"AI coding tool" covers several genuinely distinct products. They do not compete for the same role, and choosing the wrong category leads to a costlier mistake than picking the wrong product within one category.
Four categories
| Category | Examples | Designed for |
|---|---|---|
| Autocomplete | GitHub Copilot | Completing the line you are typing |
| IDE assistants | Claude Code, Cursor | A developer working on a task, with assistance |
| Prototyping tools | Lovable, v0, Bolt, Replit Agent | Turning an idea into something visible |
| Production delivery | Coroid | Modifying an existing codebase, under review |
The first two place a model alongside a developer. The third creates something new quickly. Coroid does neither: it takes a defined outcome and delivers a reviewed change to a codebase you already run.
Prototyping and production address different problems
This distinction is crucial to understand, as prototyping tools are highly effective and it is easy to assume the same approach works for production work.
Prototyping prioritises speed to produce something visible. You start from scratch; there is no existing architecture to follow, no test suite to maintain, no conventions to adhere to, and no one relies on the result yet. Constraints would only slow you down — and indeed, these tools impose very few.
Production work is largely defined by constraints. The code already exists and contains established decisions. Other components depend on it. There are tests that must continue to pass, conventions to follow, security and compliance requirements, and a review process that must be completed before anything is shipped.
Coroid is built around these constraints rather than trying to avoid them:
| Prototyping | Coroid | |
|---|---|---|
| Starting point | A blank slate | Your existing repository |
| Destination | A running demo | A pull request change on a branch |
| Verification | Does it look correct? | Your test suite, quality gates, independent QA |
| Governance | Minimal by design | Policies, review rules, audit trail |
| Review | You examine it | Your engineers review a diff under your branch protection settings. |
| Success | The idea is worth turning into reality. | The change is safe to merge. |
They complement each other well
This is not an either/or scenario. The two work well together:
Use prototyping to decide what to build. Validating an idea, exploring a user interface, getting something in front of a stakeholder this week — a prototyping tool outperforms Coroid in these areas, so you should use one.
Then build it within the environment where you will maintain it. Once the idea is confirmed, the work moves into the codebase you actually run, following your conventions, tests and review process. That is precisely what Coroid does.
The prototype answers should we build this. Coroid answers build it properly within the system we already have.
When not to use Coroid
Being clear about this is more helpful than listing features:
- You are validating an idea, not shipping it. Use a prototyping tool. Coroid produces a reviewed change to a real codebase, which represents unnecessary overhead for something you may discard tomorrow.
- You want to see something visual within minutes. Coroid generates pull requests, not live demos.
- You need a pair programmer. If you prefer to stay in your editor and work alongside a model line by line, that is an IDE assistant. Coroid handles entire units of work while you get on with other tasks.
- You do not have a repository yet. Coroid requires a workspace — see Connect your code.
What follows from a production-focused approach
Several elements in Coroid appear like unnecessary overhead until you recognise them as production requirements:
- Work is specified before it is built, so there is something to verify against.
- Verification is carried out by an agent that did not write the code.
- Nothing reaches your default branch without a pull request.
- Policies and gates are enforced within the execution path, rather than being optional suggestions.
- Every execution is recorded — including cost, model, steps and evidence.
None of this is worth paying for when creating a throwaway prototype. All of it is essential for a system that your business relies on.