How to Run Coding Agents in Parallel
Last Updated on February 17, 2026 by Editorial Team
Author(s): Eivind Kjosbakken
Originally published on Towards AI.
Get the most out of Claude Code
In the last few years, coding agents have become more and more prevalent. Initially, coding agents could only auto-complete specific lines of code. We then experienced how agents could interact with a single file and make changes to entire functions. After this, we started seeing agents capable of keeping track of and updating code in multiple files.

The article explores the increasing capabilities of coding agents in software engineering and emphasizes the importance of running multiple agents in parallel for maximum efficiency. It provides techniques for effectively utilizing coding agents, such as creating a prioritized task list, using plan mode for detailed interactions, and leveraging tools like Claude Code or Gemini CLI for managing multiple agents simultaneously. The author argues that integrating these practices can significantly improve productivity and effectiveness in programming tasks.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.