10 Best AI Coding Assistant Tools in 2025 – Guide for Developers

AI tools for coding are becoming more and more popular, revolutionizing the software development industry. They can generate code and automate tedious tasks, providing intelligent code snippets and suggestions that reduce development time. By integrating these tools into your workflow, you can focus on creative problem-solving, resulting in the faster delivery of customer projects. So, if you’re looking to improve your development process, enhance code quality, and stay up-to-date with the latest technological advancements, you’ve come to the right place!

My name is Karol, and I’ve been a mobile developer since 2011 (you can find out more about me in the bio below). I use AI code generation every day, mostly through GitHub Copilot and Gemini. I finished the AI Devs 2 course in November 2023, which covered generative AI, programming AI assistants, and even more exciting topics related to AI coding. Since then, I’ve also completed the AI Devs 3, focusing on more autonomous solutions like AI agents.

Recently I finished the 10xDevs program. It was a four-week online course for experienced developers, focused on using generative AI tools to boost productivity and code quality across the software development lifecycle. Moreover, I’m currently participating in the Developer Jutra program. It’s an advanced educational program for Polish developers focused on building interdisciplinary skills. Not only writing code but also combining architecture, backend, frontend, databases, and DevOps – to stay relevant in an AI-driven future

I wanted to share some popular AI tools with you that I think you’ll find really valuable. We’ll go over why they’re so great to use in your workflow, the key features they offer, and some important risks to keep in mind. Plus, I’ll give you some insights into how they integrate with popular IDEs for different programming languages.

What is an AI coding assistant?

An AI coding assistant is a sophisticated software tool that leverages artificial intelligence to support developers throughout the coding process. Its primary purpose is to generate code, help in writing and debugging code, assist in code reviews, and provide real-time code suggestions, corrections, auto-completions, and optimizations. These AI programming assistants also detect bugs and security vulnerabilities to improve code quality.

It works much like a virtual pair programmer. What’s more, it never tires and continuously learns from vast repositories of code. Thanks to the latter, it improves its quality over time.

AI coding assistants target a broad spectrum of users. Novice programmers can benefit from guidance and learning opportunities. Seasoned veterans, on the other hand, can speed up their work by ensuring their source code follows the best practices and latest standards. These tools can adapt to various coding styles and project requirements.

The rise of AI coding agents

As the field evolves, more advanced forms are emerging, such as AI coding agents. Unlike assistants that primarily offer suggestions or completions, agents are designed to autonomously perform more complex, multi-step tasks, often interacting with various tools and environments to achieve a defined programming goal. They represent the next frontier in AI coding tools, moving beyond simple AI code completion to more proactive problem-solving.

Read also: 10 Ways AI Can Speed Up your Mobile App Development | Guide for Developers

Is it possible to develop digital products with AI tools?

The development of digital products with AI coding tools is not only possible, but very common in the modern tech landscape. AI programming assistants can significantly enhance various stages of the software development lifecycle, from conceptual design to deployment. Alongside automating repetitive tasks, these tools excel at providing intelligent code suggestions and even acting as an AI code generator.

Through this assistance, AI code completion features contribute immensely to the development process, but it’s important to note that the creative and strategic decision-making aspects still rely on human developers. AI coding is not yet at a point where it can independently manage the nuanced requirements of crafting a complete digital product.

Therefore, these AI coding tools serve as powerful adjuncts to human expertise, functioning as a virtual AI pair programming partner. They streamline the development process, enabling developers to focus on the more intricate and innovative aspects of product creation.

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Why you should consider using an AI coding assistant

Software development is growing more complex and demanding. Incorporating AI coding assistants into your workflow can be a game-changer. These AI programming assistants are designed to significantly boost productivity and streamline development. Here are the most compelling reasons why you should consider using AI coding tools to enhance your programming endeavors:

