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Writing
Pragmatic field notes on AI agents, MLOps, cloud architecture, and engineering systems.
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How I built GentWriter with Google's ADK: a multi-agent system that turns one article URL into an SEO description, an X post, and a LinkedIn post.
As developers and AI practitioners, many of us belong to vibrant online communities, like the MLOps Community on Slack.
The MLOps Python Package is your go-to solution for building robust and reproducible AI/ML workflows. Check out the latest v4.1.0 release!
MLOps pipelines are often too rigid. We propose using reusable artifacts orchestrated by DAGs. Think functional programming for ML!
Poetry vs uv from a real migration: how I moved the MLOps Python Package to uv, with the pyproject.toml, CI, and Docker changes, and why builds got faster.
Tame your Python chaos! Learn how pyenv simplifies managing Python versions for AI/ML & MLOps, ensuring smooth, reproducible development.
The Cookiecutter MLOps Package offers a powerful code template to jumpstart your MLOps journey and accelerate your AI/ML development.
A method to build robust yet flexible MLOps code bases with Python's ABC and Pydantic, grounded in design patterns and the SOLID principles.
The MLOps ecosystem is evolving into a sophisticated symphony, composed of diverse tools, methodologies, and cultures.
In this article, I will outline the steps for configuring VS Code for data scientists and machine learning engineers.
Programmers have always been passionate about their preferences, whether they discuss spaces vs. tabs, Vim vs. Emacs, or light mode vs. dark mode.
MLOps practitioners (rightfully) point out that running notebooks in production is a bad software practice, but what are the alternatives?
