Potential Changes to Computer Science Curricula 

The following is an excerpt from the new book Vibe Coding: Building Production-Grade Software With GenAI, Chat, Agents, and Beyond by Gene Kim and Steve Yegge.

As vibe coding transforms our industry, changing the nature of what it means to be a programmer, let’s take a couple of moments to explore what this looks like for the universities and bootcamps that form part of the developer training pipeline. In a world where AIs can generate thousands of lines of code in seconds, the ability to write algorithms from scratch becomes far less critical. Instead, aspiring engineers need to develop a new set of competencies.

Code Reading

It’s no longer rare to be confronted with hundreds of changes across thousands of lines in a single day. This means giving every student extensive practice in code reading, more than has ever been common in traditional curricula. Students should look at code in multiple languages—C, Python, JavaScript, Kotlin, or anything else—and train themselves to skim and spot errors lurking under the surface. Using AI can help a lot here, but AIs also miss things (as often as humans, seemingly) and can have biases when summarizing. A human needs to be the backstop for when AI misses. So, you should provide your students with some code-inspection drills and exercises they can practice daily. In an era where developers will help generate tens of thousands of lines of AI-assisted code per day, students need to become speed-reading experts with an eagle eye for anomalies.

Precise and Articulate Communication

In the new world, your success hinges on how effectively you can direct your AI assistants. Back in the old days, when developers typed out code by hand one character at a time, you could get by with little to no communication skill. But vibe coding requires you to frame your goals and instructions clearly, to help avoid misinterpretation by both AIs and humans. We have had several major miscommunications with AIs; they’re like people and you need to be clear.

We see this as a fundamental role shift for developers, one that demands logical thinking, coherent language, and the ability to refine instructions at each iteration. (As author David McCullough says, “Writing is thinking. To write well is to think clearly. That’s why it’s so hard.”)³

Concentration: Keeping Multiple Projects Going

This skill is keeping larger and larger problems—and more and more of them—in your head as you work with multiple agents. Programming may no longer be about immersing yourself in one task for a day. For instance, Steve is running up to four concurrent agents, and each agent he adds gets more addictive, but also requires more context switching, which is increasingly taxing as you add agents. He is building up that muscle slowly. 

Multitasking also requires real version control discipline, since you’ll often be merging changes from multiple sources—your teammates will have lots of code from their AI teams as well, and these changes will all need to be integrated. AIs can help tremendously here. But you need to keep your eyes on it carefully, especially three-way and N-way merges.

Merging code requires conflict-resolution expertise. It also often requires discussion and human coordination. It helps to adopt a systematic approach to your process. Regardless of the process you use, stick to it, and you’ll make fewer mistakes.

Software Modularity and Architecture

Understanding how and why large systems are designed, how to enable independence of action, and how they behave under load, will become much more important than memorizing language specifics. The more advanced aspects of hardware, operating systems, or compilers—all under the hood for most developers at this point—can now be approached more sparingly in CS and software engineering degrees. But the conceptual underpinnings still matter—for troubleshooting, for early detection, for mentoring others, and for guiding the overall system design.

Entrepreneurial Awareness

Whether students join a major tech firm or start their own enterprise, small, AI-driven teams can disrupt markets. Knowing the essentials of business and revenue models, how to pitch ideas, and collaborating with other disciplines will serve students well—especially when they possess the technical know-how to create real, AI-augmented solutions. These are broadly useful skills to have in the new world.

Curricula in technical research and learning institutions have been changing for decades. They face a bigger challenge than ever. Schools will have to change to adapt to a new way of developing software that has replaced everything we knew and loved, practically overnight. 

For more insights on effective AI-assisted development, check out Kim and Yegge’s new book Vibe Coding and their podcast Vibe Coding with Steve and Gene on YouTube.

- About The Authors

Gene Kim

Gene Kim has been studying high-performing technology organizations since 1999. He was the founder and CTO of Tripwire, Inc., an enterprise security software company, where he served for 13 years. His books have sold over 1 million copies—he is the WSJ bestselling author of Wiring the Winning Organization, The Unicorn Project, and co-author of The Phoenix Project, The DevOps Handbook, and the Shingo Publication Award-winning Accelerate. Since 2014, he has been the organizer of DevOps Enterprise Summit (now Enterprise Technology Leadership Summit), studying the technology transformations of large, complex organizations.

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Steve Yegge

Steve Yegge is an American computer programmer and blogger known for writing about programming languages, productivity, and software culture for two decades. He has spent over thirty years in the industry, split evenly between dev and leadership roles, including nineteen years combined at Google and Amazon. Steve has written over a million lines of production code in a dozen languages, has helped build and launch many large production systems at big tech companies, has led multiple teams of up to 150 people, and has spent much of his career relentlessly focused on making himself and other developers faster and better. He is currently an Engineer at Sourcegraph working on AI coding assistants.

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