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
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
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
Code review has always been a sign of a healthy team and our last line of defense against expensive mistakes, whether we used paper in the 1970s or AI tools today. It reminds me that responsibility and teamwork have always mattered in this process.
In the last post, I wrote that creating a common bond helps create a culture of respect and shared goals. In any convertion having a clear structure helps reduce anxiety for everyone in these conversations. Here are two templates I use to keep things focused, supportive, and effective.
This blog explores how software engineering leadership is less about rigid status updates and more about building a "Common Bond" to drive growth. A good 1-1 serves as a psychological "growth lab".