Best AI tools for developers to use in your next coding project

Looking to build your next coding project? Learn about the best AI developer tools that you can use to code faster and better.

When was the last time you went to a search engine to look for commonly faced problems? 2022? 2023? This will make you realize how fast we are adopting AI for our daily tasks. As developers, we no longer need to leave our IDEs; AI tools can help us in research, finding bugs, and also auto-completing.

This has people on the internet divided in their opinions about how AI is the “copilot” versus how AI is the “job-snatcher.” New technology has always led to such controversies and in turn, it has led to the creation of new jobs instead of making people jobless.

As a developer, you need to know AI tools that you can use and build with. In this article, we will cover some of the best AI tools for software developers, along with their hero features that can help you become a 10x developer.

On Pieces website, we already published one original article so consider this as the continuation of this long prolonged list:)

Before you drive your conclusions, let’s consider this:

What features should you look for in an AI tool?

There has been an increase in the number of AI tools launching, and every product has its own pros and cons, but which one should you choose?

Ask yourself three questions to narrow down a few options to choose from:

• What do I need an AI tool for? Is it just for code generation? Is it for code generation + documentation? Is it for help with front-end development? Is it for software testing? Find your reason.
• What do I want my AI tool to help me with? Is it for memory retention, contextual suggestion, or research?
• What are the must-have features? Is it good developer experience? Is it integration with IDEs? Is it more accurate? Or Is it support for multiple LLMs?

Once you’ve answered these questions and done thorough research on the best free AI tools for developers, finding your perfect AI tool will become easier.

Top AI tools that you need to try out

Having played around with multiple AI tools for coding, I chose the top ones based on:

• Personal experience: Any tool that I use should be contextually aware, able to auto-complete, have the ability to browse the internet and help with research, have an assistant with a chat-like interface, can be integrated with IDEs, and an add-on feature if it can replicate my coding style.
• Community feedback: How developers across different domains feel about it. Checking reviews from users on G2, Reddit, and other developer forums.

Here are the top ten tools that I would suggest you use for coding:

Pieces for Developers

Assistants should do more than just generate code.

They should be able to correct you on the go, assist in research, remember those annoying warnings that keep showing up, and eliminate those version errors. Pieces for Developers can do all of this, making it the best AI tool for learning and development.

Here’s one hero feature within Pieces, that can shadow your day-to-day progress, capture relevant workflow, and use that as context to give you a better and more accurate response.

Other key features:

• Can run locally, giving more security and privacy.
• Runs on browsers as well as can be integrated with any IDE of choice.
• The Pieces Copilot has a chat-like interface that makes it easier to prompt and get additional help.
• Allows users to choose between models, which leads to more flexibility.
• Has the ability to capture snippets, save and share them, and also use that for context for more accurate results.
• Is free and easy to use.

v0 by Vercel

The contributions of Vercel to the development ecosystem now go beyond easy hosting and Next.js and expand to the ability to create modern frontend and full-stack applications with prompt engineering. It goes without saying that v0 is the best AI tool for front-end developers.

For someone who is in the shadcn + Next.js + Vercel ecosystem, this tool is a game changer and will help you ship faster than any AI tool, since it is already very contextually aware and specifically built for this ecosystem.

One hero feature in v0 is the built-in ability to deploy the projects that one is building with the help of prompting.

Other key features:

• It has pre-built starter templates that make it super easy for anyone to get started.
• It has a live preview, so now you can see what the code is rendering and also click on particular components to edit the code if needed.
• With every file that is being generated, it has an IDE-like interface, which makes it easier for developers to understand the changes.

GitHub Copilot

GitHub Copilot is one of the oldest AI tools launched for developers. It is best known for its auto-completion features and can help you write code in any language. According to Sourcegraph and other developer forums, it is considered one of the best tools for React developers and app development.

Other than being pretty flexible, one feature that stands out to me for Copilot is the ability to understand local languages.

We have often come across developers whose first language is not English, and it becomes harder for them to get started coding. Copilot removes this barrier.

One can now prompt in their mother tongue, and GitHub Copilot can comprehend that and answer accordingly.

Here’s a demo of Copilot understanding Hindi:

Other key features of GitHub Copilot are:

• Ability to use Copilot in IDE of choice, terminal, browser, and mobile (as a chat interface).
• Creating and managing collections of documentation, called knowledge bases, to use as a context for chatting with Copilot
• AI-generated summaries of the changes that were made in a pull request, which files they impact, and what a reviewer should focus on when they conduct their review.

Windsurf Editor

If you have been keeping an eye on the AI space, you must have heard about the word “Agentic AI”, which basically means that AI will be able to make decisions and take actions on its own.

