Parallelizing AI Coding Agents – AI Native Dev

AI coding environments have evolved rapidly, from simple chat-based prompting, to retrieval-augmented generation (RAG), and more recently to autonomous agents. Each step has improved output quality, but also introduced new workflow patterns. Agent-based coding, for instance, often means longer execution cycles: the agent works autonomously for a while before returning for human feedback.

This shift resembles the transition from a synchronous for-loop to an asynchronous, event-driven architecture. Instead of one AI working step-by-step, we now have multiple parallel coding agents operating independently and reporting back—bringing both speed and complexity.

Source: Parallelizing AI Coding Agents – AI Native Dev