DR 35
Access multiple AI models through one unified API, reducing integration complexity and accelerating AI application development.
AI Developer Tools · 16 tools
Compare AI developer tools for code completion, in-editor chat, debugging, test generation, code review, and agents that edit across your whole codebase.
AI developer tools are coding assistants built on large language models that read your code and help you write, fix, and understand it. They range from inline autocomplete in your editor, to chat that answers questions about a file, to agents that plan and edit changes across many files. Most plug into an IDE, the terminal, or your Git workflow.
Autocomplete, quick fixes, and inline chat that keep engineers in flow while writing code.
Ask what a function does or where logic lives when joining a new project or language.
Hand an agent a task and let it draft, edit, and test changes across files.
Catch bugs, suggest refactors, and write tests before code reaches a pull request.
They send your prompt along with nearby code and relevant files to a model trained on large amounts of source code. The model predicts the next lines or a full diff, which the tool inserts or shows for you to accept. Agentic tools go further, calling the compiler, tests, or a repo search, then reading the output and retrying until the change works.