Generative AI tools and platforms are changing the software development lifecycle and the way software products are developed, accelerating the process and quality of the final output. Artificial intelligence boosts developers’ productivity and speed even by 50%, improve end user satisfaction, and help deliver innovative applications more quickly than ever.
From workflow automation, automating mundane coding tasks or providing auto-complete suggestions to assisting in bug detection and resolution, GenAI tools allow software engineers to focus on creative problem-solving and building high-quality software. Yet, with constantly new AI tools for software development popping out, choosing the right one may be a challenge.
Whether you’d like to be more productive, simplify creative tasks or complex code, this article highlights the best generative AI tools available today, together with their key features, use cases, and pricing.
What is generative AI?
Generative artificial intelligence refers to advanced machine learning technology that can create different types of content such as text, images, audio, and video. Based on patterns learned from the existing data, the technology generates original outputs that resemble human creativity.
GenAI improves workflows, encourages new ideas, and allows businesses to reduce expenses. Already, 92% of Fortune 500 companies have adopted it in their processes.
GenAI platforms vs tools for developers: What is the difference?
Generative AI tools are software programs that help with specific tasks, like writing text, creating images, or generating code. They have a rather narrow purpose and can be used on their own or built into other apps, websites, or search engines to make work easier.
GenAI platforms offer a broader range of services as their ecosystem can include multiple tools, models, and other elements. They let users build, test, and manage different projects. Unlike single-use tools, platforms provide more options and flexibility, making them useful for businesses and developers who need a complete or tailored solutions.
How can GenAI tools and platforms be used in software development?
Depending on the needs, GenAI tools and platforms can be used for various purposes. For software development, they can be used as an assistant for programmers or as a guide on how to solve common coding errors and problems. There are many GenAI tools and platforms available on the market. Let’s have a look at the most helpful for the software development industry.
AlphaCode by Google DeepMind
AlphaCode by Google DeepMind is a system developed for competitive programming that shows how far code creation has come. It uses Gemini Pro model’s power to handle challenging coding tasks at a speed comparable to human programmers. It has achieved a ranking within the top 54% in simulated tests on platforms like Codeforces.
With a dataset of more than 15 thousand problems and 30 million human code samples, AlphaCode revolutionizes how AI helps developers by generating code, automating routine tasks, and improving problem-solving.
AlphaCode by Google DeepMind — use cases
AlphaCode can facilitate programmers and improve their productivity by providing real-time code suggestions, AI-driven code reviews and bug fixes, or performance optimizations. It automates repetitive coding tasks and helps write cleaner code. Also, AlphaCode supports engineers in learning new languages by providing them with code examples created by AI. It can assist business users in scaling AI-powered coding solutions for large projects.
AlphaCode by Google DeepMind — pricing
Alpha Code is free to use.
GitHub Copilot
By partnering with OpenAI, GitHub created Copilot—a leading code completion tool that seamlessly integrates with popular code editors like Visual Studio Code and JetBrains. The goal was to make developers’ lives easier with an AI pair programmer that helps to write code faster and more efficiently. The name itself reflects the company’s message that AI isn’t to replace the developer, but to be always on their side.
GitHub Copilot makes real-time code completions and recommendations as developers type in the integrated development environments (IDE). It uses advanced AI models, like OpenAI’s Codex, to understand the context of the code and offer relevant suggestions. Currently, it’s widely used and has become an industry standard.
GitHub Copilot — use cases
It creates relevant code snippets, gives ideas in real time, supports multiple programming languages, and can adapt to individual developers’ coding style. By using GitHub Copilot, developers can speed up their work, learn new concepts, and find alternative coding approaches and innovative solutions.
This GenAI for software development serves both experienced developers and beginners. Having AI-generated code together with explanations, users find it easier to meet tight deadlines and navigate and contribute to large codebases.
GitHub Copilot — pricing
GitHub Copilot offers several pricing plans:
- Individual: $10/month or $100 annually
- Business: $19 per user/month
- Enterprise: $39 per user/month
There’s also a free limited option: users have 2,000 code completions and can pull 50 chat requests per month.
