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Pragmatic field notes on AI agents, MLOps, cloud architecture, and engineering systems.
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AI coding agents amplify repository friction. Here is how we redesigned an MLOps codebase around deterministic single-command gates, SQLite isolation, and machine-readable AGENTS.md guardrails.
Bridge the gap between engineering specs and AI agents using Agent Skills. Learn to inject ‘Senior Engineer’ context for production MLOps.
Building AI applications is incredibly exciting. But let’s be honest: getting started can be challenging, especially in large…
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 to Uv: A faster, simpler way to manage dependencies for MLOps projects.
The Cookiecutter MLOps Package offers a powerful code template to jumpstart your MLOps journey and accelerate your AI/ML development…
This article dives deep into the essential tools and practices for achieving comprehensive observability in your AI/ML projects.
The MLOps Coding Course is an open-source resource specifically designed to bridge the gap between data science and software engineering.
MLOps projects are straightforward to initiate, but challenging to perfect. While AI/ML projects often start with a notebook for…
The MLOps ecosystem is evolving into a sophisticated symphony, composed of diverse tools, methodologies, and cultures. This diversity…
Programmers have always been passionate about their preferences, whether they discuss spaces vs. tabs, Vim vs. Emacs, or light mode vs…
While the future of machine learning and MLOps is being debated, practitioners still need to attend to their machine learning models in…
MLOps practitioners (rightfully) point out that running notebooks in production is a bad software practice, but what are the alternatives…
Large Language Model (LLM) is such an exciting topic. Since the release of ChatGPT, we saw a surge of innovation ranging from education…
There is an ever-growing landscape of tools and solutions for MLOps. In this article, I propose a solution to address this challenge.