The Deploy That Looked Clean Two agents, one story: “you handle the flow, I’ll handle the page layout.” Reasonable split — except we hadn’t split the object, we’d split the request. Both agents ended up touching the same page-layout XML in the same run. One added a related list for open cases. The other reordered two fields per a design note from three sprints back. The deploy went out clean. Zero errors, zero warnings. ...
Forget the “Golden Age of Agile.” That party is over. We are currently living through the most aggressive inversion of software engineering since the compiler replaced punch cards. If you’re still measuring success by your ability to close Jira tickets or write clean syntax from scratch, you are essentially manually tuning a channel on a transistor radio while the rest of the world is streaming 4K video. We have moved beyond “tools” and into the era of the AI-Driven Development Life Cycle (AIDLC)—an ecosystem where the machine doesn’t just assist the work; it executes the work. ...
Everyone is building chatbots right now. It’s the “Hello World” of the AI era! But here is the dirty secret of Enterprise AI: Latency and Tokens are the new technical debt. If you simply paste a Python demo into a Salesforce Flow, you aren’t building an agent—you’re building a generic “chat” interface that burns cash and hits timeouts. I learned this the hard way. I set out to build Revenue Radar, an agent that analyzes massive 40-page earnings calls. ...