• Time-to-market reduction: By accelerating the coding process through efficient AI code generation, AI coding assistants can help bring products to market faster, providing a competitive edge.
• Cost savings: Automation can reduce the need for extensive manual labor, leading to significant cost savings in the long run.
• Accessibility for non-experts: AI coding assistants can make app development more accessible to those with less experience. They effectively bridge the gap between novice and expert developers by offering guidance and AI code completion.
• Scalability: AI tools can easily scale with the project as they learn from the growing codebase. This supports projects as they increase in size and complexity.
• Continuous improvement: Because they’re trained with a lot of data, the suggestions and insights offered by AI code tools become more sophisticated and valuable over time.
• Stress reduction: AI coding assistants can reduce the mental load on developers by handling many of the mundane aspects of coding. This frees the latter to tackle coding challenges with a clearer mind.
• Increased efficiency: AI tools can automate routine or repetitive coding tasks, such as boilerplate code, enabling developers to focus on more complex and creative aspects of their projects. Their AI code completion and AI code generation capabilities are key here.
• Enhanced code quality: With real-time suggestions and the ability to flag potential errors, AI-powered code assistants help maintain high coding standards and reduce the likelihood of bugs.
• Learning and growth: Developers can learn from AI-driven recommendations. They often reference best practices and newer, more efficient ways of coding.
• Faster debugging: AI coding assistants can detect issues and offer solutions, speeding up the debugging process significantly.
• Code refactoring: When it comes to improving structure and readability, AI tools can refactor code without changing the external behavior of the codebase.
• Personalized assistance: By adapting to individual coding styles and preferences, AI coding assistants provide individually tailored support that improves over time, making them a true AI pair programming partner.
• Integration with development environments: Many AI coding assistants can be integrated into popular IDEs, streamlining the software development process and workflows. For instance, the best AI code editor experiences often come from well-integrated AI plugins.
• Image processing: Some AI coding assistants support images in prompts, allowing developers to get answers as quickly as possible.

By using AI coding assistants, developers can improve their current practices. They can also future-proof their skills and projects. These are some of the biggest reasons why the industry as a whole is quickly shifting towards smarter, automated code generation tools.

The 10 best AI coding assistant tools

In crafting this comprehensive guide to the best AI coding assistant tools available in 2025, we have identified and evaluated ten leading options: GitHub Copilot, Qodo, Jules, Cursor, Windsurf, Aider, Bolt.new, Tabnine, JetBrains AI Assistant, and Gemini in Android Studio. These AI programming assistants represent a diverse range of capabilities, from powerful AI code generation to intelligent AI code completion and AI pair programming features. This list has been curated through a combination of extensive industry research and our team’s direct, hands-on experience with several of these cutting-edge AI coding tools.

To provide you with the most reliable and useful insights into the best AI coding tools of 2025, our evaluation process combined rigorous industry research with genuine, hands-on experience. This dual approach ensures both comprehensive coverage and practical understanding of each tool’s real-world benefits and limitations.

As mobile developers at Droids On Roids, we are committed to leveraging the latest advancements in AI to enhance our workflow and deliver high-quality digital products faster. Consequently, our team actively integrates several AI programming assistants into our daily coding practices. Specifically, our developers widely use and rely on GitHub Copilot, JetBrains AI Assistant, and Cursor for various tasks ranging from AI code generation and AI code completion to sophisticated AI pair programming. Additionally, as Karol, the author of this article, I personally utilize these tools, alongside Gemini in Android Studio, which is invaluable for native Android development.

How we evaluated these AI coding tools

This direct, continuous usage gives us firsthand insights into how these particular AI coding assistants perform under real project conditions, how they integrate with popular IDEs, and their actual impact on productivity and code quality. We’ve experienced their strengths in automating boilerplate code, debugging, and even refactoring, alongside understanding their learning curve and potential challenges.

For the tools not regularly used by our team, our evaluation involved extensive research. This included analyzing official documentation, reviewing expert opinions, assessing user feedback from developer communities, and examining case studies to understand their core features, pricing models, supported languages, and unique selling points. While we couldn’t run specific benchmark tests on every tool for this article, our aim is to provide a well-rounded and informed perspective on the current landscape of AI coding solutions, helping you make an informed decision for your own development journey.

To make it easier for you to pick the right AI coding tool from all the great options out there, we’ve put together a quick comparison table. This handy overview will show you the important details like each AI programming assistant’s pricing model, how easy it is to get started (its entry threshold), and what it’s best for – whether that’s lightning-fast AI code generation, smart AI code completion, or helping you with AI pair programming. Our goal with this summary is to help you quickly find the perfect fit for your specific development needs and preferences.

