TB.
01 / FIELD NOTES

Triet
Bui

Tech Lead AI Systems Builder

I turn factory problems
into working systems.

AIComputer VisionAutomationRFIDCustom Web Apps

Self-taught.
Systems-minded.
Results-first.

I learned technology by staying close to real problems—and refusing to accept “that's how it has always worked.”

My work sits where software, hardware, AI and people meet. I move from observation to prototype quickly, then turn what works into systems that teams can operate, improve and own.

Today I lead builders across software and automation while remaining hands-on enough to challenge architecture, assumptions and outcomes.

2016ONE BUILDER

Started by solving the next useful problem.

TODAYTECH LEAD

Building teams and systems across real operations.

NEXTAI-NATIVE WORK

Making intelligence a practical operating layer.

Work that crosses boundaries.

Software is only one layer. The outcome comes from connecting process, data, devices, intelligence and ownership.

/ 01

Enterprise AI Vision

Multi-camera computer vision that turns noisy visual signals into clear operational decisions.

OpenCVYOLOVision LLMEdge AI
/ 02

Internal Work Platforms

Approval, visitor, access and action systems shaped around how factory teams actually work.

LaravelNuxtPostgreSQLWorkflow
/ 03

Private LLM Gateway

A local-first AI layer for translation, knowledge, governance and practical internal agents.

LiteLLMOllamaRAGGuardrails
/ 04

RFID & Connected Operations

RFID, Android and automation tools that connect physical work with reliable digital records.

UHF RFIDAndroidIoTAutomation

First principles, applied.

My default is not “add more.” It is to find the constraint, remove noise and build the smallest loop that creates learning.

01

Observe the real work

The useful requirement is rarely the first request. Watch the bottleneck, the workaround and the human cost.

02

Build the smallest system

Reduce the idea until one small release can prove or kill the most important assumption.

03

Measure useful impact

A system is done when the work becomes clearer, safer or faster—not when the presentation looks complete.

Bring me the
hard problem.

I am interested in practical AI, factory systems, automation, technical leadership and ideas that look slightly impossible at first.

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