The vibe coding revolution
Vibe coding has the potential to unlock new forms of creativity and democratize access to software development.
Democratizing technology
The barrier to creating apps, websites, and even entire businesses has been significantly reduced as conversational AI chatbots replace the need for deep technical expertise in coding languages. Kids as young as eight years old can now vibe code.
Increased speed
Vibe coding increases the speed of development and prototyping. What used to take days now takes hours. What used to take hours now takes minutes. The time between idea and workable prototype has shrunk, and the experience has improved.
- In educational settings, students can rapidly prototype ideas and receive immediate visual feedback, leading to a more engaging and motivational approach to learning.
- In professional settings, 84% of developers are using AI coding tools in their workflows, according to the 2025 Developer Survey.
Greater creativity
Instead of spending time mastering the precise rules, structures, and syntax of programming languages (such as debugging semicolon placement and memorizing function signatures), people can now focus on computational thinking—the ability to break down complex problems, recognize patterns, and design logical solutions using technology. Builders can outsource the burdensome cognitive load of coding to software, allowing them to stay focused on the bigger picture.
The data privacy risks
The rise of vibe coding could lead to substantial data privacy risks. We might be at the dawn of an explosion of software created by individuals that lacks proper security protocols and data privacy settings. As we observed with 23andMe (by no means a small or vibe-coded company), the bankruptcy of a company could expose users to losing control of their data or it being sold.
Building a robust data privacy infrastructure is more complicated than vibe coding a website. As the number of solopreneur vibe-coded tools grows exponentially, so too could the gaps and vulnerabilities around data privacy and security.
// The risks of cognitive offloading
Tools that democratize access and accelerate development can also encourage us to hand over too much of our thinking to machines.In a July newsletter, we explored the implications of “cognitive offloading” when leaning on AI to do too much of our thinking for us. A similar disengagement occurs when AI tools handle the heavy lifting in the coding process.
Lisa Barceló, a staff data scientist at Gusto, a payroll software company, is one of the top users of Cursor on the data team.
“It’s a difficult balance to strike between what to offload and what to hold tightly,” she said. “There’s a temptation to outsource too much work to AI tools. But when we do, we abdicate our role as strategists and true data scientists.”
// The human role in building technology
With tools that help us to outsource the technical work to AI, how should the education of technologists like software engineers and data scientists change?
At the University of Washington, the curriculum is already evolving. Magdalena Balazinska, head of the Paul G. Allen School of Computer Science & Engineering, put it starkly:
