There is a simple story about AI and software development: models write more code, so organisations need fewer developers.
I think that story misses what is changing.
If AI can produce more of the implementation, the value of a developer shifts. Less time may be spent manually creating routine components. More value comes from deciding how the system should be built, which model is appropriate, how performance will be managed, where data should flow, what controls are required, and how the result will be maintained.
Generated code does not remove engineering trade-offs. It may increase them. A solution can work in a demonstration while being expensive, insecure or impossible to support at scale. The model may select a technically valid approach that performs poorly in our environment. It may duplicate capability, introduce fragile dependencies or consume far more compute than the outcome justifies.
That is where developers become more important, not less.
I see the future developer acting as designer, engineer, architect, reviewer and coach. They help business owners turn intent into a testable specification. They establish patterns that generated solutions must follow. They choose between models based on performance, cost, risk, and context. They review integrations, design observability, and make sure the organisation can operate what it creates.
This should be more satisfying work, but it will challenge identity. Many developers built their craft through the act of writing code. Asking them to move towards specification, curation and assurance is not a minor tooling change. It changes how expertise is demonstrated and where professional pride sits.
The transition will not be uniform. Some systems will still require deep manual engineering. Some generated implementations will not be dependable enough. The point is not that coding disappears. It is that coding is no longer the only, or always the most valuable, expression of software expertise.
There is another implication. If technical teams are released from repetitive construction, the organisation must resist filling that capacity with a larger queue of the same work. The opportunity is to redirect it towards architecture, security, resilience, data, AI safety, and complex problems that have remained unsolved.
AI may reduce the scarcity of code. It does not reduce the need for judgement. The developers who help organisations distinguish between something that runs and something worth operating may become more valuable than ever.