"Which AI agent should I use?" is the wrong question. The right question is: what are you trying to…

"Which AI agent should I use?" is the wrong question. The right question is: what are you trying to automate — and at what level? Most people haven't mapped that out yet.

Here's how I think about it: three layers — execution (doing the work), workflow (coordinating the work), and governance (managing who does what, at what cost, with what guardrails). Different tools, different jobs.

Execution layer: Cursor, Claude Code, Codex CLI. Cursor gives you an AI-first editor with tight inline integration. Claude Code goes deeper — full codebase context, end-to-end task execution, terminal-native. Codex CLI is OpenAI's answer to the same problem. I run Claude Code and Cursor daily; they complement more than they compete. Codex is worth watching if you're deeper in the OpenAI ecosystem.

Workflow layer: Claude CoWork and OpenClaw. CoWork takes the same agentic engine as Claude Code and points it at knowledge work — non-developers, local files, multi-step tasks outside a code editor. OpenClaw is broader: a 24/7 agent workforce across 200+ models, email, calendar, Slack, browser. Not a dev tool — an automation platform. Different job, different configuration discipline.

Governance layer: Paperclip (and LangGraph). This is where it gets interesting. LangGraph gives developers graph-based control over multi-agent pipelines — powerful, but you're writing the plumbing. Paperclip takes a different bet: org charts, budgets, approval gates, configured not coded. Enterprise platforms like UiPath and watsonx have done this for years — Paperclip just made it accessible. 30K GitHub stars in three weeks suggests the timing is right.

This is my mental model of the space right now. What am I not considering?

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