AI-assisted Software Development: Tools & Processes

AI assisted software development

In the rapidly evolving landscape of software development, the integration of artificial intelligence (AI) and generative AI (Gen AI) is not just a luxury but a cornerstone for enhancing software development velocity. This blog delves into the key aspects of Gen AI and AI-assisted software development, presenting actionable takeaways for software leaders, including engineering managers, project managers, product managers, and software engineers. We will look into different tools and related processes that can be enhanced across the entire software development lifecycle.

Design & Architect: Crafting the Blueprint

Integrate the following tools to speed up the design process while ensuring adherence to best practices, significantly reducing design iteration times.

  • DALL-E 3: Ideal for generating variations of images with consistent styles, useful for branding and UI elements. You can use Bing Image Creator for this.
  • Canva: Boasts AI features like Magic Resize for graphics, useful for rapid prototyping of designs.
  • Adobe Sensei & Firefly: Integrated across Adobe products, these AI tools help with content intelligence and generative design features.
  • Microsoft Designer

Code & Build: Implementation Phase

Leverage these AI coding assistants to automate repetitive tasks, ensuring more time is spent on complex problem-solving and innovation.

  • GitHub Copilot: AI-powered coding assistant that provides suggestions and autocompletes code.
  • Tabnine: Offers advanced code completion and integrates with your unique codebase, adapting to your organizational coding styles.
  • Google Cloud AI Code Generator: A robust tool for generating and explaining code, and powering conversations in various programming languages.
  • AlphaCodium: AlphaCodium takes a unique approach to code generation by employing a test-based, multi-stage, iterative process. This process is designed to tackle complex coding problems by running the generated code against tests, and making corrections until the code is error-free. AlphaCodium’s performance has been tested and proved to outperform existing models like AlphaCode, showing a 12-15% increase in accuracy on average.
  • ChatGPT is very useful for writing and optimizing code, as well as debugging and generating documentation.
  • Bard also does a great job in code generation like ChatGPT.
  • Amazon CodeWhisperer is another useful tool for AI-assisted coding. It’s designed to help developers by providing real-time code recommendations. This tool, developed by Amazon Web Services (AWS), is capable of generating code suggestions that are tailored to the application code you’re working on.
  • Android Studio Bot: Assists with Android app development by generating code solutions and optimizing best practices.
  • Anthropic Claude

Integrate: The Synthesis Phase

Generative AI tools are becoming increasingly valuable for creating unit tests and integration tests. These AI-powered tools can automatically generate test cases based on the code’s behavior, which helps in achieving high coverage and ensures that the various components of the application work together as expected. One of the ways generative AI assists in this phase is by understanding the intended functionality of a piece of code and then creating tests that verify this functionality.

Some of the following generative AI tools can be used for test suites:

  • ChatGPT: ChatGPT can be used to generate test cases by conversing in natural language, describing the functionality, and receiving corresponding unit and integration test scripts for various scenarios. It can help in writing unit tests and integration tests.
  • AlphaCodium: AlphaCodium’s iterative approach to code generation can be harnessed to produce unit tests, ensuring the code logic fulfills specified requirements with each iteration.
  • Bard: Google Bard’s ability to generate new content from prompts and instructions makes it a potentially valuable asset for developers and QA engineers. When tasked with developing tests for a specific website or application, Bard can provide prompts for creating test cases, page objects, and actual tests. This can significantly speed up the process of test development, allowing QA teams to focus on more complex tasks that require human intervention.
  • Anthropic Claude

Deploy/Release: The Distribution Stage

Utilize Generative AI to maintain clear and comprehensive documentation and to facilitate the design of user interfaces for better deployment strategies. Tools such as ChatGPT, Google Bard can be used for creating the documentation.

Ajitesh Kumar
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Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog,
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