AI
Building Java-Native AI Agents with Google ADK
This blog explains how Google ADK for Java helps enterprises get the most out of the Java ecosystem.
Do Not Trust, Always Verify Twice!
A widespread breach of school platforms highlights how BOLA vulnerabilities expose sensitive data. Learn what BOLA is, why traditional security misses it, and how to secure APIs with robust relationship checks.
AI
Building a Secure Spring Boot MCP Client for Legacy Inventory Integration.
Learn how to build a secure Spring Boot MCP client that enables AI agents to connect with your legacy inventory server, discover and use tools at runtime, and implement robust security measures against prompt injection and other risks.
AI
How to Expose a Legacy Spring Boot App as an MCP Server Using Spring AI
Learn how to wrap legacy Spring Boot apps as MCP servers using Spring AI, enabling AI agents to interact with your backend via a unified protocol. The guide covers setup, adapter design, and practical tips for fast AI integration.
Team
How to Master Progressive Rollouts and Incident Recovery
This blog covers safe software releases using strategies like canary releases and feature flags, stressing testing, monitoring, fast rollbacks, and a blameless culture. It highlights leadership, checklists, and AI-driven remediation as future trends.
Managing Up: How to Share What You Measure with Leadership
When you share engineering metrics with executives, link each one to a key business goal. First, find out which outcomes matter most to your leaders, such as cutting costs, speeding up delivery, or improving product quality. Next, figure out which engineering work supports those goals and choose metrics that show
Writing
How I Learned to Write for Everyone.
William Zinsser’s "On Writing Well" teaches that clear, simple writing connects with readers. Cut out jargon, focus on clarity, and rewrite for conciseness. The book’s advice makes non-technical writing approachable and enjoyable for everyone.
Metrics
The Metrics Trap: How Engineering Metrics Obsession Can Crumble Your Engineering Culture
Obsessing over engineering metrics can harm team culture and block innovation. Use metrics for reflection, not as strict targets. Separate AI and human outputs, prioritize psychological safety, and focus on meaningful improvement over chasing numbers.
Security
Stop Shipping Security Debt: How to Turn a Crisis into a Secure Engineering Culture
A team works best when it can quickly find and fix system issues. Speed and accuracy both matter. Success also depends on how much risk the organization is willing to take and how much technical debt stands in the way of fixing big security problems. 💡The answer is not to
AI
Team Agreement: Our AI-Human Collaboration Charter
1. Our Core Principle We use AI to help us do more, but we don’t let it replace our own judgment. We are fully responsible for every line of code, every design choice, and every customer interaction, even if AI helped us. 2. Roles & Responsibilities We’ve set
AI
The AI-Human Workflow Matrix: A Guide for Modern Development Teams
As we built modern, efficient teams, our true goal emerged: work smarter while retaining the personal touch that makes our products special and delights our customers. To address these needs, we created the AI-Human Workflow Matrix. This structured approach helps us decide when to assign tasks to AI rather than
Feedback
The Heart of the Code Review: My Experience With Quality and Culture
Code reviews are more than bug catching—they foster team trust, knowledge sharing, and quality. AI tools help, but human feedback ensures robust, readable code and a healthy engineering culture. People first, code follows.