Best AI developer tools for coding

[Last updated: May 2025]

The AI developer tools in this list are the state-of-the-art in AI coding and development assistance – compiled from senior engineers who use AI dev tools for coding every day.

These tools span from intelligent code completion (GitHub Copilot) to comprehensive platforms for building, testing, and deploying LLM-powered applications (Vellum.ai). 

They handle the routine and repetitive aspects of coding – freeing developers to focus on creative problem-solving and architectural decisions where human expertise shines.

Code completion and assistant tools

AI coding assistants work as sophisticated pair programmers – understanding context and intent to generate everything from single lines to complete functions. 

1. GitHub Copilot: Microsoft and OpenAI's AI pair programmer that significantly boosts productivity with context-aware code suggestions. Research indicates developers using Copilot report 55% faster coding and 75% higher job satisfaction, with support for most programming languages across multiple IDEs.
   
   
2. Cursor: A fork of VS Code that offers deep AI integration including tab completion, code generation, and multi-file editing capabilities. Cursor builds a knowledge graph of your entire codebase for more context-aware suggestions and offers multiple AI model options for different tasks.
   
   
3. Cline: An AI assistant that uniquely connects your editor and terminal through its Model Context Protocol (MCP). Cline's extensible framework allows teams to create custom MCP servers to integrate with specific tools and workflows, adapting to any development environment.
   
   
4. Amazon CodeWhisperer: AWS's AI coding assistant that excels in cloud application development with specialized knowledge of AWS services. It offers real-time code suggestions, security scanning, and reference tracking to help developers build cloud applications faster and more securely.
   
   
5. TabNine: A code completion tool that uses deep learning to predict and suggest code across numerous languages and IDEs. TabNine offers both cloud-based and local AI models for privacy-conscious teams and adapts to your coding style over time.
   
   
6. Aider: A terminal-based AI coding assistant that enables you to edit code through natural language commands. Aider works with your existing git repositories and can be used with your preferred AI models through your own API keys.

AI-driven IDEs and code editors

Next-generation development environments now incorporate AI capabilities that understand your entire codebase. These intelligent editors provide contextual insights and refactoring suggestions that adapt to your coding style, helping developers navigate complex projects more efficiently.

1. Windsurf IDE: Formerly Codeium and acquired by OpenAI, this Agentic IDE combines agent capabilities with real-time codebase analysis through its Cascade feature. Windsurf offers both standard autocomplete and Supercomplete which analyzes code context before and after the cursor.
   
   
2. Cody by Sourcegraph: An AI assistant that understands your entire codebase to help with writing, editing, and refactoring. Cody integrates with popular IDEs and leverages Sourcegraph's code intelligence to provide more accurate and context-aware suggestions.
   
   
3. Visual Studio IntelliCode: Microsoft's AI-powered code completion tool built directly into Visual Studio that learns from your code patterns. IntelliCode offers context-aware completions and recommendations tailored to your coding style and project needs.
   
   
4. Gemini in Android Studio: Google's AI assistant integrated directly into Android Studio to help with app development. It provides code completion, refactoring suggestions, and debugging assistance specifically optimized for Android development workflows.

LLM orchestration & workflows

As LLM applications grow in complexity, orchestration tools provide critical infrastructure for managing interactions between models, data sources, and processing steps. These platforms offer robust prompt engineering, workflow visualization, and monitoring capabilities essential for production AI systems.

1. Vellum.ai: A comprehensive platform for building, testing, and deploying LLM-powered applications with tools for prompt engineering, workflow orchestration, and model evaluation. Vellum helps you model AI systems as intuitive graphs to improve visibility into their operations, bottlenecks, and failure modes, with support for building provider-agnostic workflows that can call models, run code, and process LLM outputs.
   
   
2. Flowise AI: A low-code platform for creating and deploying customized LLM applications without extensive coding knowledge. Flowise is an "open source low-code tool for developers to build customized LLM orchestration flow and AI agents."
   
   
3. Braintrust: A platform specifically designed for evaluating and improving LLM applications. It helps teams develop and monitor high-quality LLM applications at scale.
   
   
4. AutoChain: A lightweight and extensible framework for building generative AI agents. AutoChain makes it easy to update prompts and visualize outputs for iterating over them, which is crucial for building generative agents. It offers simple memory tracking for conversation history and tools' outputs.
   
   
5. LlamaIndex: A data framework specifically designed for building LLM applications with a focus on context augmentation. LlamaIndex excels in search and retrieval tasks, offering seamless data indexing and search querying for quick retrieval with a detailed and structured metadata schema. It provides support for over 150 data sources and 40+ vector database providers.

Project builders & generators

AI-powered generators can create entire applications or components from simple text prompts, dramatically accelerating prototyping. These tools transform natural language descriptions into working code, enabling teams to quickly test concepts and demonstrate ideas without extensive manual coding.