Duet AI for developers
Duet AI is a collaborative tool for developers, development and cross functional teams, which integrates GenAI into Google Workspace and Google Cloud to boost productivity and optimize workflows. This gives programmers an opportunity to work together across different coding environments, which is especially valuable in large projects where a consistent coding style and shared architecture are key to success.
Additionally, Duet AI works well with project management tools to help keep track of progress and predicts when a project will be finished based on coding speed and complexity.
Google Duet AI — use cases
It supports more than 20 programming languages such as C, C++, Go, Java, JavaScript, or Python and integrates with multiple IDEs, including Visual Studio Code, IntelliJ, PyCharm, and Cloud Shell Editor. Developers can use the tool to simplify complex concepts, stick to best practices, and handle repetitive tasks. By debugging, troubleshooting, and generating boilerplate code, it helps save time and focus on important tasks.
Moreover, Duet AI can also be customized to suit the specific business needs by using private codebases, which makes it a flexible tool for enterprise software development.
Duet AI by Google — pricing
Currently, there is no specific price for the tool. AI developers can get a custom quote for their organization by contacting a Google Cloud sales representative.
Claude.ai
Claude.ai is a chatbot powered by Anthropic’s Claude 3.0 model family. Released in February 2025, Claude 3.7 Sonnet represents the latest advancement in the lineup. What makes Claude stand out is that it can write good code and think like an experienced developer. It can process up to 200,000 tokens of context, which equals around 150,000 words or a small codebase.
Anthropic says that GitLab’s development teams are 25–50% more productive when they use Claude. Sourcegraph, a code intelligence platform, reported a 75% rise in code insertion rates after choosing Claude as its main AI tool for developers.
Claude.ai by Anthropic — use cases
With Claude.ai developers can write, test, and debug complex software, and translate code between various programming languages. Through Github integration, they can analyze codebases with expert-level reasoning and make better engineering decisions in a shared workspace. For technical teams, it serves as both a productivity tool and a learning resource of modern technologies that accelerates development work.
Anthropic Claude.ai— pricing
Claude.ai has varying prices based on the model:
- Claude 3.5 Haiku: Input $0.80/MTok and output: $4/MTok
- Claude 3.7 Sonnet: Input: $3 / MTok and output: $15/MTok
- Claude 3 Opus: Input: $15/MTok and Output: $75/MTok
Amazon Bedrock
Amazon Bedrock is a solid option for software developers, especially for the integration of generative AI within processes. It offers access to foundation models (FMs) like Anthropic, Stability AI, and AI21 Labs through a single API. With this platform, it becomes easier to build and deploy GenAI applications without worrying about managing the underlying infrastructure and security.
Amazon Bedrock — use cases
Bedrock automates coding and debugging, generates detailed explanations for codebases and APIs, and even creates unit tests. It helps developers produce code snippets based on natural language prompts and boost team communication by simplifying repetitive coding processes. Amazon Bedrock also optimizes DevOps pipelines, improving software development efficiency and security.
Amazon Bedrock — pricing
Amazon Bedrock offers a few types of pricing:
- On-demand: Users pay for the resources they use without any long-term commitments. Prices depend on the model, but it’s usually a few cents per thousand tokens.
- Provisioned throughput: In this option, users commit to using a specific amount of processing power for a month or six months and pay by the hour. The longer the commitment, the lower the rate.
- Batch mode: It processes many prompts in one go, storing answers in an Amazon S3 bucket so that they can be accessed anytime. This mode costs 50% less than on-demand rates for selected models.
More details are available on their website.
Google Vertex AI
Google Vertex AI is a unified machine-learning platform that makes it easy to create, deploy, and manage ML models and AI applications. It brings together tools for data preparation, model training, evaluation, and deployment into one place, so users don’t have to be experts in all of them.
With over 160 foundation models in its Model Garden, including Google’s Gemini models, Vertex AI supports text generation, image recognition and custom ML use cases. It’s designed to streamline workflows and scale AI applications using Google Cloud’s infrastructure.
Google Vertex AI — use cases
Vertex AI is useful for software development processes because the platform helps developers easily integrate AI and GenAI into their apps. It uses GenAI for effic