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AI in Software Development

Definition

AI coding systems support code generation, explanation, testing, refactoring, repository search and increasingly agentic software tasks that operate across tools.

What AI coding tools do

AI coding systems generate and explain code, write tests, search repositories, refactor functions, summarize changes and increasingly operate as agents that can edit multiple files and run development tools.

Why repository context matters

A code model can write a plausible function without understanding the project's actual interfaces. Better systems inspect files, types, tests and dependency information before editing. Retrieval and tool use are therefore central to serious coding agents.

Why tests remain essential

Generated code can compile and still be wrong or insecure. Automated tests, linters, code review and runtime checks are the evidence that an AI-generated change works. AI speeds production of candidate code; it does not remove software engineering discipline.

Related terms, defined

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.