The Windsurf editor is said to be the first agentic IDE.

The standout feature of Windsurf is their Flows engine. It allows smooth, real-time teamwork between the developer and AI, working together perfectly.

This means the AI always knows what you’re working on and quickly adjusts as you switch tasks, helping you without needing updates or breaking your concentration.

Other key features of the Windsurf editor:

• Super-fast auto-complete with in-house models.
• Chat-like interface for the coding assistant that can help in research, along with the ability to integrate into popular IDEs.

Ability to direct AI to generate or edit code directly in the editor using Ctrl + I or ⌘ + I.

Aider

For those of you who like to use the terminal, Aider is the one for you. It is an AI program that runs in your terminal.

It can help you code with LLMs in your local git repository. It works best with Claude 3.5 Sonnet, DeepSeek V3, o1 & GPT-4o and can connect to almost any LLM.

What I like the most about Aider is that it is open-source and very simple to use. All you need to do is type command `aider <filename>` and it will run for you.

Here’s a video from their official documentation on how it works.

Other key features of Aider are:

• Aider has Git integration, so it can automatically commit code using a sensible commit message.
• You can code with the use of voice.
• Aider can edit multiple files at once for complex requests. You can edit files in your editor while chatting with Aider, and it will always use the latest version.

By the way, stay in the trends and watch out for these essential open source large language models in 2025.

Gemini Code Assist

Gemini Code Assist is the AI coding assistant developed by the Google team. It is contextually aware and can help you auto-complete and generate code blocks with their chat-like interface.

Code Assist can be integrated with almost all popularly used IDEs and currently supports 20+ languages.

One feature that stands out the most for me is the contextual smart actions and smart commands. These quick shortcuts help in automating tasks such as fixing errors, generation, and code explanation.

These smart actions and commands are available right in the IDE, thus it reduces the context switching of copying/pasting.

Other key features of Gemini Code Assist are:

• You can customize Code Assist with your organization’s private codebases to get help with more customized responses.
• It is contextually aware, and gets the context from your local codebase and current development session. Powered by Google’s Gemini 1.5 Pro model, it can help with large-scale changes, including adding new features, updating cross-file dependencies, and more.
• It can help you create APIs that are consistent with enterprise standardization.

GitLab Duo

GitLab Duo as an assistant can help you throughout all the stages of the software development lifecycle — from coding to deploying. It can help in writing tests, explaining code, and chat directly in your IDE or web interface.

What is unique about GitLab Duo is its focus on security. It can understand and remediate vulnerabilities efficiently. You get detailed explanations and auto-generated merge requests to mitigate security risks.

Other key features of GitLab Duo are:

• It can help with AI-assisted root cause analysis for CI/CD job failures.
• It lets you measure the ROI. Gives you a detailed analysis on how it helped in the entire software development lifecycle and the improvement you saw.

CodeRabbit

We have talked about AI tools that can help in writing code, and even pushing them. The next step is where the code needs to be reviewed, and this is where CodeRabbit can help.

It is an AI-powered tool that can analyze pull requests, and provide feedback on issues like logic bugs, readability concerns, and other insights that might have been missed during manual reviews.

What I liked the most about CodeRabbit is that you can chat with it within code review comments. If you have questions, want to generate code, or want to open an issue, you can do it all in real-time.

Other key features of CodeRabbit are:

• It can auto generate release notes, daily standup reports, and sprint reviews.
• It can generate pull request summaries of your code changes.
• It is contextually aware of your codebase, so it is capable of offering line-by-line reviews & 1-click fixes.

Qodo

Qodo is one such tool that can help in writing code, writing test cases and helping in writing thorough descriptions in PRs.

It can currently be installed on VS Code and JetBrains. You can use its chat feature to clean code and improve it by detecting bugs and vulnerabilities.

What stands out for me with Qodo is how well it can generate unit tests with edge case coverage and the availability of quick commands like `/quick-test` (for test generation), `/ask` (for asking queries), and `/explain` (for explaining code in plain English).

Other key features of Qodo are:

• You can customize it to align the output with your team’s coding standards.
• It has great documentation capabilities. Along with writing PR summaries, it can also document code changes.
• It can help in PR reviews by highlighting potential problems to focus on, and help in code quality by suggesting code changes ranked with severity.

Keeping up with the AI tools

While talking about the different AI tools, we saw how each tool has its own unique capabilities.

As these tools keep improving and newer ones keep coming, we as developers should be able to make the best use of them.

After using various AI tools for coding, my top priorities for selecting the right AI tool are: security, contextual awareness, speed and accuracy, and how well it aids in research.

Depending on your use case, you should choose the one that is best suited for your needs.