Quick comparison table

It’s important to note that the popularity of AI-powered code assistant tools can fluctuate rapidly. As new advancements are made in AI code generation and AI code completion, developers’ preferences can change. Moreover, each AI code tool has its unique strengths and may be more or less suited to specific tasks, programming languages, or even AI pair programming styles. When choosing an AI coding assistant, always consider the tool’s compatibility with your preferred programming languages and IDEs, as well as its ease of integration into your existing workflows.

GitHub Copilot

GitHub Copilot is a leading AI coding assistant born from a collaboration between GitHub, OpenAI, and Microsoft. It uses advanced AI to offer coding assistance, understanding the context in which you are writing code. Trained on a vast array of code from open-source projects on GitHub, Copilot enhances the development process by providing smart AI code completion and explanations directly within the IDE. Our team at Droids On Roids extensively uses GitHub Copilot, valuing its efficiency and seamless integration into our workflow.

According to research from GitHub, developers using Copilot experience a significant boost in job satisfaction – reportedly 75% higher. They also report up to 55% faster coding. While this increases their productivity, it does not compromise on code quality. It is compatible with major editors like Visual Studio Code, JetBrains IDEs, and Neovim. Moreover, it is uniquely integrated into GitHub’s ecosystem. Copilot is rapidly becoming the go-to AI code completion tool for millions of users and businesses.

While it supports most of the programming languages present in public repositories, the quality of its suggestions varies. Languages like JavaScript receive more robust support due to their prevalence in training data. Copilot is accessible via multiple IDE extensions, GitHub CLI, and is increasingly incorporated directly into GitHub’s web and mobile platforms.

A significant recent advancement for GitHub Copilot is the introduction of its agent mode, transforming it into a powerful AI coding agent. This autonomous capability allows Copilot to handle complex, multi-step coding tasks with a single prompt. It can independently analyze your entire project, determine which files to modify, suggest both code changes and terminal commands, and even iterate to fix errors or refactor code until the task is complete. Basically, the agent writes code for you. This means you can assign tasks like creating apps from scratch, improving test coverage, fixing defects, or migrating legacy code, and Copilot will work in the background, pushing commits to a draft pull request that still requires human approval. This moves beyond simple code completion, offering a true AI pair programming experience where the AI takes on more proactive development roles.

Key features:

• High popularity and a large community.
• Deep integration with many IDEs (Visual Studio Code, IntelliJ products, Neovim, Xcode, Eclipse).
• Intelligent AI code completion and easy navigation through multiple code snippets.
• Support for multiple programming languages.
• Code referencing, finding public code that matches AI code generator suggestions.
• Ability to block code suggestions matching public code snippets, important for avoiding accidental open-source license violations.
• New Agent Mode: Autonomous AI coding agent capabilities for multi-step tasks, including refactoring, test generation, bug fixing, and app modernization.

Pricing:

• Free – $0. Limited completions and agent chat interactions.
• Pro – $10 per month or $100 per year. Unlimited completions and agent chat interactions. Free of charge for verified students, teachers and maintainers of popular open-source projects.
• Pro+ – $39 per month or $390 per year. Access to all models and coding agent.
• Business – $19 per user per user per month. Unlimited completions and agent chat interactions.
• Enterprise – $39 per user per user per month. Access to all models and coding agent.
• The Copilot coding agent features, when activated, will consume premium requests.

It is a discretion of GitHub to decide whether an open-source project qualifies for a free Pro plan or not. As a personal example, I was eligible due to my android-gif-drawable library with 9.6k stars on GitHub.

Qodo (formerly Codium)

Qodo (formerly known as Codium) is a quality-first AI coding platform designed to revolutionize how developers write, test, and review code. Unlike many general-purpose AI code generation tools, Qodo stands out with its strong emphasis on code integrity, making it a powerful AI coding assistant for ensuring software quality at every stage of development. It integrates AI across development workflows, leveraging a multi-agent approach to provide precise and context-aware assistance.

