With AI making code generation cheap, the limiting factors for development velocity are now defining what to build (product) and ensuring its quality (review). Engineers will increasingly focus on high-level systems architecture rather than typing code.

AI coding tools automate implementation, elevating the developer's role from writing logic to designing systems, reviewing AI-generated code, and making high-level architectural decisions. The focus moves from implementation details to overall system design and strategy.

As AI handles low-level coding, Barbara Liskov suggests the crucial human skill will be working at a higher level of abstraction. The future engineer's role will involve design, modularity, and verification to ensure the systems AI builds are correct, safe, and meet specifications, rather than focusing on implementation minutiae.

The programmer's role is evolving from a craft of writing code to a managerial task of orchestrating fleets of AI coding bots. The critical skill is no longer manual typing but directing, debugging, and arguing with these AIs to achieve a desired outcome.

With AI handling a large percentage of code generation, the core work of an engineer is evolving. The job now involves spending more time planning what code to generate and carefully reviewing the AI's output, a significant shift from the traditional focus on manually writing code.

As AI agents handle the mechanics of code generation, the primary role of a developer is elevated. The new bottlenecks are not typing speed or syntax, but higher-level cognitive tasks: deciding what to build, designing system architecture, and curating the AI's work.

AI tools are automating code generation, reducing the time developers spend writing it. Consequently, the primary skill shifts to carefully reviewing and verifying the AI-generated code for correctness and security. This means a developer's time is now spent more on review and architecture than on implementation.

With AI agents and non-technical staff now generating code, the primary bottleneck has moved from code creation to code review. The human's job is becoming less about writing lines of code and more about applying taste, judgment, and architectural oversight to AI-generated outputs.

The craft of software engineering is evolving away from precise code editing. Much like compilers abstracted away assembly language, modern AI coding tools are a new abstraction layer, turning engineers into directors who guide AI to write and edit code on their behalf.