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In this episode, we explore how Large Language Models (LLMs) like GPT-4 and GitHub Copilot are revolutionizing full-stack web development—from speeding up boilerplate generation and test writing to simplifying infrastructure-as-code and DevOps workflows. Based on the white paper Enhancing Full-Stack Web Development with LLMs, we break down the tools, use cases, architectural patterns, and best practices that define modern AI-assisted development.
We cover real-world applications, including LLM-driven documentation, code refactoring, test generation, and cloud config writing. We also dive into the risks—like hallucinated code, security gaps, and over-reliance—and how to mitigate them with a human-in-the-loop approach. Whether you're a solo developer or leading a team, this episode offers a comprehensive look at the evolving toolkit for building smarter and faster with AI.
In this episode, we explore how Large Language Models (LLMs) like GPT-4 and GitHub Copilot are revolutionizing full-stack web development—from speeding up boilerplate generation and test writing to simplifying infrastructure-as-code and DevOps workflows. Based on the white paper Enhancing Full-Stack Web Development with LLMs, we break down the tools, use cases, architectural patterns, and best practices that define modern AI-assisted development.
We cover real-world applications, including LLM-driven documentation, code refactoring, test generation, and cloud config writing. We also dive into the risks—like hallucinated code, security gaps, and over-reliance—and how to mitigate them with a human-in-the-loop approach. Whether you're a solo developer or leading a team, this episode offers a comprehensive look at the evolving toolkit for building smarter and faster with AI.