Beyond test generation, Qodo enhances productivity through:

• Qodo Gen: An IDE plugin providing intelligent AI code completion, AI code generation, an AI-powered chat feature, and tools for test generation, planning, and coverage.
• Qodo Merge: A Git agent that streamlines pull requests by automating code reviews, generating thorough PR descriptions, flagging potential issues, and improving code quality.

Qodo’s advanced AI programming assistants also facilitate automated documentation generation, code analysis, and bug detection with fixing suggestions, contributing to a more efficient and reliable development pipeline.

Key features:

• Specialized in comprehensive unit and component test generation with code behavior analysis.
• Advanced AI coding agent capabilities for issue detection, code review, and test coverage.
• Context-aware AI code generation and AI code completion directly within the IDE.
• AI-powered chat for free-form questions and code improvements.
• Automated documentation generation.

Pricing:

• Developer – Free of charge. Offers repository context chat, multiple model options, code review, test generation, documentation, and community support.
• Teams – $38 per user per month. PR automation, enhanced privacy, and standard support.
• Enterprise – $45 per user per month. Multi-repo awareness, self-hosting, SSO, and priority support.

Qodo prioritizes data privacy and security, offering various deployment options, including SaaS and on-premise solutions, to ensure intellectual property protection. Its focus on code integrity and quality makes it a compelling AI code editor and assistant for individual developers and teams alike.

Jules

Google Jules is Google’s innovative, AI-powered coding agent designed to tackle complex coding tasks autonomously. Unlike traditional AI coding assistants or AI code completion tools that offer real-time suggestions, Jules operates asynchronously, allowing developers to assign tasks and focus on other work while the agent operates in the background. It integrates directly with your existing GitHub repositories, cloning the codebase into a secure Google Cloud virtual machine (VM) to understand the full context of your project.

Powered by Google’s Gemini 2.5 Pro large language model, Jules can perform a wide range of functions, effectively acting as an AI pair programming partner for more demanding tasks. It can autonomously write code for new features, fix bugs, update dependencies, refactor source code, and even generate audio changelogs. Upon completion, Jules presents a detailed plan, its reasoning, and a diff of the changes made, pushing these directly to a draft pull request for human review. This makes it a powerful AI code generator and a crucial AI tool for enhancing the entire software development process. Jules is private by default, ensuring your data remains isolated and your private code generated by it is not used for training. It’s now in public beta, accessible globally where Gemini is available.

Key features:

• Autonomous, AI coding agent capabilities for multi-step coding tasks.
• Direct integration with GitHub repositories.
• Secure operation within a Google Cloud VM.
• Tasks include writing code for new features, fixing bugs, refactoring, and updating dependencies.
• Generates detailed plans, reasoning, and pull requests.
• Powered by Gemini 2.5 Pro.
• Asynchronous workflow for enhanced developer productivity.
• Prioritizes privacy; does not train on private source code.

Pricing:

• Free – Currently available in public beta at no cost. (Usage may be subject to Gemini model pricing in the future.)

Windsurf (formerly Codeium)

Windsurf is a groundbreaking AI-native IDE (Integrated Development Environment) developed by the Codeium team. Conceived as the “world’s first agentic IDE,” it aims to keep developers in a deep flow state by proactively anticipating needs and resolving issues. Unlike traditional code editors that primarily offer AI code completion, Windsurf combines both copilot-style assistance with powerful AI coding agent capabilities, making it a comprehensive AI code tool for the entire coding process.

At the heart of Windsurf is its “Cascade” feature, an advanced AI coding agent that can autonomously write code, fix bugs, refactor source code, and even perform multi-step coding tasks. Powered by models like Anthropic’s Claude 3.5 Sonnet, Cascade deeply understands your codebase and maintains full context throughout a development session, allowing for efficient code generation and accurate interventions. Windsurf also includes “Windsurf Tab” for smarter code suggestions based on command history, and supports integrated workflows for building, iterating, and shipping applications, streamlining the software development process. Built on a fork of Visual Studio Code, it offers a familiar interface with augmented artificial intelligence capabilities.

