SAN FRANCISCO — Anthropic, the company behind the Claude AI models, says its AI now writes almost all the code for its internal software. Human engineers mostly review and manage what the AI produces, according to company leaders and industry experts. This isn’t just a small tweak—Anthropic is showing how generative AI can reshape the heart of engineering work.
Mike Krieger, Anthropic’s Chief Product Officer, says their whole approach to building software has turned upside down in just a few months. Instead of developers writing code line by line, their Claude AI system spits out huge sections of code on its own. Engineers now spend most of their time checking, testing, and planning—making sure everything works and fits together. Teams at Anthropic regularly deal with automated pull requests containing thousands of lines of AI-written code. That’s become the new normal.
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Why This Matters
1.Switching to AI-generated code throws out a lot of old ideas about how software gets built.
2.Teams move faster. The AI cranks out code quickly, so people can prototype and build new products way faster than before.
3.But engineers aren’t out of the picture. They still review code, run tests, debug problems, and handle the big-picture architecture. AI writes, but humans make sure it’s right.
4.The job changes. Instead of hammering out every line of code, developers now guide and critique the AI’s work, shaping solutions rather than building them from scratch.
5.A lot of folks in tech see this happening elsewhere, too. Other AI companies report the same thing: AI tools are cutting down on repetitive coding, so developers can focus on design, architecture, and solving trickier problems.
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What This Means for the Industry and Developers
People are excited about how much more productive teams can be, but this shift brings up real questions about what software engineering will look like from here on out.
The job is different now. Routine coding is fading as AI takes over the basics, so engineers are moving toward more oversight, design, and system-level thinking.
Skills have to grow. Developers will need to go deeper into system architecture, testing, and quality assurance to stay ahead in a world where AI handles the grunt work.
The market’s paying attention. Some tech stocks have already reacted to the news that automation is ramping up—investors are watching to see how demand for traditional coding skills changes.
Still, experts point out that AI isn’t building things alone. Humans set the goals, define the constraints, and handle testing. When it comes to tough decisions or complex problems, people are still in charge. As Anthropic and other companies keep improving models like Claude Opus 4.6, AI will probably get even more involved in writing, debugging, and optimizing code. Researchers are working on making these systems smarter at spotting bugs, improving performance, and tuning software automatically.
It’s not just engineers who need to adapt. Companies and schools are starting to think about what skills future tech workers need—like understanding AI models, thinking about ethics, and integrating big, complex systems. AI isn’t about to replace software engineers, but the way software gets built is changing fast. In this new era, engineers review and steer the work, while AI does more of the heavy lifting. The tools are different, but the need for good judgment and expertise is as important as ever.
