AI Can Write Code. Engineers Still Have to Make It Work.

Marc Benioff and Mark Zuckerberg have made bold predictions about AI and software engineering. But writing code is only one part of the job and the tools that generate it still need people to guide, review and improve their work.

Picture an AI coding assistant producing a patch that looks right. It compiles. The tests pass. But it misunderstands a requirement, breaks an older feature, or mishandles an unusual case.

Someone still has to notice.

That is my concern when I hear predictions that AI will replace software engineers. Generating code is not the same as building dependable software. Engineers have to understand what people need, fit changes into complicated systems, test what could go wrong and take responsibility for the result. AI can help with parts of that work, but it does not make the rest disappear.

In late 2024, Salesforce CEO Marc Benioff said the company might not add software engineers in 2025, citing productivity gains from AI tools. In January 2025, Meta CEO Mark Zuckerberg predicted that AI could become “a sort of mid-level engineer” that could write code. Those were significant statements, but they were forecasts about productivity and capability not proof that companies no longer need engineers.

There is a difference between a company deciding it can do more with its current team and a company being able to build and run software without engineers. Benioff’s comments were about Salesforce’s hiring plans. Zuckerberg was describing what he expected AI to be able to do. Neither statement, on its own, shows that AI can independently understand a product, maintain a large system and make sound decisions when something goes wrong.

A 2025 study by the research organization METR offers one useful test of the productivity claims. Sixteen experienced developers completed 246 tasks in open-source projects they knew well. For those tasks, the developers took 19% longer on average when they could use the AI tools tested. Yet after the study, they estimated that AI had made them faster.

That result needs context. It was a small study of experienced developers working in familiar, complex codebases, using a particular set of tools in early 2025. It does not prove that AI always slows engineers down. It does show that code generation and real-world productivity are different things and that perceived speed can differ from measured completion time. METR’s paper describes the study and its limits.

Google’s DORA research points to a related challenge at the team level. Its 2024 report found that higher AI adoption was associated with lower software delivery throughput and stability in the organizations studied. That is an association, not proof that AI caused the decline. The report suggests one possible reason: AI can help produce code faster, while larger changes can take longer to review and make systems less stable. Faster output still needs effective testing and review.

This is why engineers remain essential even when AI writes more of the code. People have to explain the goal, supply context the model may not have, judge whether the result meets the need, and feed mistakes and user feedback back into the system. That feedback might come from a failed test, a bug report, a customer who cannot complete a task, or an engineer who spots a security problem during review.
The same is true of the AI tools themselves. They depend on software, data pipelines, computing infrastructure, integrations, monitoring and safeguards. Engineers build and maintain those systems. Human feedback helps teams see where an AI feature is useful, where it fails, and what needs to change.

AI will change engineering work. It may automate some routine tasks, help teams move faster in some situations and affect how companies hire. But the real question is not simply whether AI can write code. It is whether it can reliably help deliver software that meets people’s needs and who checks that it does.

For now, the evidence supports a more careful conclusion than “engineers are being replaced.” AI can generate code. Engineers make sure that code belongs in a product, works in the system around it, and serves the people who use it.

Sources

• Marc Benioff’s 20VC interview
• Mark Zuckerberg’s January 2025 interview with Joe Rogan
• METR’s developer productivity study
• Google Cloud’s summary of the 2024 DORA report