AI Coding

Comparison

Tool	Best for	Pricing
Amp	Developers who prefer a CLI-first or terminal-native workflow	Pay-as-you-go, no fixed subscription; Smart Mode bills at underlying model API cost with no markup
Cursor	Developers who want an AI-first editor rather than an AI plugin	$20/month (Pro, individual; ~$16/month if billed annually)
Devin Desktop	Existing Windsurf users — migration is automatic, with settings and extensions preserved	$20/month (Pro)
GitHub Copilot	Developers already living in VS Code, JetBrains, or Visual Studio	$10/month (Pro, individual)
Replit Agent	Non-experts or beginners building a first app or prototype from scratch	$20/month billed annually ($25/month month-to-month), Core plan
Tabnine	Regulated industries such as finance, healthcare, government, and defense needing air-gapped deployment	$39/user/month (Code Assistant plan, annual billing)

Reviews

Amp

Sourcegraph's agentic AI coding tool, run from a VS Code extension or a terminal-first CLI, with an unusually generous free tier and pay-as-you-go paid usage instead of a flat subscription.

Cursor

A VS Code-based code editor rebuilt around AI, with deep codebase indexing, multi-file agentic editing, and its own in-house fast-completion models.

Devin Desktop

An AI-native code editor and agent manager, formerly known as Windsurf, now owned and rebranded by Cognition (maker of Devin) as part of a unified local and cloud agent product line.

GitHub Copilot

GitHub's AI coding assistant, integrated directly into major IDEs and GitHub.com, offering inline code completion, chat, and autonomous agent modes.

Replit Agent

A browser-based cloud development platform where an AI agent builds, runs, and deploys full applications from natural-language prompts, without requiring a local dev environment.

Tabnine

An enterprise-focused AI coding assistant emphasizing private and on-premises deployment and strict code-privacy guarantees, with no free or low-cost individual tier as of 2026.

Frequently asked questions

Will AI coding assistants replace developers?

Not based on current capability — they accelerate well-defined, bounded tasks but still require human review for design decisions, security, and correctness on anything non-trivial.

Are AI-generated code suggestions safe to use as-is?

No — treat suggestions as a first draft. Review for correctness, security issues, and license or copyright concerns before merging, especially with autonomous agent modes that touch multiple files.

Do these tools train on my proprietary code?

It varies by tool and plan — check the current policy for the specific tier you're on, since free or individual tiers often have different (or opt-out-based) training policies than paid enterprise tiers.

Do I need to switch my editor to use one of these?

Not necessarily — some tools work as extensions or a CLI inside your existing IDE, while others require adopting a purpose-built AI-native editor.

How much should I expect to pay?

Individual plans in this category range from free with limits to roughly $10–$60 per month; team and enterprise pricing is typically $19–$59 per seat per month or custom-quoted, and usage-based tools can vary based on actual consumption.

How to choose the right AI coding assistant

Decide which layer you actually care about first — inline completion, chat about your code, or an agent that makes multi-file changes — because that matters more than any feature checklist:

• Which layer do you need? Most tools combine autocomplete, code-aware chat, and an agent mode that plans and executes multi-step changes. Be honest about whether you want fast suggestions, a chat that understands your code, or something that opens pull requests on its own.
• Does it fit your editor and workflow? Some plug into the editor you already use; others require switching to a purpose-built AI-first editor or working entirely in the browser. Changing where you work is a bigger cost than it looks.
• How does it price? Flat per-seat subscriptions are predictable; usage- or credit-based models can swing month to month. Pick based on how steady you need the bill to be.
• What’s the code-privacy and training policy? For proprietary or regulated code, confirm how your code is stored and whether it’s used for training against the vendor’s current terms. Policies here change often, and free tiers frequently differ from paid ones.
• Does it know your language and stack well? Real-world strength varies by language and framework. Test it on your actual codebase, not a demo repo, before committing a team to it.

How AI coding assistants differ from coding without them

Without an assistant, every line is yours to type, and getting into an unfamiliar codebase means reading it manually until it makes sense. These tools compress both. They finish the repetitive, well-understood code for you, generate the boilerplate and the tests, explain code you didn’t write, and — in agent mode — take a whole bounded task and make the edits across files themselves. The gain is real on work that’s tedious rather than hard: the parts you know how to do but would rather not type out again.

What they don’t do is understand your system the way you do. They produce plausible code whether or not it’s correct, secure, or a good fit for the rest of the codebase, and the more autonomy you give an agent mode, the more there is to check. The reliable way to use them is as a fast first draft: let them handle the volume, then review for correctness and security yourself. They’re never a substitute for actually understanding what the code does.

Where AI coding needs a human no matter what

Some code you can let an assistant write and move on from; some you can’t. Security-critical code, anything touching authentication, payments, or personal data, and changes that ripple across many files all want line-by-line human review regardless of how good the suggestion looks — plausible and correct are not the same thing. Generated code can also carry licensing or copyright questions worth checking before it ships. And if your team works under strict data-residency or confidentiality rules, verify a tool’s privacy and training policy before it ever sees the codebase, since the default behavior on free or individual tiers is often different from the enterprise tier. Used with that discipline, these tools save real time; used blindly, they just move mistakes into production faster.