💡 From Compatibility Fixes to Full-Field Automation

How one field automation suite turned daily bottlenecks into instant actions.

When your tools start saving you time, you realize you’ve built something bigger than a workaround.

Two months ago, I shared how I rebuilt our Meraki automation tools to run natively on macOS. Since then, I’ve gone deeper — developing a personal suite of Python-based automations that streamline how I work in the field.

Over time, it grew into a compact Meraki Automation & Site Operations Suite — designed to make my workflow faster, cleaner, and easier to document.

What the Suite Handles

  • Pull Network IDs from MX serials instantly
  • Rename switches and APs using Excel-driven templates and API logic
  • Run port health scans before sign-off
  • Use AI logic to read and rename install photos, auto-resizing them for documentation
  • Generate clean Excel photo reports with one click

Everything runs through my Stream Deck Neo, letting me launch scripts with one button — whether at my desk or on-site.

Spotlight: AP Photo Batch Renamer

This video shows one of those automations in action — the AP Photo Batch Renamer, a Python-based AI tool that reads text from AP install photos, guided by a whitelist of approved naming patterns and site identifiers.

It automatically renames each image based on the detected text, resizes it for efficient storage, and outputs a clean, labeled set of photos ready for documentation.

→ Transforms raw install photos into labeled, storage-optimized assets — combining intelligent text detection with rule-based automation to maintain naming integrity and eliminate manual rework.

All of this ties directly into my Stream Deck, where every button triggers a specific automation. The suite covers Network, Switch, Photo, and AP-level automation, each mapped to its own process running quietly in the background.

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The Impact

Faster deployments. Cleaner records. Better visibility.

Each script started as a pain point I faced on-site — and evolved into a workflow that saves time, reduces errors, and raises the documentation standard for every project.

And soon, I’ll be taking it a step further — containerizing these tools in Docker so they can run from the web or any environment, not just my Mac.

Every automation begins as a problem you’re tired of repeating — until you build something that solves it once and for all.