As AI coding agents generate vast amounts of code, the most tedious part of a developer's job shifts from writing code to reviewing it. This creates a new product opportunity: building tools that help developers validate and build confidence in AI-written code, making the review process less of a chore.

As AI generates more code than humans can review, the validation bottleneck emerges. The solution is providing agents with dedicated, sandboxed environments to run tests and verify functionality before a human sees the code, shifting review from process to outcome.

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 generating code, a developer's value shifts from writing perfect syntax to validating that the system works as intended. Success is measured by outcomes—passing tests and meeting requirements—not by reading or understanding every line of the generated code.

As AI generates more code, the developer tool market will shift from code editors to platforms for evaluating AI output. New tools will focus on automated testing, security analysis, and compliance checks to ensure AI-generated code is production-ready.

Formal verification, the process of mathematically proving software correctness, has been too complex for widespread use. New AI models can now automate this, allowing developers to build systems with mathematical guarantees against certain bugs—a huge step for creating trust in high-stakes financial software.

The role of a senior developer is evolving. They now focus on defining outcomes by writing tests that a piece of code must accomplish. The AI then generates the actual implementation, allowing small teams to build complex systems in a fraction of the traditional time.

The current model of a developer using an AI assistant is like a craftsman with a power tool. The next evolution is "factory farming" code, where orchestrated multi-agent systems manage the entire development lifecycle—planning, implementation, review, and testing—moving it from a craft to an industrial process.

It's infeasible for humans to manually review thousands of lines of AI-generated code. The abstraction of review is moving up the stack. Instead of checking syntax, developers will validate high-level plans, two-sentence summaries, and behavioral outcomes in a testing environment.