Paul Nguyen

Paul Nguyen

Applied AI Engineer — Safety-Critical AI Products | Building Autodidact (local-first agent that learns) | PhD (Adversarial ML & Security)

Building AI agents using LangChain

less than 1 minute read

Published:

LangChain

An open-source framework to help build applications powered by language models

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Stop Training Your LLM Router: Zero-Shot Confidence Beats Supervised Baselines

5 minute read

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TL;DR: We tested whether you actually need labeled training data to route queries between a cheap local LLM and an expensive cloud model. You don’t. Average token log-probability — available for free from the first query — matches supervised routing in-distribution and crushes it when the query distribution shifts. We tested across 3 model families, 2 datasets, ~4,500 queries, and $123 in cloud costs. All code and data are open.

What Automotive AI Taught Me About Responsible Deployment

9 minute read

Published:

When you ship AI into a vehicle, the consequences of failure aren’t abstract. They’re not a bad user review or a dip in engagement metrics. They’re a driver who takes their eyes off the road because the system said something confidently wrong, or a voice assistant that crashes mid-navigation and leaves someone lost on an unfamiliar highway. Shipping AI where failures have physical consequences changes how you think about deployment — permanently.

AI Agents: Buzzword or Paradigm Shift?

less than 1 minute read

Published:

“AI agent”—a fancy buzzword for AI model integration, or is there more to it? With increasing autonomy and decision-making capabilities, are we just rebranding models, or is this a true paradigm shift?