OpenAI chairman says students should still get computer science degrees — even if they won't be typing code
Bret Taylor serves as chairman of OpenAI, the AI giant that recently rolled out its own AI coding agent, Codex. The tool is set to compete with Anthropic's Claude Code, Cursor, Replit, and other vibe-coding products competing for market share.
These tools are designed to allow engineers to write fewer and fewer lines of code. The goal is a world where all you need is to prompt an agent and review its output.
Even with the rapid growth of AI coding, Taylor said he continues to support the computer science major. On his podcast, host Lenny Rachitsky asked Taylor whether students should still learn to code.
"Studying computer science is a different answer than learning to code, but I would say I still think it's extremely valuable to study computer science," Taylor said.
Taylor listed some of the concepts that computer science majors may understand that aren't mere coding languages: Big O notation, complexity theory, randomized algorithms, and cache misses.
"There's a lot more to coding than writing the code," he said. "Computer science is a wonderful major to learn systems thinking."
Taylor received a BS and MS in computer science from Stanford University.
Many of Taylor's AI competitors and colleagues agree. Microsoft CPO Aparna Chennapragada recently struck a similar tone on the same podcast. Chennapragada said that AI pushes programming to a "much higher level of abstraction," but that it doesn't eliminate the need for coding knowledge.
Sameer Samat, Google's head of Android, told BI that computer science needed a rebrand. Instead of "learning to code," Samat said that computer science should be framed around "the science, in my opinion, of solving problems."
Meanwhile, the early impact of AI-assisted coding tools is clear.
At Google, CEO Sundar Pichai said that AI writes 30% of the company's new code.
On the podcast, Taylor envisioned a future in engineers are "operating a code-generating machine," rather than typing into a terminal.
"Your job as the operator of that code-generating machine is to make a product or to solve a problem," Taylor said. "Systems thinking is always the hardest part of creating products."
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