Video 10 [12:26]: Managing Risks in Vibe Coding

  1.  Module 4: Introduction and Instructions (Completed)
  2.  Video 1 [03:56]: Module Introduction (Completed)
  3.  Reading: Vibe Coding (Completed)
  4.  Video 2 [04:21]: Introduction to Vibe Coding (Completed)
  5.  Video 3 [03:59]: Vibe Coding Applications: Demo (Completed)
  6.  Video 4 [01:33]: Steps in Vibe Coding (Completed)
  7.  Video 5 [07:32]: Building Your First App: Demo (Completed)
  8.  Video 6 [04:36]: Create Data Dashboards: Demo (Completed)
  9.  Video 7 [06:02]: Apps for Vibe Coding (Completed)
  10.  Video 8 [10:24]: Separating Hype from Reality (Completed)
  11.  Video 9 [03:51]: AI Strengths vs Limits (Completed)
  12.  Self-Study Quiz 4.1: Think & Apply💡Separating Hype from Reality ((Must submit the Quiz))
  13.  Reading: Fast to Build, Ready to Deploy (Completed)
  14.  Self-Study Quiz 4.2: Think & Apply💡 Executive Judgement and Risk Evaluation ((Must submit the Quiz))
  15.  Video 10 [12:26]: Managing Risks in Vibe Coding (Completed)
  16.  Self-Study Assignment 4.3: Think & Act 💡Selecting the Right Tool for the Right Problem ((Must view in order to complete this module item))
  17.  Video 11 [03:19]: Final Thoughts ((Must view in order to complete this module item))
  19.  Discussion Board 4.5: Think & Share 💡The Deployment Decision ((Not yet completed))
  20.  Summary and Video Transcripts: Module 4 ⭐ ((Must view in order to complete this module item))
  21.  Professor Ian's Recommendation for Further Learning: Module 4 ((Must view in order to complete this module item))
  22.  Module 4: Q&A Discussion Board ((Not yet completed))
  23.  Module 4: Feedback Survey ((Must submit the Quiz))

In this video, Prof Ian examines the key risks associated with Vibe Coding, including false confidence, weak security, poor architecture, scalability challenges, integration failures and issues of accountability. He outlines practical best practices for mitigating these risks, emphasising the importance of thorough testing, cybersecurity, documentation, continuous monitoring and responsible stewardship of AI-generated solutions. Prof Ian shares best practices for responsible Vibe Coding, emphasising the importance of defining problems clearly, validating AI outputs, protecting data and continuously improving applications. He explains that clear requirements also reduce unnecessary compute—for example, building only the features users need instead of repeatedly generating and rebuilding unused functionality—making solutions more efficient, reliable and sustainable.