Claudio Masolo·Oct 28Slow Down to Speed Up: Why Studying the Cloud is More Important in the Age of AIThe “Prompt-and-Deploy” era is here. But if you don’t know what’s happening under the hood, you aren’t building a system, you’re building a…
Claudio Masolo·Apr 10The prompt is the new specThere’s an engineer on almost every team I’ve worked with who had a particular skill: they could hold an entire feature in their head…
Claudio Masolo·Mar 31The Note You Didn’t Write Is Now a BugThere’s a PR in the queue. The code is clean. The tests pass. The AI generated most of it in under two minutes, which felt impressive at…
Claudio Masolo·Dec 12, 2025From Slack Messages to Searchable Knowledge: My Note-Taking System for Distributed TeamsEvery day, thousands of important decisions happen in Slack channels. A product manager explains why they chose feature A instead of…
Claudio Masolo·Dec 5, 2025The Engineer’s Secret Weapon: Why Note-Taking Matters More Than You ThinkAs engineers, we love to think we’ll remember the clever solution we found at 2 AM, or the specific configuration that finally made that…A response icon1A response icon1
Claudio Masolo·Sep 23, 2025Real-World Example: Complete Application SetupThis is the second part of the post: ConfigMaps and Secrets: Managing Configuration in Kubernetes
InDevOps.devbyClaudio Masolo·Sep 15, 2025ConfigMaps and Secrets: Managing Configuration in KubernetesWhen you’re building applications for Kubernetes, one of the first challenges you’ll face is: “Where do I put my configuration data?”…
Claudio Masolo·Sep 2, 2025Go 1.25: Container-Aware Runtime and Experimental Performance BoostsThe release that finally makes Go truly container-native
Claudio Masolo·Jul 29, 2025The Hidden Cost of Docker Images: Why Multi-Stage Builds Are Essential in 2025In the era of microservices and cloud-native architectures, containerization has become the backbone of modern software delivery. Yet, many…
Claudio Masolo·May 16, 2025Performance Metrics Monitoring: The Heartbeat of Your Machine Learning ModelsAre your machine learning models performing as expected in production? Or are they silently deteriorating, making increasingly inaccurate…
