Original LinkedIn Post
As a front-line Tableau developer, I ran an experiment that genuinely surprised me. Adam Mico I gave an AI a set of reference materials, let it generate the calculation logic on its own, and watched it produce a complete semi-donut chart ? without me open tableau even writing a single line of code manually. This wasn't about showing off. It was about testing where the boundary of AI actually is. What I've built so far: Implemented CWPrep MCP ? AI reads business requirements and automatically generates Tableau Prep data pipelines AI handles complex visualization end-to-end (the semi-donut chart is just the starting point) My role: design, review, and iterate My core belief: The most valuable hours of a data analyst should not be spent building dashboards. Let AI handle the repetitive, mechanical execution. Human effort should go where human judgment is irreplaceable ? understanding the business, forming hypotheses, validating ideas. My next step is running this on real production data. The end goal: an AI-driven end-to-end dashboard workflow, from data prep to final visualization, with minimal manual intervention. Vibe coding with AI agents is moving faster than I expected. Have you started integrating AI into your analytics workflow?
What's been the biggest friction point? Drop a comment below.
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