Key features:

• AI-native IDE integrating copilot and agent systems.
• “Cascade” AI coding agent for autonomous multi-step coding tasks, including code generation, refactoring, and bug fixing.
• Powered by advanced large language models.
• Intelligent code completion and accurate code suggestions.
• Supports building, iterating, and shipping within a single workflow.
• Features like “Windsurf Tab” for context-aware assistance.
• Familiar interface, forked from Visual Studio Code.
• Handles boilerplate code generation and offers code explanation.

Pricing:

• Free – free of charge: 100 GPT prompts per month
• Pro – $15 per month: 2000 GPT prompts per month, options to buy additional credits
• Teams – $30 per user per month: reviews, analytics, options to buy additional credits and SSO
• Enterprise – $60 per user per month: 4000 GPT prompts per month, SSO, priority support

Bolt.new

Bolt.new is an innovative, browser-based AI coding tool that redefines full-stack web development. Developed by the StackBlitz team, this AI-powered web development agent allows users to prompt, run, edit, and deploy complete applications directly from their web browser, eliminating the need for complex local setup. It stands out by giving large language models (LLMs) like Anthropic’s Claude 3.5 Sonnet direct control over the entire development environment, including the filesystem, Node.js server, and terminal.

At its core, Bolt.new acts as a powerful AI code generator, transforming natural language descriptions into functional frontend, backend, and even database structures in seconds. It integrates cutting-edge artificial intelligence models with an in-browser development environment powered by StackBlitz’s WebContainers. This allows it to install npm packages, run Node.js servers, interact with third-party APIs, and deploy to production directly from the chat interface. Beyond simple code completion, Bolt.new offers a visual editor for fine-tuning layouts and logic, empowering both experienced developers and designers to quickly prototype and build high quality code. Users can download the clean, production-ready source code, ensuring no vendor lock-in.

Key features:

• AI-powered web development agent for full-stack apps in the browser.
• Natural language to code generation for frontend, backend, and database.
• AI control over the entire development environment (filesystem, terminal, etc.).
• Integrated visual editor for refining designs and logic.
• Supports running Node.js servers and npm packages.
• Seamless deployment to production directly from the interface.
• Ability to download source code (no vendor lock-in).
• Ideal for rapid prototyping and generating boilerplate code.

Pricing:

• Free – free of charge: 1M tokens per month, up to 150K per day
• Pro – $20 per month: 10M tokens per month
• Teams – $30 per user per month: role based access

Aider

Aider is a unique AI pair programming tool that operates directly within your terminal, offering a flexible and powerful way to collaborate with large language models (LLMs) on your coding tasks. It seamlessly integrates with your local Git repository, allowing for direct interaction and editing of your source code. Aider does not come with a built-in LLM; instead, it adopts a “bring your own key” (BYOK) model, enabling you to connect preferred external models like Anthropic’s Claude 3.5 Sonnet, GPT-4o, Google’s Gemini, or even local ones via Ollama.

This AI coding assistant empowers developers to write code, modify multiple files simultaneously, and request diverse changes. You can ask it to add features, fix bugs, refactor code, or update code documentation. Aider automates commits with sensible messages, streamlining your coding process. Further enhancing the AI pair programming experience, you can interact by adding images, URLs, or even using voice commands, making it a highly dynamic and efficient AI code tool for generating code suggestions and performing complex coding tasks.

Key features:

• Terminal-based AI pair programming, independent of specific code editors.
• Connects with any external large language models (BYOK model).
• Ability to edit multiple files and automate changes.
• Supports feature addition, bug fixing, code refactoring, and code documentation updates.
• Automated Git commits.
• Interactive commands, including image and voice input.

Pricing:

• Free – The Aider tool itself is free of charge. However, you will incur costs for the usage of the connected paid LLMs (e.g., OpenAI, Anthropic) based on their respective pricing models. You can use local models via Ollama with no additional costs.

Cursor

Cursor is an AI-native code editor specifically designed for AI pair programming. It deeply integrates large language models (LLMs) into the coding process, offering a seamless experience for writing code. Our team at Droids On Roids frequently uses Cursor for its intuitive approach to code generation and assistance, making it a valuable AI coding tool in our daily workflow.

This powerful AI coding assistant supports AI code completion and provides intelligent code completions as you type, significantly speeding up development. Beyond simple code suggestions, Cursor features an integrated chat that understands your existing code and context, allowing you to ask questions in natural language, refine code snippets, and even perform code refactoring. It can also crawl the code documentation of third-party libraries, providing instant answers.

