AI Code Generation

Harness the power of AI in your entire software development lifecycle. Increase coding speed and quality while optimizing the code environment for maximum benefits.

What is AI code generation?

AI code generation is artificial intelligence technology that writes and completes code for you. Using natural language, you can make specific feature or functional requests, and AI generates the necessary code. AI coding tools integrate with your existing codebase and automate other development tasks like bug fixing, vulnerability scanning, and code optimization. AI code generation boosts developer productivity and streamlines the software development process.

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Benefits of AI code generation

AI code generation tools do not replace developers. Instead, they assist development teams in focusing on creative and high-impact tasks while taking care of the more tedious aspects of software development.

AI code generation is revolutionizing software development by automating repetitive tasks and allowing developers to focus on problem-solving and architecture. It maintains your coding style while improving speed and accuracy.

This technology assists with time-consuming tasks like writing tests, configuring settings, and creating data models. It also helps with best practices such as code commenting and descriptive naming. AI support simplifies debugging by handling routine tasks like writing and deleting debug statements.

By reducing the cognitive load associated with these activities, AI enables developers to code longer with better focus. This leads to enhanced productivity and more streamlined development processes. Teams can tackle complex projects more efficiently, dedicating more energy to innovative solutions rather than mundane coding tasks.

Developers repeatedly switch contexts in the code development process, such as looking up documentation, searching for example code snippets, or running tests on the command line. They also have to think through complex coding structures and syntax details and plan ways to express abstract ideas in code.

AI code generation tools help you do everything from a single place. You can have natural language conversations with AI and ask it to look up relevant information online or in third-party documents as needed. Focus on higher-level thinking and strategic planning while offloading the responsibility of remembering details to AI code generators.

The AI-powered code assistant knows your codebase and its challenges, so you don’t have to restate every problem. Get answers immediately and ask follow-up questions without leaving your trusted coding environment.

AI coding tools provide real-time code suggestions based on industry best practices. They help you identify security vulnerabilities and suggest design improvements. They can also automatically refactor code blocks to enhance maintainability and increase performance. The tool also prevents common coding mistakes that can cause more significant issues or result in time wastage in resolving bug fixes. You can create cleaner, error-free, and more readable code.

AI code generation makes code development easier for new developers. They get contextual guidance and code examples that facilitate the learning curve for new programming languages. They also get additional support if onboarding to new projects.

For example, the tool can:

  • Generate code based on the new programmer's natural language input.
  • Provide code explanations so they can quickly learn and contribute to new projects.
  • Provide step-by-step instructions to complete complex coding tasks.
  • Review existing code and make suggestions for improvement.

AI code tools can also help non-technical team members contribute more to the coding process. Business users best know the functionality of their applications. They can describe new features or issues to the tool and use the AI-generated code to explain requirements to developers. It bridges the gap between technical and non-technical teams to streamline software development.

Writing code is only one aspect of software development. The code must run in the correct environment containing required configurations, libraries, and other dependencies. Developers often have to maintain multiple build, test, and production environments and manage the pipeline from new development to code integration and deployment. Advanced AI code generation tools go beyond source code generation to introduce efficiencies in every aspect of the software development lifecycle.

How does AI code generation work?

You can think of AI code generation as pair programming with AI. An AI coding tool is like having a pair programmer always beside you that integrates within your IDE or coding environment and can look for information within your code base to suggests improvements, and collaborates on code, making development more efficient and interactive. Some tasks it can help you with are listed below.

Code generation

Your AI tool can generate code in various programming languages using natural language descriptions. You can explain desired functionality in natural language text. The AI "understands" your descriptions and generates contextually relevant code that follows established programming patterns and best practices. All generated code is highlighted, and it is up to you if you want to use the code as is, with modifications, or not at all.

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Code completion

Your AI code generator is also an AI code completion tool. It can suggest code snippets as you type by predicting the next most likely code snippet based on the context. You must connect the tool to your code repositories for this functionality to work. Machine learning and deep learning technology in the code generator support prediction alongside code generation capabilities.

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Code modernization

Code modernization is upgrading existing codebases from legacy frameworks or older versions to modern versions. Modernization tasks require developers to find and remove unsupported coding constructs in the new version. While most legacy codebases are functional and usable, a small percentage of legacy constructs impact the entire system. AI code generation tools can quickly find and highlight the code that needs removal. They can also generate the modern equivalent without disturbing variable names and other references. This speeds up modernization projects while maximizing code reuse.

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Code translation

For some use cases, the codebase has to be translated into other programming languages — like for compatibility with new tools or to increase efficiency. Beyond replacing code statements from one language to another, code translation requires developers to refactor the codebase to maximize the benefits of the target language. Specific code designs may change or become unnecessary in the new programming language.

AI code generation tools reduce the complexity involved in code translation. They can automatically generate optimum code in the new language by reading functions in the old language. You can also improve design by providing natural language prompts that guide the AI translation process.

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Code review

An AI code tool can also generate code based on existing code reviews and assessments. The tool scans your code for security vulnerabilities, bugs, and common coding errors. It then generates code that fixes or resolves those issues as needed. Automatic reviews and code improvement save developer time while maintaining code quality.

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Features to look for in AI coding tools for enterprise

When implementing AI code generation software in your organization, consider the following:
Not all code generation tools have the capabilities highlighted above. Some generate code but don't provide code translation or modernization. Other tools go beyond code generation to support infrastructure management, code deployment, and production tasks. Look for AI coding tools that provide the functionality you need.
Your AI code generator should integrate with your existing developer tools and code infrastructure. For example, if you have several applications in the AWS cloud, you want your code tool to know and make suggestions related to the best AWS services for your use case. You want it to integrate and work with the IDEs and other technology your developers frequently use and work with.
Enterprise-grade applications require end-to-end security regarding who accesses your code and how it is used. Your AI code generator should provide enterprise-grade access control, encryption, and other security features to meet all regulatory and compliance requirements.
The tool should provide flexible pricing options so it is practical to implement at scale for all team members. Charging should be usage-based to avoid fixed monthly expenditures. Free and low-cost options are a must for small software development projects.