Your developer mentioned Claude Code. A vendor’s proposal mentioned Cursor. Your IT contractor said everyone uses Copilot. You nodded, and you have no idea whether these are the same thing, competing things, or whether it matters to you at all.
It matters a little, and not in the way the marketing suggests. The Claude Code vs Cursor vs Copilot question is, for a business owner, less about which is “best” and more about what the choice tells you about how your software is being built, who is reviewing it, and where your code ends up.
This article describes what each of the main agentic coding tools actually does, who tends to use which, and the handful of questions worth asking whoever builds for you.
What this actually is
All of these tools do a version of the same job. A developer describes a change in plain language, and the tool reads the codebase, writes or edits the code, runs it, and hands back a result for review. That loop is agentic coding, and we explain it from zero in Agentic Coding Explained for Business Owners in 2026. The tools differ in where they live (inside a code editor, in a terminal window, or on a server in the cloud), which AI models they use, how much they do on their own, and how they are paid for.
The analogy is trades. A framer, a finish carpenter, and a cabinet maker all cut wood, and a good one of each owns a different set of saws. You do not need to know the saws. You need to know that the person holding one knows what they are doing, and that the house will be yours when they leave.
One more term: a “pull request” is a proposed change to a codebase, packaged so that another person can read it, comment, and approve it before it goes in. Several of these tools produce pull requests as their output, and that is a good thing, because it means a human review step is built into the shape of the work.
The main tools, and what an owner should know about each
1. Claude Code: an agent that works in the terminal
Claude Code is Anthropic’s agentic coding tool. It runs from the command line (the text-based window developers use to talk to a computer directly) and also plugs into common code editors. You give it a task, and it reads the project, makes a plan, edits files, runs tests and other commands, and reports back. It can use the current Claude models, keep project-specific instructions in a notes file that lives with the code, and connect to outside tools through MCP, the standard we explain in MCP (Model Context Protocol) Explained for Business Owners.
Who uses it: developers who are comfortable in the terminal and want to hand off larger, multi-step pieces of work rather than autocomplete a line at a time. It is paid for through an Anthropic subscription or by usage; check the current pricing page.
What it means for you: a developer using Claude Code is likely working in the “direct an agent, review the result” style. Ask how they review, and whether the project’s instruction notes will be delivered with the code. Levelbrook uses Claude Code heavily in its own practice, with a senior engineer reviewing every change before it ships.
2. Cursor: a code editor with the AI built in
Cursor is a code editor, a modified version of the widely used Visual Studio Code, with AI woven through it. It offers autocomplete as you type, a chat panel that can answer questions about the project, and an agent mode that makes multi-file changes on request. It can be pointed at models from several providers, including OpenAI, Anthropic, and Google.
Who uses it: a very large share of working developers, because it slots into the editor they already use and covers the whole range from small suggestions to agent tasks. It is a subscription with usage tiers.
What it means for you: nothing in particular about the process, because Cursor supports every working style from cautious autocomplete to full agent mode. The useful question is which mode the developer actually uses for your project and, again, how the output is reviewed.
3. GitHub Copilot: the incumbent, now with an agent
GitHub Copilot started as autocomplete inside the editor and was the first tool most developers ever used. It has since grown a chat feature, an agent mode inside the editor, and a cloud “coding agent” that can be assigned a task in GitHub (the service where most of the world’s code is stored) and responds by opening a pull request for a person to review. It offers a choice of underlying models. It is priced per seat, with business and enterprise plans.
Who uses it: teams already standardized on GitHub and Microsoft tools, larger companies with procurement departments, and developers who want the least friction. It is the default choice more often than the deliberate one.
What it means for you: if your vendor is a larger shop, Copilot is probably in the mix. The pull-request workflow is a healthy sign, because it puts review into the process by design. Ask whether the reviews are real or rubber-stamped.
4. OpenAI Codex: an agent in the cloud, plus a terminal version
OpenAI Codex is OpenAI’s agentic coding product. It exists in two forms: a cloud agent that works on a copy of your codebase in an isolated environment and comes back with a proposed change, and a command-line tool that works on the developer’s own machine, similar in shape to Claude Code. It uses OpenAI’s models and is included with certain ChatGPT plans; check the current pricing page.
Who uses it: developers already living in the OpenAI ecosystem, and teams that like the “assign a task, get a pull request later” pattern for well-defined work.
What it means for you: the cloud version means a copy of your code is sent to OpenAI’s servers to be worked on. That is fine for most businesses and worth knowing for some. The data questions are the same ones we lay out in AI Data Privacy for Business, What Happens to Customer Data.
5. The rest: Gemini CLI, Windsurf, Aider, Devin, and the app builders
There are more. Google offers Gemini CLI, a terminal agent similar in shape to Claude Code, built on its Gemini models. Windsurf is another AI editor in the same family as Cursor. Aider is an open-source terminal tool that predates most of the others and is popular with developers who want to bring their own model. Devin, from Cognition, is marketed as a more autonomous agent that takes on whole tasks with less supervision.
