Top 15 AI Tools for Developers in 2024

Have you ever found yourself stuck in a coding challenge that seems to take forever, or frustrated by the repetitive tasks that eat up your valuable time?

As developers, we know how overwhelming it can be to juggle multiple tasks, debug endless lines of code, and stay on top of evolving technology.

But what if you could streamline your workflow and speed up the development process?

In 2024, AI tools for developers have emerged as game-changers, helping developers overcome these challenges by automating routine tasks, improving code quality, and boosting overall productivity.

Whether you're coding, debugging, or managing projects, the right AI tool can make a world of difference.

Let's dive into the Top 15 AI Tools for Developers that will help you work smarter, not harder, and take your development game to the next level!

 

What are AI Tools for Developers?

AI tools for developers are software applications and platforms that leverage artificial intelligence to assist with various aspects of the development process.

These tools help developers automate repetitive tasks, improve code quality, enhance productivity, and create smarter, more efficient solutions.

From coding assistants to machine learning frameworks, AI tools for developer productivity​ are designed to boost developer efficiency and streamline the development lifecycle.

 

Best AI Tools for Developers 

 

Here we've discussed some of the best AI tools for developers to make them better at their jobs. Explore below -: 

1. Kroolo - Create Custom Agent Using AI

Kroolo’s Create Custom Agent Using AI feature is the best AI tools for developers​ that allows developers to design and build AI-powered agents tailored to specific tasks or workflows.

Developers can define the behavior, responses, and functionalities of the agent using text or voice prompts, giving them the flexibility to automate repetitive processes, integrate AI into existing systems, and build more intuitive applications.

Whether it’s automating customer service, managing workflows, or enhancing decision-making processes, Kroolo’s AI agents can be customized to suit various needs.

How Developers Can Use It:

• Automate Workflows: Developers can create custom agents to streamline repetitive tasks such as data entry, reporting, or customer inquiries, saving time and improving efficiency.
• Integrate AI with Apps: Custom agents can be integrated with existing applications to enhance functionality, such as providing AI-driven support or interacting with users in real-time.
• Tailor Agent Behaviors: Developers have full control over how the AI agent interacts with users, whether it’s through natural language processing, text-based responses, or automated actions.
• Simplify Complex Tasks: By setting clear instructions and templates, developers can create agents that simplify complex tasks like data analysis, system monitoring, or decision-making.

Features

• Customizable Templates: Pre-built templates that developers can customize for specific use cases.
• Flexible AI Agents: Agents can be designed for text or voice-based tasks, enabling interaction via chat or voice interfaces.
• Easy Integration: Seamlessly integrates with existing tools and platforms, such as CRMs, helpdesk systems, and communication platforms.
• Automated Responses: Program agents to automatically handle routine tasks, reducing manual intervention.
• Scalable: Create multiple agents for various tasks without extensive development overhead, making it suitable for businesses of all sizes.

With Kroolo's Create Custom Agent Using AI, developers can harness the power of artificial intelligence to optimize operations, enhance customer experiences, and improve business outcomes without needing deep AI expertise.

 

2. DeepCode: AI for Bug Detection and Code Review

via DeepCode

DeepCode uses AI to provide real-time code reviews and catch bugs before they can impact your application. It leverages machine learning models to analyze your code, identify security vulnerabilities, and suggest improvements.

DeepCode is especially useful for developers looking for faster, more efficient ways to manage code quality without manually combing through lines of code.

Features

• Real-time code review with instant feedback.
• AI-based bug and security vulnerability detection.
• Supports Java, Python, JavaScript, TypeScript.
• Automated code improvement suggestions.
• Integrates with GitHub and GitLab.

 

3. TensorFlow: Machine Learning Frameworks

via TensorFlow

TensorFlow is an open-source framework widely used for building and deploying machine learning models. It supports deep learning and neural networks and is designed for both research and production.

TensorFlow allows developers to train large models efficiently and deploy them across various platforms, from desktops to mobile devices and IoT systems.

Features

• Extensive library for building and deploying ML models.
• Deep learning and neural network support.
• Cross-platform compatibility (desktops, mobile, IoT).
• Pre-trained models for quick testing.
• Scalable for large applications.

 

4. spaCy: Natural Language Processing (NLP) Tools

via spaCy

spaCy is a fast, robust NLP library built for production use. It offers pre-trained models for multiple languages and is designed for text processing tasks such as tokenization, part-of-speech tagging, and Named Entity Recognition (NER). It’s commonly used for analyzing and understanding text data at scale, and it integrates well with deep learning libraries.

Features

• Fast and efficient text processing.
• Pre-trained models for multiple languages.
• Named Entity Recognition (NER).
• Integration with deep learning frameworks.
• Supports 50+ languages.

 

5. Zapier: Automation Tools

via Zapier 

Zapier is a leading automation tool that allows developers to connect apps and automate workflows without writing a single line of code. It supports thousands of apps, enabling seamless task automation across multiple platforms.

Zapier’s triggers and actions allow for custom automation flows that save time on repetitive tasks, making it ideal for integrating software and tools without the complexity of API development.

Features

• Automates workflows without coding.
• Connects 3,000+ apps.
• Multi-step workflows with conditional logic.
• Real-time task automation and updates.
• Easy integration with popular tools.

