6 AI-Powered Tools Every Developer Should Be Using in 2025

For SaaS founders and developers, leveraging AI-powered tools is no longer optional—it’s essential for staying productive and competitive. In The Ultimate Guide to Productivity & Workflow Optimization for SaaS Founders, we covered fundamental strategies to streamline SaaS workflows. Now, let’s explore the best AI tools for developers in 2025 that can automate coding, enhance security, and optimize your development process.

1. GitHub Copilot – Your AI-Powered Coding Assistant

GitHub Copilot is an AI pair programmer developed by GitHub and powered by OpenAI’s Codex model. It seamlessly integrates with popular code editors like VS Code, JetBrains, and Neovim, offering intelligent code suggestions based on the context of your project.

Key Features & Benefits:

• Context-Aware Code Suggestions: Copilot can complete entire lines or blocks of code based on comments and existing code structure.
• Supports Multiple Languages: It works with Python, JavaScript, TypeScript, Go, Ruby, and many other programming languages.
• Speeds Up Development: Reduces the time spent on repetitive coding tasks by generating boilerplate code instantly.
• Enhances Learning & Productivity: Helps developers explore new programming languages and frameworks by providing real-time coding assistance.
• AI-Powered Code Completion: Understands natural language comments and translates them into working code snippets.

While Copilot is an excellent assistant for experienced developers, it can also be a great learning tool for beginners who want to understand how code is structured. However, it’s important to review and validate AI-generated code to ensure accuracy and security in production environments.

If you’re like us, VS Code is your go-to programming editor. Installing GitHub Copilot is as simple as searching for ‘Copilot’ in the VS Code Marketplace, as shown above.

2. Tabnine – AI-Driven Code Completion

If you’re like me, you probably rely on ChatGPT or DeepSeek when you’re stuck on a coding problem. But what if AI could assist you in real-time, right inside your editor—without having to switch tabs? That’s where Tabnine comes in.

Tabnine is an AI-powered code completion assistant that suggests context-aware snippets, function calls, and even full lines of code as you type. It integrates seamlessly with popular IDEs like VS Code, JetBrains, and Vim, helping developers write code faster and with fewer interruptions.

Key Features & Benefits:

• AI-Powered Code Suggestions – Tabnine predicts what you’re about to type and suggests completions based on context.
• Works with Multiple IDEs – Compatible with VS Code, JetBrains (IntelliJ, PyCharm, WebStorm), Vim, Sublime Text, Eclipse, and more.
• Supports Many Languages – Whether you’re coding in Python, JavaScript, TypeScript, Go, Rust, or Java, Tabnine has you covered.
• Privacy-Focused AI – Unlike cloud-based AI assistants, Tabnine offers an offline mode, allowing you to use AI-powered code completion without sending your code to external servers.
• Complements Other AI Tools – Even if you rely on ChatGPT or DeepSeek for problem-solving, Tabnine can work alongside them, streamlining your workflow.

My Take: Should You Try Tabnine?

I haven’t personally used Tabnine yet, but after diving into its features, I’m curious to see how it compares to my usual AI-assisted workflow. If you’ve tried it, I’d love to hear your thoughts—does it really speed up coding, or do you still find yourself reaching for ChatGPT?

3. OpenAI Codex – AI API for Custom Development

As someone who builds AI-powered applications, OpenAI Codex is one of the most exciting tools I’ve explored. Unlike AI code completion tools like Copilot or Tabnine, Codex is an API, meaning you can integrate it directly into your own apps to generate or interpret code dynamically.

I’ve personally used OpenAI’s APIs in various projects, including AI-powered job post generation and automated text processing tools. Codex takes this further by allowing natural language-to-code conversion, making it possible to build interactive coding assistants, AI-driven debugging tools, and no-code/low-code solutions.

Key Features & Benefits (Short Take)

• Natural Language to Code – Describe what you need in plain English, and Codex will generate functional code.
• Multi-Language Support – Works with Python, JavaScript, TypeScript, Go, Shell scripting, and more.
• API-First Approach – Unlike GitHub Copilot, Codex is an API, meaning you can integrate AI-assisted coding into your own SaaS tools, chatbots, or automation workflows.
• Enhancing Developer Productivity – Automates repetitive coding patterns, generates boilerplate code, and assists in debugging and refactoring.

