Building ShouldWeAutomate: A Decision Intelligence Platform for Workflow Automation

Harish Kotra (he/him) Posted on May 30 Building ShouldWeAutomate: A Decision Intelligence Platform for Workflow Automation # ai # programming # python # dailybuild2026 How we built an open-source platform that tells you whether your business process is ready for AI automation — with deterministic scoring, gamified UX, and optional LLM inference. The Problem Every week, someone asks: "Can we automate this workflow?" The answer is never simple. It depends on data quality, process stability, regulatory exposure, exception rates, integration readiness, decision complexity, and ROI potential — seven dimensions that interact in non-obvious ways. Most automation decisions are made on gut feel. Teams spend months building automation only to discover the process changes too frequently, the data is too messy, or the compliance team blocks it. We wanted to build a tool that makes this evaluation systematic, data-driven, and interactive — something a team can open in a browser, describe their workflow, and get a defensible answer in seconds. The Architecture Frontend Single-page Flask application rendered server-side with Jinja2 templates. The frontend is vanilla JavaScript with Chart.js for the radar visualization and a custom SVG gauge for the overall score. Key design decisions: No build step. No webpack, no React, no npm. Pure HTML/CSS/JS. Zero friction for contributors. Gamified sliders. Instead of 35 individual range inputs (5 questions × 7 dimensions), we show 7 aggregate dimension sliders with tier badges — Critical → Bronze → Silver → Gold → Mythic. Click "Fine-tune" to expand the 5 sub-questions. Live preview. A mini gauge and recommendation badge update in real-time as sliders move. Users see their score change before they click "Analyze." // Core rendering — dimension cards with aggregate + fine-tune function createDimSection ( key , dim , prefix ) { const aggDefault = Math . round ( dim . questions . reduce (( s , q ) => s + q . default , 0 ) / dim . questions .