Course:ELEC300E/CaseStudies/VibeCoding
Context: Software Jobs
| Vibe Coding |
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| Content / Topics |
| Grief Bots |
| AI Chatbots |
| AI Ethics |
| Relevant Analysis Strategies or Tools |
| Decision Impact Assessment |
| Plutchik's Wheel |
| Needs Analysis |
The advent of widespread generative AI has had a pronounced and measurable impact on entry level software jobs.
Stanford's AI Index shows a steady decrease in the number of entry-level software development jobs: a decrease of nearly 20% since 2024. The labour market impacts are attributed directly to Generative AI, with research showing that software development jobs that can be automated with AI have declined the most.
These impacts don't apply to all industries, or even senior software developer roles - they disproportionally impact entry-level software developers specifically, although as AI capabilities advance, more positions may be impacted. In a longer Stanford research paper on these changes to the labour market, entry-level software engineers are compared to the 'canary in the coal mine':
Historically, technologies have affected different tasks, occupations, and industries in different ways, replacing work in some, augmenting others, and transforming still others. These heterogeneous effects suggest that there may be “canaries in the coal mine” which are harbingers of more widespread effects of AI.
Case: Vibe Coding
Vibe coding is essentially prompting AI tools to create apps or software based on natural language descriptions. The term was coined by OpenAI cofounder Andrej Karpathy:
"There's a new kind of coding I call 'vibe coding,' where you fully give in to the vibes, embrace exponentials, and forget that the code even exists,"
A CBC radio show, discusses how people around Canada are developing apps and technologies using vibe coding. One example is a vibe-coded recipe site that included recipes for cocaine, 'cyanide ice cream' and 'cholera cake'.
As the podcast explains, today, many new businesses use exclusively 'vibe coded' software, instead of relying on professional software developers. Vibe coding allows the every day person to make creative new apps and tools, democratizing the software development process. It also helps developers create software faster, and to quickly build and iterate on prototypes.
This new automated software development process also leads to security risks though. Without experienced developers reading, understanding and testing code, "more lines of code that have never been checked by a human may creep into our collective technological backdrop".
Recommended Readings
- 22 minute podcast, "The AI website that told people how to make cocaine": https://www.cbc.ca/player/play/audio/9.6745902
- Or read this article (10 minutes): https://www.cbc.ca/radio/thecurrent/vibe-coding-cyanide-ice-cream-1.7531196
Discussion Questions
Here are a few questions to help you begin analyzing the issues discussed in this case study. The purpose of these questions is to prompt reflection and further consideration: there are no right or wrong answers!
- Emotional Responses: Take stock of your immediate response to this case study? How might your unique personal experiences and perspectives inform this response?
- Contradictory viewpoints and outcomes: Consider the perspective of two potential stakeholders on vibecoding. Stakeholders might include a small business owner who is looking to develop an app for their company, a new software engineer graduate who is looking for a job, an AI company like ChatGPT, or a member of the general public who wants a fun and safe experience online. Which priorities and needs are in conflict?
- Positive action: What is one hopeful takeaway from this article, or a potential positive outcome? How can you contribute to this positive change?
- Interruptions and invitations: AI is certainly interrupting the traditional software engineering industry. Some would say that vibe coding is 'democratizing' software development. Would you agree with that assessment? Is vibe coding democratizing software development, or concentrating power with specific companies, industries or stakeholders?
- Physical connections: As an engineering student, you might feel personally invested in this case study. Working in this quickly changing context requires acceptance of ambiguity and uncertainty. What strategies can you use personally to manage feelings of stress, ambiguity and uncertainty in the face of a changing software engineering industry?
- Social and Historical Context: Some have compared the advent of widespread AI (and its impacts on the labour market) to the Industrial Revolution. What similarities do you see? What might be different?
- Positive Practices: What is one concrete action that you could take, or a practice that you could adopt in your personal, academic or professional life in response to this case study?