Programming in the Age of Generative AI

Learn how generative AI is changing the face of writing, testing, and even thinking about code.

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Generative artificial intelligence (GenAI) is no longer science fiction. It has become part of our lives as an empowered force that can understand natural language and produce human-like text, images, and even code.

There are many AI tools today that can boost the software development process, if not totally automate it. What would have taken many hours to do manually — writing boilerplate code, debugging for several hours only to find syntax errors, and spending long hours on a function documentation — can now take seconds thanks to the likes of GitHub Copilot, ChatGPT, or Amazon Code Whisperer. These models are fed on huge datasets of code and text, which make up their large language models (LLM), and prompt them to understand how to respond in advanced ways even better than experienced developers.

Generative AI represents a paradigm shift as it brings natural human language and computer code closer than ever before, leading to a future where coding becomes as much communication as logic.

How GenAI is transforming programming and the SDLC

Generative AI tools do not simply replace mundane tasks but redefine the process of building an application. Here is how these tools are helping.

Code creation and autocompletion:

Code generation has traditionally been a painstaking task that required deep knowledge of syntax, libraries, and logic structures. Generative AI tools such as GitHub Copilot and Tabnine change that by providing suggestions for complete lines or blocks of code as programmers type.