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.
Git Hooks Not Running in a Worktree? Fix the Path
Find why Git hooks stop running in agent worktrees, inspect the effective hooks path, and configure shared or per-worktree hooks safely.
Parallel Coding Agents and Duplicate MCP Servers
Learn why parallel agent sessions launch duplicate MCP server processes and how to disable unneeded servers in Claude Code, Codex CLI, and Gemini CLI.
How to Detect When Codex Exec or Claude Code Finishes
Learn to distinguish completed, failed, and stalled Codex exec or Claude Code headless runs using process status, JSON events, time limits, and review checks.
Cherry-Pick a Commit Between Git Worktrees
Learn how to cherry-pick one completed fix between Git worktrees, resolve conflicts, check dependencies, and keep both agents' branches separate.
How to Update a Git Worktree Branch From Main
Learn to update a Git worktree branch from main during an active agent task, protect unfinished edits, resolve conflicts, and review the result.
Git Worktree Branch Already Checked Out: Safe Fixes
Fix the Git worktree branch already checked out error: find the owning worktree, inspect agent edits, and safely reuse or release the branch.
Why AI Agent Worktrees Miss Uncommitted Changes
Learn why AI agent worktrees miss edits in your main checkout, then use a commit, stash, or patch to give an agent the changes it needs.
Gemini CLI --worktree for Parallel Sessions
Enable Gemini CLI worktrees, launch concurrent sessions in separate directories, and review, merge, resume, and clean up their changes.
Resume a Coding Agent Session in the Right Git Worktree
Learn how to find the right Git worktree, check its branch and pending changes, then resume a Claude Code, Codex, or Gemini CLI session safely.
Parallel AI Coding Agents: Handle 429 Rate Limits
Handle 429 rate limits in parallel AI coding agents: identify shared quotas, stagger sessions, and retry temporary errors without wasting requests.
Clean Up Stale AI Agent Git Worktrees Safely
Learn to clean up stale AI agent Git worktrees by auditing files and commits, preserving unfinished work, and removing worktrees and branches safely.
Parallel AI Agents: Stop Sharing a Test Database
Learn how to give each parallel AI agent its own test database, run migrations safely, isolate Compose stacks, and verify connections before tests.
AGENTS.md and CLAUDE.md: One Context File for Every Agent
Claude Code, Codex, Gemini CLI, and Copilot CLI read different instruction files. How to keep one source of truth without duplicating it four ways.
Is It Safe to Run AI Coding Agents With Permissions Off?
Skipping approval prompts is not the same as sandboxing. What each agent's permission and sandbox settings actually enforce, and what parallel runs change.
How to Merge Work From Parallel AI Agents
Parallel agents finish on separate branches. A practical integration workflow: test the merges before you run them, pick an order, and keep main releasable.
How to Run Multiple Claude Code Agents in Parallel
Run multiple Claude Code agents with worktrees, agent view, subagents, cloud sessions, or Parallel Code—and know when to choose each approach.
How to Use Claude Code and Codex Together: 4 Practical Workflows
Use Claude Code and Codex together for parallel tasks, cross-review, handoffs, and races—with isolated working copies when both agents write.
How to Run Multiple Codex Agents in Parallel
Run multiple Codex agents using the desktop app, CLI worktrees, subagents, cloud tasks, or Parallel Code—and know when to choose each approach.
How to Write Better Prompts for AI Coding Agents
A practical AI coding agent prompt template for clearer scope, focused diffs, stronger verification, and fewer avoidable retries.
AI Coding Agent Best Practices: A Practical Workflow
Use AI coding agents without losing control. These 10 best practices cover task scope, worktree isolation, tests, review, security, cost, and merging.
What Does Running Multiple AI Agents in Parallel Actually Cost?
Learn how subscriptions, metered APIs, repeated context, and redundant races affect the real cost of running multiple AI coding agents.
Running AI Coding Agents on Linux: Your Real Options
Most AI agent orchestrators are macOS-only. Here's what actually runs on Linux — native GUIs, terminal tools, and the CLIs — and how to pick one.
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 one codebase without working-copy collisions or merge chaos.
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.
AI Agent Isolation: Separate Working Copies for Concurrent Tasks
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.