The short answer
The best AI harness for coding is Claude Code or Codex CLI if you work in the terminal, and Cursor if you work in an editor. If you want to pick the model yourself, take an open-source harness such as Aider, Cline, or OpenCode. And if you are building an agent for something other than code, you start from an SDK such as the Claude Agent SDK, the OpenAI Agents SDK, LangGraph, or Pydantic AI.
A harness is the software around a language model that turns it into a working agent: the loop, the tools, the context management, and the limits. How that works is covered in what is an AI harness. This piece answers the question that comes next: which harnesses exist, and which one fits you?
The best AI harness per situation
No harness wins every task. Per situation, the pick is clear.
You write code in the terminal
Take Claude Code or Codex CLI. Both are strong at tasks that touch many files, and both read an instruction file from your repo. The gap between the two is smaller than the gap a good instruction file makes.
You prefer working in an editor
Take Cursor. You see every change as it lands and pick a model from several providers per task. If you work in VS Code and don't want a new editor, Cline is the open-source alternative.
You want to pick the model yourself, or keep everything local
Take Aider, Cline, or OpenCode. You decide which model runs and where your data goes, local models included.
Your task is not code
An agent for customer questions, quotes, or your own systems is built on an SDK. Take the Claude Agent SDK or the OpenAI Agents SDK for a quick start, LangGraph if you want every step pinned down.
You don't know yet
Start with Claude Code or Cursor on a real task from your own work. You learn quickly where it gets in your way, and only then do you know what your own harness needs to do.
Three kinds of harness
The list of names gets manageable once you sort it by one question: how much of the harness do you run yourself?
Ready-made harnesses
You install them and start. The maker handles the loop, the tools, and the limits. You mostly handle the instructions and the permissions.
Open-source harnesses
Also ready to use, and the code is open. You pick the model, run them where you like, and can change them.
SDKs to build your own harness
Building blocks you write a harness with, using your own tools and limits, for a task no standard tool covers.
Ready-made coding harnesses
These are the harnesses most developers already use. They are built for one job, writing software, and they are good at it.
Claude Code
Anthropic's coding agent, built around the Claude models. Runs in the terminal, in your editor, and in the desktop app. Reads a CLAUDE.md file in your repo for your conventions and asks for permission before it does anything risky. Strong at long tasks that touch many files.
Codex CLI
OpenAI's coding agent for the terminal, built around OpenAI's models. The code is open source. Reads instructions from an AGENTS.md file, a format that many other tools now read too.
Gemini CLI
Google's open-source terminal agent, built around the Gemini models. Handy if your team already works in Google Cloud.
Cursor
A code editor with an agent built in. You pick a model from several providers per task. A good fit if you prefer an editor over the terminal and want to see every change as it lands.
GitHub Copilot belongs on the same list: next to completions in your editor, it has an agent mode and an agent that works on an issue by itself and opens a pull request.
Open-source harnesses
Open source matters for two reasons. You are not tied to one model maker, and you can see and change what the harness does. The second one counts as soon as you want to know why an agent did something.
Aider
One of the first coding harnesses for the terminal. Works with almost any model and records every change as a git commit, so you can roll back any step.
OpenHands
Formerly OpenDevin. Runs the agent in an isolated container and comes with a web interface. A fit when you want agents to work on tasks on their own, away from your own machine.
Cline
A VS Code extension that puts every step in front of you: I want to change this file, I want to run this command. You bring your own API key, so you pick the model.
OpenCode
A terminal agent that works with models from many providers, including local models. For anyone who wants the Claude Code or Codex way of working without being tied to one provider.
SDKs to build your own harness
A coding agent is a harness for one kind of work. If you want an agent that prepares quotes, handles tickets, or pulls data from your own systems, you build a harness for that task. For that you use an SDK that handles the groundwork, such as the loop.
Claude Agent SDK
The harness under Claude Code, available as a building block for Python and TypeScript. You get the loop, the context management, and the built-in tools, and you add your own tools and permissions.
OpenAI Agents SDK
A lightweight SDK from OpenAI for Python and TypeScript. Builds agents that hand tasks to each other, with guardrails that check input and output and tracing to see what happened.
LangGraph
From the team behind LangChain. You describe the agent as a graph of steps with a shared state. Strong when you want to decide exactly which step follows which, and when a task must be able to pause until a person signs off.
Pydantic AI
A Python framework from the makers of Pydantic. Puts typed input and output first, so your code knows what an agent returns. Works with models from several providers.
An SDK gives you the loop. The rest is still your work: which tools the agent gets, what it may not do, how you catch errors, and how you see what it does. What that looks like is in building an AI agent.
The three kinds side by side
| Ready-made | Open source | SDK | |
|---|---|---|---|
| Examples | Claude Code, Codex CLI, Gemini CLI, Cursor | Aider, OpenHands, Cline, OpenCode | Claude Agent SDK, OpenAI Agents SDK, LangGraph, Pydantic AI |
| Built for | Writing software, from day one | Writing software, with your own model | Any task you define yourself |
| Model | Usually the maker's own | Your choice, local models too | Your choice, sometimes with a preference |
| What you handle | Instructions and permissions | Instructions, permissions, model, and hosting | Tools, limits, error handling, and monitoring |
| Skip it when | Your task is not code | You have no time to set it up | An existing harness already does the job |
Same model, different harness
Cursor, Cline, and OpenCode can all run a Claude model. They still behave differently: one reads more files before it starts, another asks for permission more often, a third keeps the conversation shorter to stay inside the context window. That difference lives in the harness.
That is why a model comparison tells you little about how a tool performs in your codebase. Try two harnesses on the same real task from your own work. And keep your instructions in a file in the repo, so they come along when you switch.
The model decides what an agent can do. The harness decides how much of that ends up in your codebase.
Whichever you pick, a harness only works well once you set it up for your own codebase, with instructions, tests, and limits. That work is called harness engineering.
Need an agent no standard tool can be?
We build custom harnesses: with your tools, your limits, and access to your own systems. And we set up your team’s coding agents for your codebase.
Conclusion: pick the kind first, then the name
New harnesses appear every month and the existing ones change fast. The three kinds stay. Decide first how much of the harness you want to run yourself, then compare the few options of that kind on a real task.
