AI agents are built to accommodate. They say yes, they make it work, and they skip the hard questions. Two words changed that for me — "first principles" shifted my agents from implementation-mode to reasoning-mode during design work.
I rewrote my agent context system three times. The first was too shallow. The second was thorough and almost completely wasteful. The third works — because I stopped thinking about what agents should know and started thinking about what they should load.
Why your AI agents keep getting it wrong, and how the Trinity of Clarity — agent context, environment context, and strong interaction — transforms your results.
A developer-friendly breakdown of multi-agent patterns by mapping them to OOP concepts you already know - from console apps to enterprise helper classes.