AI Coding Workflow Guides
Practical guides and tutorials on running AI coding agents in parallel, reviewing AI-generated code, and using git worktrees for isolated development workflows. Whether you use Claude Code, Codex CLI, or Gemini CLI, these tutorials help you get more done with less waiting.
Modern AI coding assistants are powerful, but using them one at a time means you spend most of your day waiting. Parallel Code changes that by letting you run multiple agents simultaneously, each in its own git worktree. The articles below cover the techniques and workflows behind efficient parallel AI development — from understanding git worktrees to structuring your review process when agents produce hundreds of lines of code at once.
Racing AI Agents: Run Claude, Codex, and Gemini on the Same Task
Stop guessing which agent is best. Run several on the same task in parallel, then keep the winning diff. How to race AI coding agents and judge the results.
How to Split a Feature Into Parallel AI Agent Tasks
Parallel agents only save time when tasks don't overlap. A practical guide to splitting a feature into independent tasks you can run at the same time.
Multi-Agent Coding Tools in 2026: An Honest Comparison From Someone Who Built One
How to choose between Parallel Code, Nimbalyst, Conductor, Claude Squad, Vibe Kanban, Augment Intent, Gas Town, and Antfarm.
How to Use Multiple AI Coding Agents on One Repo
A practical guide to running Claude Code, Codex CLI, and Gemini CLI on the same codebase — without conflicts, wasted tokens, or merge hell.
Claude Code vs Codex vs Gemini CLI Compared
A practitioner's comparison of the three major AI coding agents — code quality, cost, and speed — with guidance on when to use each.
Git Worktree Isolation for Parallel AI Agents
Why every parallel AI coding agent needs its own git worktree, branch, and working directory before you scale beyond one session.
Git Worktrees: Why AI Agents Need Them
Git worktrees let you check out multiple branches simultaneously from one repo. Here's how they work and why they matter for parallel development.
How to Review AI-Generated Code Efficiently
AI agents write code fast, but reviewing it is the real bottleneck. A practical checklist and workflow for staying in control.