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Automation Vibes Weekly #9: Claude Code Case Study Sprint

Turn messy inputs into client-ready deliverables with Claude Code. A case study sprint covering logistics, restaurants, and clinics with prompts, guardrails, and ROI math.

AC

Alex Cinovoj

Founder, TechTide AI

Oct 3, 20258 min read
#claude#n8n#case-study#smb

From Chaos to Client-Ready

Welcome to Automation Vibes Weekly #9! This week, we're running a case study sprint on using Claude Code to transform messy inputs into polished deliverables. You hand it notes or a CSV, and it returns a clean deck, a working spreadsheet, and a polished SOP.

The Pattern That Works

The secret isn't in the AI—it's in the workflow design. Here's the pattern we've refined across dozens of implementations:

  • Input Stage: Accept messy data (notes, CSVs, emails)
  • Processing Stage: Claude Code structures and analyzes
  • Output Stage: Generate multiple deliverable formats
  • Review Stage: Human approval before client delivery
  • Wiring to n8n

    We wire Claude Code outputs to n8n with simple approvals and logs:

    // n8n webhook receives Claude output
    

    const deliverables = $input.all();

    // Route to approval queue

    if (deliverables.requiresReview) {

    return { json: { route: 'approval-queue', data: deliverables }};

    }

    // Auto-deliver if confidence is high

    return { json: { route: 'client-delivery', data: deliverables }};

    Real-World Applications

    Logistics Company

    • Problem: Manual route optimization from driver notes
    • Solution: Claude processes driver feedback, generates optimized schedules
    • Result: 4 hours/week recovered

    Restaurant Chain

    • Problem: Menu updates scattered across 12 locations
    • Solution: Central CSV → formatted menus for all locations
    • Result: Menu updates in minutes, not days

    Medical Clinic

    • Problem: Patient intake forms → billing codes
    • Solution: Automated form processing with compliance checks
    • Result: 71% reduction in processing time

    ROI Math That Matters

    For every implementation, we track:

    • Time Recovered: Hours saved per week
    • Error Reduction: Mistakes caught by automation
    • Throughput Increase: Volume handled without adding staff

    The typical SMB sees ROI within 30 days.

    Your Takeaway

    Start with one messy input you deal with weekly. Build the Claude Code prompt, wire it to n8n for logging, and measure the results. Ship week one, optimize week two. This is adapted from the TechTide AI Newsletter. Subscribe at techtideai.beehiiv.com for weekly automation insights.

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