Vibe Analytics: Vibe Coding’s New Cousin Unlocks Insights
The Excel spreadsheet era asked, “What happened?” The dashboard era asked, “Why did it happen?” The vibe era asks, “What insights emerge if we explore together?” Consider the gains that real-world companies are already making.
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Traditional data analysis looks like this: Define questions; structure queries; execute models; visualize results. Vibe analytics collapses this chain into an improvisational dialogue with data using generative AI tools, much like vibe coding transforms programming. Instead of waiting for data scientists to produce insights, leaders can engage directly with data sets through conversation — and get insights quickly. Find out how companies have already used this approach and learn what’s required.
Editor’s note: The author used GenAI tools as resources in the process of writing this article.
In February, former Tesla AI director and OpenAI cofounder Andrej Karpathy posted a casual humblebrag on X about his clever weekend coding approach: “There’s a new kind of coding I call ‘vibe coding,’ where you fully give in to the vibes, embrace exponentials, and let LLMs write the code for you.” Karpathy’s hack literally and figuratively has prompted a profound and provocative disruption in software design and development. “It’s not really coding,” he observed. “I just see stuff, say stuff, run stuff, and copy-paste stuff, and it mostly works.” It now seems almost certain that Karpathy’s AI-infused “stuff-ification” will have a significant impact on other forms of knowledge work — especially data-driven analysis.
What vibe coding does for (and to) programming, vibe analytics does for (and with) data. Vibing with structured or unstructured data — comma-separated value (CSV) files, SQL databases, Excel spreadsheets, or transcribed Zooms — can generate empirical insights that neither legacy analytics nor data science are likely to produce. Much like vibe coding transforms programming from syntax to intention, vibe analytics transforms data queries to conversations, and dashboards to jam sessions. In these contexts, vibe describes an alignment between human intent and machine interpretation that emerges through improvisational interaction.
The improvisation evokes and enables actionable insight; insight comes from the data effectively and affectively arguing back. In the spirit of early statistics pioneers (notably, John Tukey and Frederick Mosteller, whose exploratory data analysis approach encouraged data to speak before formal models imposed meaning), vibe analytics pursues value via dynamic interaction — where data engages, responds, and sometimes resists. It’s not just pattern recognition; it’s pattern negotiation.
So where the Excel spreadsheet era asked, “What happened?” and the dashboard era asked, “Why did it happen?” the vibe era — beginning with code but inevitably expanding to data — asks, “What emerges if we explore together?” For executives, this means faster time-to-insight and the democratization of analytical powers: The need to wait days or weeks for data teams to translate business questions into technical queries vanishes. When leaders engage directly with messy/structured/unstructured data through improvised multimodal exploration to surface unexpected patterns and accelerate decision-making, they are innovating out loud.
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Chadi El Rhanmi Karim