AI-Assisted Coding: A Developer's Perspective

Artificial Intelligence has moved from a buzzword to a daily utility in a developer's toolkit. Tools like GitHub Copilot, ChatGPT, and Claude are fundamentally changing how we write code.

The Shift in Workflow

Previously, a significant portion of time was spent typing out syntax or searching StackOverflow for boilerplate. AI handles this now.

• Boilerplate Destruction: "Create a React component that fetches users and displays a table." This is done in seconds.
• Test Generation: AI is surprisingly good at writing unit tests if you provide the implementation logic.
• Regex & Types: Writing complex Regex or TypeScript generics is error-prone. AI is a great assistant here.

The "Copilot Pause"

There's a new behavior pattern: developers pausing for a second to let the Ghost Text appear. We are becoming Editors rather than Writers. This requires a higher level of understanding, because you must be able to read and verify code faster than you write it.

The Pitfalls

• Hallucinations: AI will confidently invent libraries or syntax that don't exist.
• Security: It might suggest insecure patterns if its training data contained them.
• Context Window: It often lacks the full architectural context of your large repo (though this is improving with RAG).

The best developers in the future won't be the ones who ignore AI, but the ones who can orchestrate it to multiply their output while maintaining high quality standards.