AI SDLC Pipeline: 5 Agents/Fully Autonomus

The Problem with "AI-Assisted" Development Most AI coding tools today are autocomplete on steroids. They make you faster at typing , but the fundamental loop hasn't changed: you still decompose requirements, design architecture, write code, write tests, and review — one step at a time, context-switching between roles. What if you could delegate the whole loop ? That's the question behind AI SDLC — a multi-agent pipeline where a chain of specialised AI agents handles every phase of the software development life cycle. You write a plain-English task description. One command later, you have: A structured software specification A full technical design with an implementation checklist Working Python source code pytest unit tests (edge cases included) A code review with severity-coded issues No scaffolding. No boilerplate. No switching tabs. The Landscape: Agentic AI Frameworks in 2026 Before diving into the implementation, it's worth understanding where this fits in the current ecosystem. A