Building an AI Forensic Investigator for Vehicle Failures
I built an AI agent that diagnoses cars — and asks before it touches anything Built for the TrueForge Agent Harness Hackathon (Aug 24–30, 2026). "Something expensive broke. Figure out why and prove it. Ask a human before you touch anything." That was basically the idea behind FaultTrace. I wanted to build something that felt more like an actual investigation than another chatbot with a few tools…
The article describes the development of an AI-powered vehicle diagnostic forensics system called FaultTrace, which was built for the TrueForge Agent Harness Hackathon in August 2026. The system aims to act more like a genuine investigation than a chatbot with a few tools attached.
FaultTrace works by gathering evidence from various vehicle sensors and systems, creating competing root-cause hypotheses, predicting what each hypothesis would look like in the data, running actual analysis in a sandbox, and using Bayesian calculations to rank the hypotheses. The system predicts which additional test would reduce uncertainty the most and stops for human approval before taking any physical action.
The key features highlighted are the autonomous nature of the investigation, the use of deterministic Bayesian calculations for hypothesis ranking, and the system's ability to stop and seek human approval before performing any physical actions. The main distinction from a traditional chatbot is that FaultTrace runs an actual investigation, retrieves evidence from multiple tools, delegates specialized investigation to dynamic subagents, and continuously evaluates and refines its approach based on the observed evidence.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
