Mentioned in 6 AI use cases across 2 industries
Think of AI code assistants as a smart co‑pilot sitting next to every developer: they read what you’re typing, suggest the next few lines or whole functions, explain confusing code, and help spot bugs — much like autocomplete on steroids for programming.
This is like an AI pair-programmer built directly into Visual Studio Code. As you type, it suggests whole lines or blocks of code, helps write tests, explains code, and can transform comments or natural language into working code snippets.
Think of AI code assistants as smart copilots for programmers. As you type, they guess what you’re trying to build and suggest code, explain errors, write tests, and help you understand unfamiliar code — like an always‑available senior engineer sitting next to every developer.
This is like giving every software developer a smart co-pilot that suggests code as they type, understands your codebase, and can help write, refactor, or explain code—while staying under your company’s control instead of sending everything to a public cloud AI.
Think of GitHub Copilot as an AI pair‑programmer that sits in your code editor and guesses what you want to type next, suggesting whole lines or functions based on what you’ve already written and your comments.
This is like giving every software engineer a smart co-pilot that reads their whole codebase, remembers how things work, and helps write, review, and understand code directly in their workflow.