3 months building production apps with AI coding tools (medium.com)

Over three months the author built multiple production apps without writing a single line of code from scratch—citing a watershed moment when an AI produced a real-time chat app with authentication, encryption, and a React frontend in about 20 minutes. This isn’t just better autocomplete; it’s a move to agent-driven development where tools generate, wire together, test and deploy full stacks. The story highlights Google’s Antigravity (released alongside Gemini 3 in Nov 2025) as a tipping point: an “agent-first” IDE that uses autonomous agents to plan, execute and verify end-to-end workflows across services, effectively shifting the cognitive load from line-by-line coding to high-level orchestration and verification. For the AI/ML community the implications are twofold: technical opportunity and new risks. Technically, agent architectures, tool integrations, and model-in-the-loop verification become core research and engineering priorities—improving reliability, provenance, and automated testing for generated systems. Practically, teams must rethink developer roles (prompt and system designers over syntax experts), CI/CD for model-driven pipelines, and governance around security, hallucinations, IP and compliance. In short, the era of model-native software delivery demands robust guardrails, evaluation metrics, and tooling that make autonomous agents safe, auditable and production-ready.