A curated index of the tools developers actually use to build with AI. No models — just the tooling around them: frameworks, vector databases, inference, observability, agents and more.
AI coding tools range from full editors to terminal pair programmers, code reviewers and app builders. Compare what each one does, how it works and what it costs.
The AI-first code editor.
Cursor is a VS Code fork rebuilt around AI: it indexes your whole codebase, edits across multiple files at once, and runs agentic tasks that can read code, run commands and fix their own errors. The most polished AI coding experience available today.
AI pair programming in your terminal.
Aider edits your git-tracked files directly from the CLI, writes clean commits, and works with any model — from Claude and GPT to local Ollama models. Perfect for developers who live in the terminal and want AI without leaving it.
Open-source AI code assistant for VS Code and JetBrains.
Continue brings tab-autocomplete, chat and edit modes into your IDE with total control: choose any provider and any model — including fully local ones via Ollama — and decide exactly which files and context your assistant sees.
AI code reviews for every pull request.
CodeRabbit reviews your pull requests with context-aware feedback, line-by-line suggestions and one-click fixes, then keeps learning from your team's replies. It works on GitHub, GitLab, Bitbucket and Azure DevOps, and also reviews code in your IDE and CLI before you even open a PR.
Turn one sentence into a live, working app.
whacka is a no-code AI app builder that generates, hosts and runs an app from a plain description, with a database, user login, notifications and analytics included. Apps are installable web apps that you can share by link, and you can keep refining them just by describing changes.
LLM frameworks & SDKs →Inference & model routing →Vector databases →LLM observability & evals →Data & agent tooling →
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