Writing
Pragmatic field notes on AI agents, MLOps, cloud architecture, and engineering systems.
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.
Running a remote Model Context Protocol (MCP) server behind multiple instances presents immediate infrastructure challenges. Because the…
As AI agents transition from isolated developer experiments into production-scale workflows, engineering organizations are waking up to a…
Most coding-agent tasks have one right answer hiding behind a workflow. “Add password sign-in.” “Fix the off-by-one in the pagination…
A coding agent is only as useful as the spec you give it. That sentence sounds like a truism until you watch it play out for an afternoon.
Pair-program with a coding agent for an afternoon and you start noticing a quiet, recurring tax. Every time the agent reaches for a flag, a…
The AI providers are in a horse race. Every quarter, a new model lands, a new harness ships, and the gap between “the best tool for this…
We are building the most advanced AI systems in history, yet the best way to control them relies on paradigms from the 1970s. I see…
AI Coding — or Spec-Driven Development — is a recent trend that amazes as much as it scares IT engineers. We now have access to powerful…
I see many friends and acquaintances generating amazing applications in mere weeks. We are in the midst of a craze of innovation, an era…
Build a cost-effective, private AI Agent solution on Google Cloud using Chainlit and Vertex AI. Detailed architecture and code guide.
Build a personal AI assistant using Google Cloud Run, Vertex AI, and Google Chat. A guide to architecting context-aware agents.
Building AI-First apps with A2UI: from the Agent-View-Controller (AVC) pattern to managing latency. A practical case study with Featest.
Bridge the gap between engineering specs and AI agents using Agent Skills. Learn to inject ‘Senior Engineer’ context for production MLOps.
Discover how A2UI solves the AI Agent UI bottleneck. A deep dive into replacing chatbots with agents that project their own native UIs.
Build a production-grade AI Agent Platform. A guide to the 7-layer architecture for scaling secure, autonomous enterprise agents.
Power up your AI agent in production. Learn to deploy a secure ‘Slides Translator’ using ADK, OAuth, and Gemini Enterprise.
For AI agents, the biggest challenge isn’t the model, it’s the UI. A deep dive into the user interface bottleneck for enterprise AI.
For decades, the story of data platforms has been one of centralization and heavy engineering. We built massive data warehouses and data…
Speed up AI agent development on GCP with Ackgent. Build, deploy, and iterate faster using Google ADK and Agent Config's declarative approach.
Build custom AI image workflows fast with Combo-Banana. Empower designers to automate tedious editing tasks with Google Nano-Banana.
I’m incredibly excited to announce the launch of the first video series for my MLOps Coding Course, covering the introduction and the…
Learn to deploy AI agents in the enterprise using ADK & Google Cloud. We compare Cloud Run & Vertex AI for secure, scalable AgentOps.
A father tests Gemini AI’s coding skills to create a magical birthday for his 6-year-old. See the staggering results from Deep Think!
It is a classic tale of corporate life. A colleague of mine at Decathlon had a mammoth task: translate a 155-slide presentation into…
A guide to creating conversational AI with Gemini. Generate custom educational audio with multiple voices using a simple Python script.
Agentic Cloud: Disrupting cloud giants with AI. Learn how intelligent agents will commoditize hyperscalers & reshape infrastructure.
Navigate the challenges of scaling LLMs on GCP and get benchmark insights for cost-effective, reliable, and quick LLM serving.
Explore the shift from slow data pipelines to real-time API management for building Gen AI systems and modern enterprise data architecture.
Build & deploy a RAG app in minutes! Use Vertex AI Studio & Vertex AI Search for a rapid hackathon win. Ground LLMs with your data.
In the fast-paced world of content creation, efficiency is key. Manually crafting social media posts for different platforms based on a…
CAG vs RAG for Generative AI: Compare latency, cost & complexity. Choose the best LLM context strategy for your app.
As developers and AI practitioners, many of us belong to vibrant online communities, like the MLOps Community on Slack. These platforms are…
A Python notebook agent that reviews GitHub repositories against your own guidelines automatically, using Google Colab, the GitHub API, and Gemini models.
Video meetings on platforms like Google Meet are essential for collaboration, but how often do crucial details get lost moments after the…
Team collaboration often lives and breathes within chat applications like Google Chat or Slack. It’s where questions are asked, decisions…
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!
Meet Kate: an AI-powered, live, multimodal website assistant. She uses voice, understands your needs, and retrieves info from a website.
Explored Gemini’s long context in a Kaggle competition. Key lessons learned about its potential and limitations for real-world…
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.
Tame your Python chaos! Learn how pyenv simplifies managing Python versions for AI/ML & MLOps, ensuring smooth, reproducible development.
The AI landscape is constantly evolving, pushing the boundaries of what’s possible with technology. One of the most exciting frontiers is…
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…
Visual Studio Code is a remarkable application. In the past, developers faced a choice between simple, lightweight text editors like Vim…
If you have checked the Internet in 2023, you’re likely familiar with Generative AI. The launch of ChatGPT has sparked a surge in interest…
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.
Kubeflow Pipelines (KFP) is a powerful platform for building machine learning pipelines at scale with Kubernetes.
A fundamental trade-off that affects the design of programming languages and the success of software projects.