The important shift is not that developers will stop writing code. It is that code generation, testing, documentation, search, and debugging are becoming increasingly assisted. The valuable skill is moving from typing every line to defining problems, verifying outputs, and designing reliable systems.
Build five habits: write clear specifications, ask tools for small changes, review generated code, run automated tests, and document decisions. Learn enough security to recognize prompt injection, unsafe deserialization, secret leakage, dependency risks, and excessive permissions.
Use AI where errors are cheap and visible, such as scaffolding, test-case ideas, refactoring suggestions, and documentation drafts. Add stronger review when output touches authentication, payments, personal data, infrastructure, or production migrations.
Develop durable fundamentals: Python or another language, HTTP, databases, version control, testing, observability, and system design. AI tools amplify good engineering judgment; they do not replace it.
A useful portfolio project should show the full loop: a clear requirement, a small implementation, tests, security notes, deployment instructions, and a retrospective explaining what the AI suggested and what you changed. That demonstrates modern productivity without pretending generated code is automatically correct.