AI Code Generation: Wins, Fails and the Future
IBM Technology. Discusses the uneven "barbell" shape of AI coding performance, architecture ownership, agent orchestration, context limits, open-source versus proprietary tooling and why models can solve hard tasks while still failing ordinary engineering details. That supports the article's rule that tests and human review remain the shipping gate.
AI Expert note
Tool names and model rankings will change quickly. Keep the durable lesson: the repository remains the source of truth, the human keeps architecture ownership, and tests, security review and product acceptance decide whether generated code ships.
What you should get from this
Build a realistic mental model for when repository-aware coding agents help and where senior engineering control is still required.
Watch or know first
Experience reviewing pull requests, reading production code and judging whether a software change is safe to ship.
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