Building Robustness in the Age of AI Agents 08.06.2026 19:27

Episode Overview In this episode, we dive into the insights of data scientist and entrepreneur Luiz Felipe Mendes as he explores the shifting landscape of Artificial Intelligence. We move beyond simple LLM prompts to discuss the rise of AI Agents —autonomous programs that don't just talk but act . We also tackle the critical need for ML Prediction Robustness , examining why large-scale systems lik...

Is AI Evil? Revisiting "Coded Bias" in the Age of LLMs 08.06.2026 23:21

Netflix's documentary Coded Bias argues that machine-learning systems quietly absorb the sexism and racism of the society that builds them — and that facial recognition in the hands of governments and big tech raises serious privacy stakes. In this episode, drawn from Luiz Felipe Mendes' 2021 essay (updated for the GPT era), we walk through what the film gets right, where it oversimplifies, and wh...