Platforms

Where you actually write code with a model. Options span a spectrum from fully-hosted tools that run in your browser to command-line agents that work directly on your own machine. The trade-offs are consistent across the spectrum: the more hosted the tool, the less setup you have to do and the less you can customize; the more local the tool, the more control and visibility you have, at the cost of complexity and your own hardware. For a first project, start further up the hosted end — most frustration at the start is setup, not code.

In-browser environments

Tools like Lovable, Bolt, v0, and Replit let you describe what you want and watch the model assemble a working app in a browser tab — no install, no setup, no git to learn on day one. They’re the fastest path from idea to running code, and the right place to prototype. The trade-off is that you’re confined to what the platform supports: particular frameworks, particular deploy targets, particular kinds of customization. When a project outgrows the sandbox, you export the code and move somewhere else.

Native desktop apps from model makers

Anthropic’s Claude and OpenAI’s ChatGPT both ship native Mac and Windows apps. These are chat-first tools — the model can read files you drop in, run small bits of code in a sandbox, and answer questions — but they don’t manage a project the way an agent or IDE does. Good for explanations, one-off snippets, debugging a small file, and learning. Not where you build a non-trivial project over weeks.

AI-integrated IDEs

An IDE (integrated development environment) is the editor you’d use even without AI — VS Code, JetBrains, Xcode. AI-integrated IDEs bolt a model into that editor. Cursor and Windsurf are VS Code forks built around an agent; VS Code + GitHub Copilot (or Claude’s extension) adds similar capabilities to the mainline editor; JetBrains has its own AI integration. This is where most day-to-day coding with AI happens — you see your project, you see the model’s proposed changes, and you decide what to accept.

Command-line agents

At the other end of the spectrum, command-line agents like Claude Code, Codex CLI, and Aider run in a terminal, read and write files in your project directly, and execute shell commands. They’re less beginner-friendly — you need to be comfortable in a terminal — but they’re also the most powerful, because the agent has the same access to your project that you do. The right tool when you’re orchestrating multi-step work across many files.

Typical pricing

Most platforms cluster into a few tiers. Free usually means limited usage, slower models, or a rate cap — enough to try the tool, not to rely on it. ~$20/month pro subscriptions are the default for serious single-user work: Claude Pro, ChatGPT Plus, Cursor Pro, GitHub Copilot, Replit Core. Usage-based API pricing (Anthropic, OpenAI, Google) charges per token — cheap for occasional scripted calls, potentially expensive for heavy agent use over time. Team and enterprise plans stack higher still, typically $50–100+ per seat with admin controls. Before committing to a platform, confirm which tier your actual workflow needs — “the monthly tier is enough for most people” is a common refrain that breaks down fast once you’re building something serious.