AI Coding Setup

AI coding field guide

Build with AI. Keep control.

Practical AI coding setup guides for Claude Code, Codex, Cursor, Copilot, and coding agents. Configure tools, workflows, repository instructions, MCP servers, and permissions.

Choose a setup Fix a problem
Setup systemTask to reviewed release
Brief
Agent
Evidence
Release
3

roles: build surface, coding agent, independent checks

1

owner: a person decides what is ready to ship

Definition of done

Expected behavior works, failure is handled, access is correct, and rollback is ready.

Start here

Configure the part of your AI coding workflow that matters now.

Claude Code setup

Install, verify, sign in, and connect it to reviewable repository work.

Open guide path →Codex setup

Install the CLI and structure delegated tasks around instructions and approval.

Open guide path →Cursor setup

Install the editor and build a workflow with reliable context and indexing.

Open guide path →AGENTS.md

Copy repository instructions agents can discover and verify.

Open guide path →CLAUDE.md

Copy concise Claude Code project guidance with validated commands.

Open guide path →MCP and permissions

Add integrations with explicit access and failure boundaries.

Open guide path →Troubleshooting

Diagnose context, indexing, output, and production failures.

Open guide path →Templates

Turn reusable structures into repository-specific instructions and checks.

Open guide path →

Most AI coding problems are workflow problems.

A better model cannot fix a vague task, missing context, broad permissions, or an app that was never tested with real data. AI Coding Setup focuses on the decisions between the prompt and production.

Why this exists

The work is moving from assistance to supervised execution.

Agent-first workParallel

Coding work is shifting from one chat at a time to several isolated agents with a person directing the result.

Human advantageDirection

Research on real coding sessions finds that people still lead planning while agents take more execution work.

Production gapControl

Production agent systems now emphasize approvals, sandboxes, durability, telemetry, and security checks.

Popular problems

Fix the failure before changing your whole stack.

Cursor indexing is stuck

Check workspace scope, progress, ignore rules, network diagnostics, and extensions in order.

Open troubleshooting path

Codex login keeps failing

Inspect auth state, reset stale credentials, or use the device flow on remote terminals.

Open troubleshooting path

An MCP server will not connect

Separate discovery, startup, transport, authentication, and tool-list failures.

Open troubleshooting path

AGENTS.md is not working

Check the new-run discovery chain, working directory, overrides, conflicts, and size limit.

Open troubleshooting path

Choose by experience

Use the path closest to the work you do now.

I have an idea, not a codebase

Start with a managed app builder

Build one complete user flow, then verify login, data access, forms, deployment, and rollback before inviting real users.

Build your first website safely

I can read code and need to ship

Start with an AI editor and one coding agent

Keep the stack small, isolate larger tasks, review every diff, and use preview deployments as the final check.

Choose a practical setup

I need agents to work on a real repository

Start with instructions, worktrees, tests, and approvals

Make tasks executable, control permissions, and require evidence at handoff before a person merges or releases the result.

Set up an agent workflow

Complete guide path

Move from first build to a controlled release.