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A curated walkthrough of the library — ordered lessons, a 15-question quiz between each, and 3 next-steps so you stay in flow. Earn XP, badges, and a streak as you go.
Library · 6440 lessons · Coding view · Codex
You are viewing coding lessons focused on Codex. Use the tool lanes below to jump sideways into related workflows.
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Start with a real app or workflow. Each lane filters the library to practical lessons, not just broad theory.
702 lessons in coding
Lessons handpicked for the Codex shelf.
Claude Code (Anthropic) and Codex CLI (OpenAI) are both terminal agents — different vibes, similar power.
Codex cloud can work in the background and in parallel. Learn how to split tasks so multiple agents do not trample the same files.
The AI coding tool market fragmented fast. Let's map the 2026 landscape honestly: who is for autocomplete, who is for agents, who wins on cost, and what the tradeoffs actually feel like.
Codex CLI is OpenAI's terminal coding agent. It runs locally, supports MCP, and ships a codex cloud mode for background tasks. Let's install it and compare it honestly to Claude Code.
Fresh Codex lessons added to the library.
AI helps engineers wire OpenAI Codex CLI into build pipelines as a first-class step.
Claude Code (Anthropic) and Codex CLI (OpenAI) are both terminal agents — different vibes, similar power.
Use cloud agents for bounded, parallel tasks that can land as branches or PRs while you keep working locally.
Codex reads project guidance files so the agent can follow local conventions. Scope and precedence decide which instruction wins.
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Follow a real agent run step by step — from prompt to result — and see exactly what happens inside. No code yet, just the anatomy of a successful task.
Agents are only as useful as their tools. Tour the big three — filesystem, browser, code execution — plus the emerging MCP ecosystem, with examples of what each unlocks.
No code. Just design. Pick a real task you do every week and draft a complete agent spec — goal, tools, loop, stop, approvals, and what success looks like.
An AI agent is AI that takes ACTIONS, not just answers questions.
A trace is the full record of what an agent did and why.
Cursor, Claude Code, and GitHub Copilot Workspace are agents specifically for writing software..
How much you should trust an agent depends on what it can do.
Want to learn something cool? AI can build a custom learning plan with resources, exercises, and milestones. Powerful for self-directed learning.
Claude Code, Cursor, and other coding agents can work on real coding projects with you. Like having a coding partner.
You can build a custom AI tutor that knows your curriculum, your weaknesses, and how you learn best.
AI coding agents (Claude Code, Cursor) can build a personal website for you with little coding from you. Real teen tool.
Portfolio projects matter for college and jobs. AI agents help you build bigger, more ambitious projects than you could alone.
Some teens run real small businesses. AI agents handle scheduling, customer messages, even pricing. Real income.
School clubs need websites for meetings, signups, photos. AI helps you build one and update it through the year.
How a teen entrepreneur could use agents to handle the boring side-hustle work.
How AI agents can help juniors and seniors track colleges, deadlines, and essay drafts.
How student leaders can use AI agents to help organize a real volunteer event.
How an agent can build a five-minute morning news digest tailored to what you care about.
An AI agent can build, track, and adjust a workout plan that learns what you actually do.
If you lead a club, an AI agent can handle agendas, follow-ups, and member tracking.
An agent can build cases, find counterarguments, and quiz you the night before a tournament.
An agent that designs daily practice plans for your instrument.
An AI agent that handles outfit, group, dinner, and afterparty in one go.
An AI agent like Claude Code or Manus runs steps on its own — a chatbot just talks back.
Claude Code can finish multi-step coding tasks unattended — but only if you fence in what it can touch.
Permission prompts in Claude Code, Cursor Agent, or Copilot Agent are the safety net — read them, don't auto-approve.
Watching the agent's plan and reasoning catches mistakes 30 seconds before the agent makes them.
Agents loop, and every loop iteration uses tokens — that's why agentic costs add up faster than chats.
Claude Code's Task tool launches mini-agents in parallel — way faster than one agent doing everything itself.
For one-off questions, a regular chatbot is faster, cheaper, and less risky than firing up an agent.
The 'stop and ask me' instruction is a power move — agents don't know what they don't know.
Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.
Add a budget so the agent stops before it spends $50.
Use an SDK like Claude Agent SDK or Vercel AI SDK to ship a working agent today.
Make, n8n, and Zapier let you build agent-style automations with zero code — perfect for your first real automation.
Real AI power comes from chaining 5 prompts that build on each other, not asking one big question.