Vibe Coding The Canary In The Coal
Source: AI Goes to College
Author: Craig Van Slyke
Original source: https://aigoestocollege.substack.com/p/vibe-coding-the-canary-in-the-coal
Published: 2025-12-10
Source type: essay
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Summary
Craig Van Slyke argues that vibe coding — building software through natural-language collaboration with AI rather than writing code directly — is an early signal of how AI may transform knowledge work. He describes building several personally useful micro-apps despite not having coded in decades, including faculty-oriented task management, time-blocking, and project tracking tools. The central education implication is that higher education should not treat AI as a narrow academic-integrity issue; it should help faculty and students experience AI-enabled work directly because current students are preparing for knowledge-work jobs likely to be reshaped by AI.
Pull quotes
Useful apps without writing code
“And yet, I was able to build fully functional, useful apps … all without writing a single line of code.”
Vibe coding is natural-language software work
“I was engaged in what is commonly known as vibe coding, building software through natural language collaboration with AI rather than writing traditional programming.”
Software is the leading edge
“Why should you care if you’re not in IT? Because this is the leading edge.”
Big ideas
Claims
Key evidence and examples
- Van Slyke built functional micro-apps without writing code by prompting, testing, and iterating with AI.
- The examples are small and practical: task management, time blocking, project tracking, recommendation-letter tracking, assignment feedback banks, paper submission trackers, reading queues, committee meeting prep, and email template libraries.
- He distinguishes novice-facing vibe coding tools from expert developer tools.
- He acknowledges that vibe coding is not currently suitable for complex, large-scale applications and may produce inefficient or lower-quality code.
- He frames software development as the leading edge of broader AI-driven change in knowledge work.
Education relevance
This article is relevant to higher education, AI literacy, faculty development, and workforce preparation. It suggests faculty need firsthand experience with AI-enabled work in order to understand how professional workflows and student career preparation may change.
Durability note
Specific vibe-coding tools will change quickly, but the broader signal—that natural-language AI can shift participation in software and other knowledge work—is the durable takeaway.