Using Vibe Coding in Real Data Projects

In this episode, the team gets hands-on with vibe coding and what it actually looks like inside real data work. From building API connections to generating synthetic datasets, they walk through where AI is genuinely speeding things up and where it still runs into friction. The big takeaway: writing code might be faster, but everything around the data still matters just as much. Key Moments: 01:30 Early experiments with AI in data workflows 02:15 Building API connections and pipeline setup 03:45 Teaching AI your standards and best practices 05:00 Why API documentation is still a bottleneck 06:20 The hidden work around data access and permissions 07:00 How AI coding tools have improved (and where they still break) 08:30 Using AI to query data and support decision-making 10:00 Creating synthetic datasets for demos 11:30 When AI-generated data goes wrong 12:50 Building dynamic data generation and testing outputs 14:30 Debugging, iteration, and working with AI 15:45 What’s next: templates, efficiency, and automation 17:00 The future of AI in data engineering workflows Blue Margin helps growing companies make better decisions with their data. From building data pipelines to creating reporting and dashboards, we handle the technical side so teams can focus on using their data—not chasing it.