Coding agents are exciting because they are verifiable. You can write tests for code, and the tests will indicate whether the code is functioning correctly, which is not possible in many other fields.

The next limiting factor for coding agents will be verification. While models are improving at writing code, real-world applications often lack perfect unit tests, making verification challenging.

The future of coding agents will involve the ability to request features and receive completed code, which will revolutionize how software is developed.

Coding has rapidly evolved, with AI tools significantly impacting how software is developed, leading to nonlinear progress in the field.

As coding agents improve, they highlight inefficiencies in product organizations, making alignment meetings more critical and time-consuming.

The development of autonomous coding agents like Devin is a significant step forward in the evolution of software engineering.

As programming evolves, the need for manual coding will decrease, with more emphasis on managing agents that handle coding tasks.

We're entering an abundance era where coding agents will lead the way, raising questions about the quality of AI outputs when labor becomes cheap and plentiful.

In the generative AI era, engineers can write code faster than ever, but this is just the beginning; thorough code review and understanding user needs are essential for product quality and completeness.