Will AI Replace Software Developers?

AI is unlikely to replace software developers as a profession in the near term, but it is changing which tasks developers spend time on and which skills employers pay for. Coding assistants such as GitHub Copilot (released as a technical preview in 2021), Cursor, Claude Code and ChatGPT can write boilerplate, generate tests, explain unfamiliar code and complete small, well-specified changes. Agentic tools can also work across many files and run commands, which extends what can be delegated. The tasks that shift most have clear specifications and easy verification: routine endpoints, data transformations, test scaffolding, documentation and library migrations. The tasks that shift least involve ambiguity: working out what users actually need, designing systems that will be maintained for years, making security and reliability trade-offs, and debugging failures that span several services. Evidence on productivity is mixed. Vendor and lab studies have reported faster completion on contained tasks, while a 2025 randomized study by METR found that experienced open-source developers working in codebases they knew well took longer with AI tools, even though they believed the tools had sped them up. Gains depend on the task, the codebase and how the tools are used. Hiring trends are hard to attribute to AI alone. Tech hiring slowed after 2022 alongside higher interest rates and post-pandemic corrections, and entry-level roles have been especially competitive. A real concern is that if junior tasks are automated, fewer people gain the experience needed to become senior engineers. A common misconception is that writing code is the whole job. Much of the work is reading code, clarifying requirements, reviewing changes and owning outcomes in production. Skills that grow in value include code review, system design, testing strategy, security awareness, domain knowledge and specifying problems precisely.