ML Lead · AI Architect · Edge & Cloud
I build AI that ships — from the edge to the cloud.
On-device inference where privacy and latency decide it; scalable cloud serving where reach and throughput do. Architected on the economics, not the hype — and shipped as open-source tools engineers worldwide actually run.
- Flagship OSSAnyLabeling3.4k★
- FocusEdge ↔ Cloud AIinference economics
- LabNeural Research Lab@nrl ↗
- ShippingSince 2016open-source by default
- 70+
- Blog Posts
- 25+
- Projects
- 5K+
- GitHub Stars
- 8+
- Years Coding
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Local-first AI, AI security, on-device Vietnamese voice, and what I am shipping next.
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I gave my website tools for AI agents with WebMCP — and thought hard about the attack surface
WebMCP lets a web page hand callable tools to browser AI agents instead of making them scrape the DOM. I wired three read-only tools into this site. The interesting part was not the API — it was deciding what an agent, or a prompt injection riding one, is allowed to do.
The Bottleneck Moved to Review: My SDLC After AI Writes Most of the Code
When a machine writes most of your diff, the constraint stops being how fast you type and becomes how well you review. Here is the SDLC I actually run — the provenance audit, the sandbox, the CI backstops, and the three questions I ask every AI-authored change — plus the parts of review that don't compress and never will.
Plan Once, Then Act: When the ReAct Loop Is the Wrong Harness for Small Local Models
On small local models, the standard ReAct loop has a failure mode nobody warns you about: the model calls one tool, declares victory, and stops. What we measured across 12 GGUF models in EdgeVox, why we added a plan-once dispatcher, and how to decide which loop your task actually needs.
Building EdgeVox: Chaining STT → Local LLM → TTS Without Touching the Cloud
A first-hand build narrative of EdgeVox — a fully offline voice agent that chains speech-to-text, a local LLM, and text-to-speech on one device. The architecture in plain language, ROS2 integration, the latency budget, and the failure modes nobody warns you about.
I put an AI version of myself online, then tried to break it
Building a represent-me chatbot is a weekend project. Treating it like a production security surface is the part nobody writes about. Here is the architecture, the prompt leak I found by attacking my own bot, and the reusable suite that keeps it honest.
Vietnam's Sovereign AI Conversation Is Stuck One Layer Too High 🇻🇳
Vietnam already has the chips, three meaningful Vietnamese model attempts in flight, and the most binding AI law in Southeast Asia. The conversation about sovereign AI keeps demanding a 70B foundation model. The actual gap is one layer down — open evaluation, license-clean data, compliance-aware specialized models, and on-device runtimes that operationalize Law 134/2025 starting March 2026.