 

6. Tabnine: Code Assistants and Generators

via Tabnine

Tabnine is an AI-powered code completion tool that integrates with your development environment to suggest relevant code completions as you type. It works with a variety of programming languages and IDEs, helping developers code faster and with fewer errors. By learning from your coding patterns, Tabnine offers suggestions tailored to your specific project.

Features

• AI-powered, context-aware code completions.
• Supports 20+ languages.
• Customizable suggestions based on coding style.
• Integrates with major IDEs (VSCode, IntelliJ).
• Code optimization recommendations.

 

7. PyTorch: Machine Learning Frameworks

via PyTorch

PyTorch is a machine learning framework known for its dynamic computation graphs, which allow for more flexibility in model development and debugging. It’s widely used by researchers and developers to create powerful deep learning models that are optimized for performance. PyTorch also supports GPU acceleration, making it ideal for training complex models.

Features

• Dynamic computation graphs for flexibility.
• Powerful tensor computations.
• GPU acceleration for fast training.
• Pre-trained models for quick adaptation.
• Active community support.

 

8. Mutable: Code Assistants and Generators

via Mutable

Mutable AI is revolutionizing software development by harnessing the power of AI to accelerate the coding process and eliminate the repetitive tasks that slow developers down.

Designed to eliminate the need for boilerplate code and minimize time spent searching through documentation, Mutable AI enables faster, more efficient code delivery, powered by cutting-edge, proprietary artificial intelligence.

Features

• AI-powered code completions and suggestions.
• In-line documentation and code examples.
• Supports Python and JavaScript.
• Seamlessly integrates with popular IDEs.
• Function signature help for libraries.

 

9. Scikit-learn: Machine Learning Frameworks

via Scikit-learn

Scikit-learn is a Python-based machine learning library designed for data mining and data analysis. This  provides a range of algorithms for classification, regression, clustering, and dimensionality reduction. Scikit-learn is particularly known for its simplicity, making it an ideal starting point for developers new to machine learning.

Features

• Simple API for building ML models.
• Includes algorithms for classification, regression, and clustering.
• Cross-validation tools for performance evaluation.
• Data preprocessing tools.
• Comprehensive documentation for learning.

 

10. SonarQube: AI for Bug Detection and Code Review

via SonarQube

SonarQube is an open-source platform used to continuously inspect the quality of code. It helps in identifying bugs, vulnerabilities, and code smells across different programming languages.

It offers powerful analysis and reporting features to ensure that code quality is maintained throughout the development lifecycle.

Features

• Continuous code inspection and reporting.
• Supports multiple languages (Java, C#, JavaScript, etc.).
• Automated bug detection and security vulnerability identification.
• Integration with popular CI/CD tools.
• Easy-to-understand reports and dashboards.

 

11. IFTTT: Automation Tools

via IFTTT

IFTTT (If This Then That) is a simple automation tool that connects apps and devices, automating repetitive tasks. Developers can set up "applets" that trigger actions based on specified conditions.

For example, automatically back up files or post to social media when certain events happen, streamlining operations and boosting productivity.

Features

• Automates simple workflows between apps.
• Easy-to-use interface with "if this, then that" logic.
• Supports over 600 apps and services.
• Customizable triggers and actions.
• Free to use with additional features in paid plans.

 

12. Google Cloud Natural Language API: Natural Language Processing (NLP) Tools

via Google Cloud’s Natural Language API

Google Cloud’s Natural Language API allows developers to build applications that can understand and process text. This tool can perform tasks such as sentiment analysis, entity recognition, syntax analysis, and content classification, helping developers extract insights from large datasets and optimize their applications accordingly.

Features

• Sentiment analysis and emotion detection.
• Entity recognition (names, dates, etc.).
• Syntax analysis and language detection.
• Scalable for enterprise use.
• Easy integration with Google Cloud services.

 

13. CodeClimate: AI for Bug Detection and Code Review

via CodeClimate

CodeClimate is one of the leading AI tools for software development that analyzes code quality and helps developers detect technical debt, bugs, and security issues.

It integrates with your version control system and provides actionable feedback, encouraging continuous improvement of code quality with minimal manual effort.

Features

• Automated code review and technical debt analysis.
• Security vulnerability identification.
• Supports GitHub, GitLab, and Bitbucket.
• Quality reports with detailed feedback.
• Integration with CI/CD workflows.

 

14. GitHub Copilot: Code Assistants and Generators

via GitHub Copilot

GitHub Copilot, powered by OpenAI’s Codex, is a popular AI tool that assists developers by providing code suggestions, completions, and explanations as they type. It helps with multiple languages like Python, JavaScript, Ruby, and Go, making it an essential tool for coding faster and more accurately.

Features

• AI-powered code suggestions and completions.
• Supports multiple programming languages.
• Works with popular IDEs like Visual Studio Code.
• Provides code explanations and examples.
• Integrates with GitHub repositories for seamless workflow.

 

15. H2O.ai: Machine Learning Frameworks

via H2O.ai

H2O.ai is one of the best AI tools for software developers and an open-source machine learning platform that enables developers to build AI models for predictive analytics.

It provides a range of machine learning algorithms, including deep learning, gradient boosting, and generalized linear models. H2O.ai also includes automated machine learning (AutoML) to simplify the model creation process.

Features

• Open-source, scalable machine learning platform.
• AutoML capabilities for automated model creation.
• Supports deep learning, gradient boosting, and more.
• Integrates with Python, R, and Hadoop.
• Cloud-native and enterprise-ready.