We Rebuilt Our SDLC Around AI Agents. Here's the Architecture, the Mistakes, and the 300% Number

This story was originally published on HackerNoon at: https://hackernoon.com/we-rebuilt-our-sdlc-around-ai-agents-heres-the-architecture-the-mistakes-and-the-300percent-number. We rebuilt our SDLC around AI agents and achieved 300% faster development. Learn the architecture, rollout strategy, quality gates, and key lessons. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #ai-agents, #ai-dev, #agentic-sdlc, #ai-software-development, #ai-development-agents, #ai-engineering-workflow, and more. This story was written by: @sergii-kravtsov. Learn more about this writer by checking @sergii-kravtsov's about page, and for more stories, please visit hackernoon.com. AI doesn't significantly accelerate software development when it's simply added to an existing workflow—it does when the SDLC is redesigned around specialized AI agents with clear roles, persistent context, and automated quality gates. In this article, Sergii Kravtsov shares how Evergreen and ConnectiveOne rebuilt their development process, achieving roughly 300% faster development velocity through an agentic SDLC, along with the architecture, rollout strategy, common pitfalls, and practical lessons learned from running it in production.