Cursor stands out with its “Auto-Debug” feature, proposing fixes for issues directly in the terminal to help you debug code and achieve error-free code. It also offers quick fixes for lint-detected problems and a “Terminal” feature that translates natural language into proper commands. Further enhancing its utility, Cursor supports images in prompts, enabling visual input for complex coding queries.

Key features:

• AI-native code editor optimized for AI pair programming.
• Context-aware AI code generation and intelligent code completions.
• Integrated AI chat that understands your source code.
• “Auto-Debug” for suggesting and applying fixes, aiding in debugging code.
• Ability to read and summarize third-party library code documentation.
• Supports images in prompts for complex coding tasks.
• Translates natural language into terminal commands.
• Designed to enhance the entire coding process and improve code quality.

Pricing:

• Hobby – Free of charge, limited number of interactions.
• Pro – $20 per month, unlimited completions.
• Business – $40 per user per month, team billing, administration, privacy mode.

Gemini in Android Studio

Gemini in Android Studio is an essential AI coding assistant developed by Google. Built directly into the official IDE for native Android and Flutter apps, it’s a tool Karol, the author, personally uses frequently, along with other members of the Droids On Roids team, for enhancing their coding process in mobile development. This AI programming assistant excels at interpreting natural language queries to provide direct assistance with code generation, helping to write code efficiently. It can suggest code snippets, locate resources, and guide developers toward best practices, accelerating the software development process.

While Gemini offers impressive intelligent code completions and can propose entire functions, it’s vital to critically review and rigorously test its suggestions. As with any AI code generator, its output may occasionally require refinement to ensure high quality code and an error-free codebase, especially when working on complex coding tasks. Leveraging powerful large language models, Gemini provides context-aware code suggestions that anticipate your needs, making the coding process smoother. It can also assist in debugging code by highlighting potential issues within your source code.

Key features:

• Developed by Google and built into Android Studio, the official IDE for native Android, Kotlin Multiplatform and Flutter apps.
• Interprets natural language for code generation and assistance.
• Offers AI code completion and intelligent code completions, including entire functions.
• Helps with debugging and identifying issues.
• Requires logging in to a Google Account.
• A valuable AI code tool for streamlining the software development process.

Pricing:

• Free – Currently available at no cost. Option to add own Google AI Studio API key.

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JetBrains AI Assistant

The JetBrains AI Assistant is a powerful AI coding assistant deeply integrated across the suite of JetBrains IDEs, including IntelliJ IDEA, PyCharm, WebStorm, and Android Studio. This intelligent assistant is designed to streamline every aspect of the coding process, offering capabilities that go far beyond simple AI code completion. It’s particularly valued by our team at Droids On Roids for its seamless integration and ability to significantly boost productivity within our preferred code editors.

Leveraging various large language models (LLMs) from providers like OpenAI and Google, JetBrains AI Assistant acts as a versatile AI programming assistant. It can generate code based on natural language prompts, explain complex code snippets, and even perform code refactoring. Developers can interact with it directly within the IDE through an AI chat, asking questions about their existing code or seeking assistance with specific coding tasks. The assistant also offers context-aware code suggestions, automates code documentation, and helps with debugging, enhancing code quality and making the software development process more efficient. Its ability to work with multiple programming languages across different JetBrains products makes it a comprehensive AI code tool.

Key features:

• Deep integration across all major JetBrains IDEs.
• AI-powered chat for contextual questions and code explanations.
• AI code generation from natural language prompts.
• Intelligent code completion and code suggestions.
• Automated code documentation generation.
• Context-aware code refactoring and quick-fixes.
• Support for numerous programming languages.
• Coding agent.

Pricing:

• Free – free of charge. Small amount of cloud credits.
• AI Pro – €10 + VAT per user per month (included in the All Products Pack and dotUltimate). More cloud credits.
• AI Ultimate -€20 + VAT per user per month. Additional cloud credits.

