I’ve been using Google Antigravity everyday since it was first released at the end of 2025. After six months into this new technology, I swung the gavel. This is the year I stop coding things by hand. No more loops, semicolons, classes, interfaces, and constructors for me. At one time I was extremely passionate about that stuff, now it seems pointless. The real magic lies in the ecosystem's dual-entry point. I treat the Gemini mobile app as my 'Architect-in-Residence.' Because its system instructions are tuned for broad reasoning rather than immediate file manipulation, it’s less likely to get 'tunnel vision' on my current implementation. It’s where I voice-chat through high-level logic and iterate on Mermaid diagrams. Once the blueprint has been created, I hand it to Antigravity. Unlike the mobile app, Antigravity is grounded in my specific workspace—it understands my repo's unique quirks, can run my terminal, and fix the very bugs it might have just introduced. Using both allows me to cross-examine a solution from two distinct vantage points: pure architectural theory and local technical reality. My initial design and architecture conversations always start with the Google Pro model. The Pro model is much better at reasoning problems with many pieces than the Gemini Fast model, however the Pro model consumes a lot of tokens. Under the AI Pro plan, I can usually use the Pro model once a week before I run out of tokens. I try to plan my work week around when the Pro model will be available again. Part of my design process usually involves creating a sequence diagram using the Mermaid markup language. I perform several iterations until “the perfect” sequence diagram is built. Once the diagram is built and I have a solid grasp of the solution, I will switch over to the Gemini fast model for the actual implementation using the sequence diagram as a guide. I will switch back over to the Pro model only when the fast model gets stuck. To manage the inherent unpredictability of Antigravity, I established a dedicated guidelines and guardrails repository. This repository is programmed to be read and verified by Antigravity whenever I initiate a session with a simple "hi." Whenever Antigravity deviates from the intended path, I update this directory with new rules to ensure Antigravity remains properly aligned. Writing software using AI is certainly different from the “classic” way of writing software by hand. You definitely have to stay on top of it, test and monitor its changes. I periodically execute git status to see what the AI has changed. Sometimes the AI will break something in your application that is not related to anything you’ve been working on, so regression testing is an absolute must. When I build solutions with AI build sections at a time, testing and documenting things in a ReadMe file and commit code only when things are working correctly. I like to make sure that the code project stays organized, and the interfaces between components are clean and easy to understand. I tell people to use AI responsibility to grow your understanding in areas that you do not understand. It’s very tempting to throw a blanket over everything and let AI do all the work for you. AI can build things faster than humans can comprehend it. It’s up to us to dedicate the time to understand the moving parts under the hood. Integrating AI into my software development process has unexpectedly sharpened my verbal communication skills, as the technology demands absolute clarity to be effective. While AI is far from infallible, it is no more flawed than the humans who use it. The combination of AI and cloud computing has democratized innovation. All you need is an idea and one person can create an app that can change the world.