My Take: Why I Find Codex Exciting

I see Codex as a game-changer for developers looking to integrate AI-powered automation into their workflows. If you’re developing SaaS applications or building developer tools, Codex offers a powerful way to add intelligent code generation, AI-assisted debugging, or even interactive coding support for users.

I’ve primarily used ChatGPT’s API for text-based AI applications, but integrating Codex into a project is something I’m keen to explore further—especially for automating tedious development tasks or even helping non-developers generate simple scripts for their needs.

4. Qodo (formerly Codium) – AI-Powered Code Testing

Writing effective tests is a crucial but often time-consuming part of software development. Qodo streamlines this process by using AI to analyze your code and automatically generate meaningful test cases. It works with various testing frameworks, including Jest for JavaScript/React applications, making it an excellent tool for frontend developers.

How It Helps with React Component Testing

One of the biggest challenges in React development is ensuring components behave correctly under different conditions. Qodo can analyze a React component and suggest relevant test cases automatically.

For example, suppose you have a simple Button component:

const Button = ({ label, onClick, disabled }) => (
  <button onClick={onClick} disabled={disabled}>
    {label}
  </button>
);

Qodo can generate Jest test cases like:

import { render, screen, fireEvent } from "@testing-library/react";
import Button from "./Button";

test("renders the button with the correct label", () => {
  render(<Button label="Click Me" />);
  expect(screen.getByText("Click Me")).toBeInTheDocument();
});

test("calls onClick when clicked", () => {
  const handleClick = jest.fn();
  render(<Button label="Click Me" onClick={handleClick} />);
  fireEvent.click(screen.getByText("Click Me"));
  expect(handleClick).toHaveBeenCalledTimes(1);
});

test("is disabled when the disabled prop is true", () => {
  render(<Button label="Click Me" disabled />);
  expect(screen.getByText("Click Me")).toBeDisabled();
});

Instead of manually writing these test cases (which really saves a lot of brain juice and time for typing your own code), Qodo analyzes the component and suggests them automatically, helping developers save time and improve test coverage.

Why Qodo is Useful

• Speeds Up Testing – Automates test case generation, reducing manual effort.
• Enhances Code Quality – Ensures components behave as expected under different scenarios.
• Supports Various Languages & Frameworks – Works with Python, JavaScript, TypeScript, and more.

If you’re developing a React or Next.js application, Qodo can be a powerful addition to your workflow, ensuring your components are well-tested with minimal effort.

5. Sourcery – AI-Based Code Refactoring

Although I keep a good practice of organizing my code, there are times when tight deadlines, rapid prototyping, or unexpected project pivots cause me to sidetrack from writing clean, maintainable code. In such situations, Sourcery has been a lifesaver.

Sourcery is an AI-powered code refactoring tool that automatically suggests improvements to enhance readability, maintainability, and performance. Instead of manually reviewing and optimizing code, I can rely on Sourcery to detect inefficiencies and provide instant refactoring suggestions.

Since TypeScript is the main language we use while developing PlanStacker products, all the examples below are in TypeScript to better illustrate how Sourcery helps in real-world development.

How It Helps with Code Refactoring

For instance, say I’ve quickly written a function in TypeScript that filters an array of numbers but isn’t as optimized as it should be:

function getEvenNumbers(numbers: number[]): number[] {
  let evenNumbers: number[] = [];
  for (let num of numbers) {
    if (num % 2 === 0) {
      evenNumbers.push(num);
    }
  }
  return evenNumbers;
}

Sourcery might suggest a more concise and readable approach using the .filter() method:

function getEvenNumbers(numbers: number[]): number[] {
  return numbers.filter(num => num % 2 === 0);
}

This small change improves readability while maintaining the same functionality.

Refactoring in a React Component

Sourcery also helps improve React components written in TypeScript. Consider this unoptimized UserProfile component:

type UserProfileProps = { 
  user: { name: string; age: number; email: string }; 
};

const UserProfile = ({ user }: UserProfileProps) => {
  return (
    <div>
      <h2>{user.name}</h2>
      <p>Age: {user.age}</p>
      <p>Email: {user.email}</p>
    </div>
  );
};

Sourcery might suggest using object destructuring to make it cleaner:

type UserProfileProps = { 
  user: { name: string; age: number; email: string }; 
};

const UserProfile = ({ user: { name, age, email } }: UserProfileProps) => (
  <div>
    <h2>{name}</h2>
    <p>Age: {age}</p>
    <p>Email: {email}</p>
  </div>
);

This reduces redundancy and enhances readability.