Separately, there are tools aimed at non-developers that build an entire small app from a description: Lovable, Bolt, Replit’s agent, and similar. These are worth knowing about because you may be tempted to use one yourself. They are good for a prototype and for seeing what you want. They are not, in our view, the right foundation for a system that handles your customers’ data or money, because the person who cannot read the code cannot judge it either.
6. The choice tells you less than the process does
Here is the honest summary: for a competent developer, the tools are close enough that the choice is mostly preference and habit. They all use the same handful of model families. They all read the codebase, edit files, and run tests. They all make confident mistakes. A senior engineer with any of them will out-build a junior with the “best” one.
So the wrong question is “which tool do you use.” The right questions are about what surrounds the tool: who specifies the work, who reads the output, whether tests exist and run automatically, and whose accounts everything lives in. A vendor who leads with the tool name and cannot answer those is showing you their marketing, not their process.
7. The four questions to ask your developer
First: who reviews what the agent writes, and what are their qualifications. The answer you want is a named senior engineer, not “the AI checks itself.”
Second: does the project have automated tests, and do they run on every change. Agents are only safe when they can check their own work, and so are reviewers.
Third: where does my code live, and where does it go. You want a repository in an account you own (GitHub or similar), and you want to know whether a cloud agent is receiving copies of it and under what data terms.
Fourth: will the instructions the agent was given come with the code. Modern agentic work leaves a written map of the project. It is part of what you paid for and the next developer will need it.
8. What this means for what you own
Because these tools make code cheaper to produce, some vendors have started treating the tooling as the product: “our proprietary AI development platform.” Be careful with that. The output of any of these tools is ordinary code in ordinary languages. It should be handed to you as such, in your repository, runnable by any competent developer with any of the tools above. If a vendor’s work can only be maintained inside their platform, the tool has become a leash. The full list of things to insist on is in How to Hire an AI Consultant Without Getting Burned.
Picture a business like this one
The business below is a composite of the kind of company that writes to us, not a client. The numbers describe the shape of the problem, not a case study.
Picture a business like this one: a specialty food distributor with 60 employees, three warehouses, and an order-entry system built by a contractor in 2019 who has since moved on. The owner wants two things: a customer portal where restaurants can reorder from their last order, and a fix for the pricing screen that nobody has dared touch.
Two vendors quote. The first leads with “we use the latest AI coding tools” and names three of them, then quotes a monthly platform fee and says the code will live on their system. The second says they use Claude Code and Cursor, describes a review process with a named senior engineer, asks for read access to the existing repository before quoting, and comes back with a fixed price and a two-page scope.
A distributor like this should pick the second vendor, and not because of the tools. The build that follows might look like:
- A week reading the 2019 code with an agent’s help, producing a written map of how orders and pricing actually work, which nobody had.
- Tests written around the pricing rules as they exist today, so the fix cannot silently change a customer’s price.
- The pricing fix itself, small once the rules are understood.
- The reorder portal, mostly standard screens the agent builds quickly, reviewed and tested against the real order flow.
- Everything committed to a repository in the distributor’s own GitHub account, with the map and the agent instructions included.
What changes: the portal exists in weeks, the pricing screen is safe to touch again, and the next developer, whoever they are and whatever tool they carry, can start from the map.
What it costs to run
The tools themselves are the developer’s cost, not yours. For reference, the individual subscriptions for Claude Code, Cursor, Copilot, and Codex each run from around twenty dollars a month at the low end to a few hundred a month for heavy use. Prices move often, so check the current pages rather than trusting any article.
What you pay for is the running of the resulting software, which is unchanged by which tool built it: a small server or hosting plan (somewhere between free and $50 a month for most small business tools), a database, and whatever services the software talks to. And the ongoing cost of a human paying attention to it a few hours a month.
The mistakes we see most
Choosing a vendor by the tool they name. The tools are close. The process is not. Ask about review, tests, and ownership.
Using an app builder for a real system. Building a prototype in Lovable or Bolt is a fine way to show a developer what you want. Running your billing on it is not.
Accepting “the AI tested it.” Automated tests written and run in the project are evidence. A model reporting that it checked its own work is not.
Letting the vendor’s platform hold the code. If your software can only be maintained through a vendor’s proprietary system, you have rented it, not bought it.
When to bring in help
You can try these tools yourself, and we would encourage it, because an hour with Claude Code or Cursor teaches you more about what is now possible than any article. For a spreadsheet macro, a one-off data cleanup, or a prototype to show a developer, that may be all you need.
For anything your business will depend on, the tool is not the hard part. The hard part is knowing what to build, catching what the agent got wrong, and making sure you own the result. That is a senior engineer’s job, whichever saw they hold.
Levelbrook builds web apps, automations, and AI systems for businesses using these tools every day, with a senior engineer specifying and reviewing every piece, delivered at a fixed price from a written scope into accounts you own. If you have a system nobody dares to touch, the form below is how a conversation starts.