Live wireframing: lean BI using AI
summary
Claims a wireframe loop cuts dashboard rework and iteration cost by 100x cheaper and replaces guesswork with a six-step, repeatable process that uses LLMs to run structured stakeholder interviews, merge notes into a DRD, evaluate completeness, generate a compact dashboard spec, pick chart representations and render grayscale wireframes. Demos use ChatGPT/Claude/Gemini/Ollama, handle large token blobs (examples hit ~235,000 tokens), produce editable wireframes and a repo of master prompts that mostly works despite rendering limits.
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chapters (16)
- 0:00Introduction to live wireframing
- 2:26What is live wireframing?
- 10:20The BI iceberg problem
- 20:15Lean BI process overview
- 27:36Setting up AI tools
- 37:53Master prompt breakdown
- 55:53Input evaluation step
- 1:06:24Dashboard requirement document
- 1:16:11Dashboard specification
- 1:23:27Choosing chart representations
- 1:32:46Layout and component mapping
- 1:57:59Rendering the wireframe
- 2:20:11Optimizing prompts
- 2:36:56Final wireframe walkthrough
- 2:43:04Scoring and feedback
- 2:50:13Future of lean BI
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