Why Sourcery is Useful

✅ Speeds Up Code Reviews – Automatically detects redundant patterns and suggests improvements.
✅ Enhances Maintainability – Encourages cleaner, more efficient code structures.
✅ Works in Real-Time – Integrates with VS Code, WebStorm, and JetBrains IDEs to provide live suggestions as you code.
✅ Supports Multiple Languages – Primarily built for Python but expanding support for TypeScript, JavaScript, and more.

Since TypeScript is our primary language, having an AI-powered tool like Sourcery ensures our codebase remains maintainable and scalable as we develop PlanStacker products. If you’re looking for a way to automate refactoring and improve code quality effortlessly, Sourcery is definitely worth trying!

6. Snyk Code – AI-Powered Static Code Analysis (Formerly DeepCode)

When developing SaaS products, it’s crucial to detect vulnerabilities early before launching. Security issues caught during development can prevent costly breaches and ensure your application meets industry best practices.

Previously known as DeepCode, Snyk Code provides AI-powered static code analysis to identify security flaws, performance bottlenecks, and maintainability issues in your codebase.

Since VS Code is our main IDE at PlanStacker, here’s a quick example of how to integrate Snyk Code for security checks in your development workflow.

How to Use Snyk Code in VS Code

1. Install the Snyk Extension
   • Open VS Code and go to the Extensions Marketplace.
   • Search for “Snyk Security” or just “Snyk” and install it.
   • Alternatively, install it directly via this link.
2. Authenticate & Connect Your Project
   • Open the Snyk extension in VS Code.
   • Sign in to Snyk using your account.
   • Connect your project for vulnerability scanning.
3. Run AI-Powered Code Analysis
   • Once connected, Snyk will automatically scan your codebase.
   • It highlights potential security vulnerabilities and provides actionable fixes directly in the IDE.

By integrating Snyk Code in VS Code, you can detect security flaws early and ensure your SaaS applications are secure, optimized, and production-ready from day one.

Below is an example of Cross-Site Scripting (XSS) that could affect a React component through dangerouslySetInnerHTML, which Snyk Code can detect and flag.:

import React from "react";

type Props = {
  userContent: string;
};

const UserProfile: React.FC<Props> = ({ userContent }) => {
  return (
    <div>
      <h2>User Profile</h2>
      <div dangerouslySetInnerHTML={{ __html: userContent }} /> {/* ⚠️ XSS Risk */}
    </div>
  );
};

export default UserProfile;

Why is this a vulnerability?

• dangerouslySetInnerHTML renders raw HTML, making it vulnerable to Cross-Site Scripting (XSS) attacks.
• If userContent contains malicious <script> tags, attackers can execute scripts in the user’s browser.

How Snyk Helps

• Snyk Code would detect and flag the use of dangerouslySetInnerHTML as an XSS risk.
• It would suggest sanitizing user input before rendering.

Safer Alternative: Sanitize User Input

Use a library like DOMPurify to sanitize user input before rendering:

import React from "react";
import DOMPurify from "dompurify";

type Props = {
  userContent: string;
};

const UserProfile: React.FC<Props> = ({ userContent }) => {
  return (
    <div>
      <h2>User Profile</h2>
      <div dangerouslySetInnerHTML={{ __html: DOMPurify.sanitize(userContent) }} /> {/* ✅ Sanitized */}
    </div>
  );
};

export default UserProfile;

This approach removes harmful scripts while preserving safe HTML, preventing attackers from injecting malicious code and keeping your React app secure against XSS vulnerabilities.

Conclusion:

As software development evolves, AI-powered tools have become essential for improving productivity, code quality, and security. The six tools covered—Qodo for automated testing, Sourcery for AI-based refactoring, Snyk for security analysis, and more—help streamline development while ensuring robust and maintainable code.

By integrating these AI tools into your workflow, you can write better code faster, detect vulnerabilities early, and optimize performance with minimal effort. Whether you’re building SaaS applications, React components, or backend services, leveraging AI will give you a competitive edge in 2025 and beyond.