Tabnine

Tabnine is a trusted AI coding assistant distinguished by its strong emphasis on privacy and security. Trained on existing code under permissive open-source licenses, it mitigates data and IP concerns; its SOC-2 compliance reinforces this. This intelligent AI programming assistant tailors AI code completion and AI code generation to your specific codebase and coding style, crucially without exposing sensitive proprietary source code. This helps developers write code of high quality code.

Tabnine operates in fully isolated modes—secured SaaS, on-premises, or VPC—ensuring your intellectual property remains under control. It learns from your code only with explicit opt-in; your existing code never leaves your environment, guaranteeing complete privacy. This makes it ideal for organizations prioritizing stringent security in their coding process using AI coding tools.

Tabnine also enables centralized policy enforcement, standardizing AI assistant configuration across teams. This simplifies management, providing full security and privacy control and enhancing the AI pair programming experience in secure software development environments.

Key features:

• High privacy and security (uses permitted code snippets).
• Flexible deployment: on-premise, VPC, or secured SaaS.
• Automated code documentation.
• Offers intelligent code suggestions, AI code completion, and AI code generation.
• Extensive IDE integrations across various programming languages, including Neovim, IntelliJ products, Visual Studio Code, Eclipse, and Sublime Text.

Pricing:

• Pro – $9 per month
• Enterprise – $39 per user per month: Advanced AI agents, premium support, private deployment, advanced admin features.

Programming with AI tools: Pros and cons

AI coding tools are transforming the software development process. As AI programming assistants, they significantly accelerate the coding process, helping developers write code faster. They excel at automating repetitive coding tasks and boilerplate code generation, providing intelligent code suggestions and code snippets through advanced AI code completion features. This frees developers for more creative problem-solving. Furthermore, these AI tools are powerful for identifying bugs, ensuring high quality code and overall code quality, leading to more efficient code.

However, challenges remain. While AI coding tools offer great code suggestions, they can struggle with highly complex problems, sometimes producing code generated that needs substantial human oversight to become truly better code and fit project specifics. Seamless integration with development environments can be a hurdle. Debugging AI-generated code is often tricky; a deeper code explanation is required to fix its logic. For sensitive proprietary code in regulated industries, ensuring AI-generated code compliance and security demands careful static code analysis.

AI-powered app development at Droids On Roids

At Droids On Roids, our developers actively integrate advanced AI coding tools into their daily work. Most of our team members leverage AI programming assistants like GitHub Copilot, JetBrains AI Assistant, or Cursor for their powerful AI code generation and intelligent code completion capabilities. Additionally, Gemini in Android Studio is a key AI tool for many of our Android developers. As Karol, the author, I personally utilize a subset of these AI coding assistants to streamline my coding process. We adhere to laws and licenses, so we have disabled suggestions that match public source code when using tools like GitHub Copilot.

In our development practice, these AI coding tools are supportive allies, not sole authorities. They assist in streamlining our processes, but the responsibility for building robust, maintainable, and high quality code rests firmly on our shoulders. We use AI to enhance our skills, not to replace the nuanced judgment and creative problem-solving that only experienced developers can provide.

What I appreciate about these AI tools is that they not only streamline my coding process by suggesting accurate code suggestions and code snippets but also help me debug code and optimize the code generated in real time, significantly reducing development time and ensuring better code.

Read also: Native vs. Cross-platform App Development

Wrap-up: Ship software faster with AI tools, but do it smartly

The artificial intelligence landscape for AI coding tools is constantly evolving, with new AI programming assistants and AI coding agents emerging rapidly. To keep pace, resources like There’s An AI For That® provide updated databases of AI tools for your coding tasks. For flexible access to diverse large language models, platforms like OpenRouter also simplify connecting to various powerful AI models.

In conclusion, leveraging AI coding assistants like GitHub Copilot, Tabnine, and others discussed here can profoundly improve your software development process. These AI tools offer numerous benefits: they intelligently generate code and provide code suggestions, boosting productivity, enhancing learning, improving code quality, and accelerating development cycles. Such AI pair programming capabilities help developers write code faster and produce better code. Remember, these tools are powerful supplements, not replacements, for human expertise.

Integrating the best AI coding assistants strategically ensures you gain more benefits than losses. Understanding their strengths for various coding tasks will bolster your development, helping achieve high quality code more consistently.