Turning industrial
complexity into
streamlined intelligence.
I build agentic systems that make manufacturing data actually useful — and write about it every week. I also built a game that lives inside a PCB, because why not.
Recent writing
The Model Finds the Defect. The Standard Decides What It Means.
A local YOLOv8 + offline LLM pipeline that maps PCB defects to the right IPC standard and process cause, plus the regex firewall that keeps bare-board and assembly domains from blending, and the recall floor it never beat.
The Co-Pilot That Refuses to Guess: Grounded RAG for PCBA Test Logs
A synthetic PCBA test-log pipeline, SPC that runs itself, and a citation-forced RAG co-pilot that refuses to answer when it isn't sure — built over eight weeks of evenings and weekends.
The Tool Was Never the Point: A 12-Step Workflow for AI-Native Projects
I built an AI co-pilot for PCBA test analytics to fill a portfolio gap. The tool became the least interesting thing I made. The real deliverable was the 12-step workflow I used to govern the agents that built it.
Stop Applying Tape: RCCA in Agentic Debugging
AI agents are good at finding something that works. They are terrible at finding out why something broke. That is a discipline problem — and manufacturing solved it sixty years ago.
The Hidden Tax on Your AI: Context Windows, Skills, and the Cost of Attention
Every skill you load, every message you send, every document you attach quietly eats into the same fixed budget. Here's what happens when that budget runs out — and how to spend it wisely.
Running Multiple AI Agents in Parallel Without Destroying Your Codebase
Two AI agents writing to the same file simultaneously is a data corruption event. Here is the file-locking orchestration layer that makes parallel AI development safe and fast.
// arcade · built for this portfolio
I built a game.
You are a signal packet navigating copper traces on a live PCB board. Collect every solder joint to clear the board — but four rogue AI agents are hunting you, each level smarter than the last. It's Pac-Man if Pac-Man cared about manufacturing.
// enemy roster
Through a cinematic lens
// about
Manufacturing Engineer.
AI-Native Builder.
Photographer.
With a backbone in Electrical Engineering from SUNY Buffalo (2023) and an M.S. in IT Management from Belhaven University (2025), I specialize in the intersection of hardware precision and intelligent software. My journey started at the Bharath Institute of Higher Education and Research, and today I work as a Manufacturing Engineer designing automated workflows that actually make sense for the people using them.
For me, engineering is about solving complex problems with simple, human-focused solutions. When I'm not building tools, I'm usually behind my camera capturing stories through a cinematic lens. You can find more details in my resume or by browsing my projects below.