1. v0: Vercel's AI-powered tool for generating web applications from simple text prompts. v0 is particularly beginner-friendly and great for quickly creating UI components and simple web applications without extensive coding.
   
   
2. Bolt.new: A rapid application development platform that allows you to quickly build prototypes from specifications. Bolt excels at starting new projects and creating demos, making it ideal for teams needing to quickly showcase concepts.
   
   
3. OpenAI Codex: The powerful language model that powers GitHub Copilot, available via API for building custom coding tools. Developers can leverage Codex to create specialized AI assistants tailored to specific development workflows and requirements.
   
   
4. Lovable: A web development platform with an intuitive chat interface that supports both technical and non-technical users. Lovable offers version control, backend support, and features like live rendering and collaborative editing to simplify the development process.
   
   
5. Creatr: A comprehensive development platform with visual tools for creating websites, apps, and digital products. Creatr includes a visual sitemap planner, wireframing tools, and whiteboard functionality to support the entire product lifecycle.

Code review and quality assurance

AI-driven code review tools provide continuous, automated analysis to identify bugs, security vulnerabilities, and maintainability issues before they reach production. These systems augment human reviews to maintain quality standards while reducing the burden on development teams.

1. Greptile: An automated AI code review tool that thoroughly analyzes your codebase to identify bugs, security issues, and maintainability problems. Greptile helps maintain high code quality through continuous automated reviews that catch issues before they reach production.
   
   
2. DeepCode by Snyk: An AI-powered static analysis tool that detects bugs, security vulnerabilities, and performance issues. DeepCode learns from millions of code repositories to provide intelligent suggestions for improving code quality and security.
   
   
3. SonarQube: Advanced code quality platforms that use AI and machine learning for continuous inspection and analysis. These tools help maintain clean, secure code by automatically detecting bugs, vulnerabilities, and code smells across your entire codebase.

AI code debugging and troubleshooting

AI debugging assistants reduce resolution time by providing contextual explanations and identifying root causes of issues. By quickly understanding complex errors and suggesting potential fixes, these tools allow developers to spend more time building features and less time troubleshooting problems.

1. Bito AI: An AI assistant that provides explanations and troubleshooting tips directly within your IDE. Bito helps developers understand complex code, resolve issues quickly, and learn new concepts without leaving their development environment.
   
   
2. Mintlify: An AI-powered documentation generator that automatically creates and maintains high-quality documentation. Mintlify helps improve code readability and speeds up debugging by ensuring that documentation is always accurate and up-to-date.

Code refactoring and optimization

Specialized AI tools can identify technical debt and suggest structural improvements while preserving functionality. These assistants guide developers through complex refactoring processes, optimizing code for performance, readability, and maintainability with intelligence and precision.

1. Qodo: An AI tool that automatically generates meaningful unit tests and suggests code improvements. Qodo helps developers ensure code quality by identifying potential issues and proposing refactoring solutions to improve maintainability.
   
   
2. Refraction: A specialized AI tool designed specifically for refactoring and cleaning existing codebases. Refraction helps developers improve code quality by identifying technical debt and suggesting structural improvements while preserving functionality.

Collaborative development environments

AI-enhanced collaborative platforms support distributed teams with shared workspaces, intelligent coding assistance, and integrated version control. These environments enable seamless remote collaboration with AI features that promote consistency across organizations regardless of physical location.

1. Replit: An online IDE with Ghostwriter, a built-in AI assistant that helps generate code and enhances collaboration. Replit enables teams to code together in real-time with integrated version control, deployment, and AI assistance all in one platform.
   
   
2. CodeSandbox: A cloud development environment that enables real-time code creation, sharing, and collaboration. CodeSandbox streamlines development workflows with instant environment setup and seamless collaboration features.
   
   
3. GitHub Codespaces: A cloud-based development environment that includes AI-powered coding suggestions. GitHub Workspace allows developers to code, test, and collaborate in a consistent environment with integrated terminal access and Copilot assistance.

Terminal & command line tools

AI-powered command line tools bring natural language processing to the terminal, allowing developers to generate scripts, manage repositories, and perform complex tasks without leaving their preferred interface. These tools combine the efficiency of CLI with the intelligence of AI for a streamlined workflow.

1. Claude Code: Anthropic's agentic command line tool that lets developers delegate coding tasks directly from the terminal. Claude Code helps streamline development by allowing natural language requests for code generation, script creation, and other coding tasks.
   
   
2. GitHub CLI with AI: GitHub's command line interface enhanced with AI assistance for repository management and coding tasks. The CLI tool allows developers to leverage Copilot capabilities directly from the terminal for improved workflow efficiency.

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