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QCG Racing · AI Infrastructure

We didn’t adopt AI.
We built with it.

Three AI programs running inside the race program. Each one has real stakes — if the AI Crew Chief gives a wrong pit signal, we lose track position we can’t recover. That’s why we built the override architecture first.

01
Engineering · Build Phase · Underway

The engine the simulation helps build.

The 5.7L Dodge engine program uses AI simulation integrated from the design phase — not as a validation tool after the fact, but as a design partner from the first sketch. The simulation models combustion dynamics, thermal loads, and power delivery curves before any metal is cut. When the physical build diverges from the model — and it does — the divergence is the data we learn from.

What this is not: a marketing claim about AI. It is a specific simulation architecture running on specific dyno data, producing specific predictions that are checked against specific physical outcomes. The failure rate of the model is published in the shop updates. The learning compounds.

Status: Build phase · Engine assembly underway · First full dyno cycle targeted Q2 2026
AI LAYER       Combustion + thermal simulation
PLATFORM       Custom 5.7L Dodge V8
MODEL VER      v0.2 · Updated monthly
DIVERGENCE     Published in shop updates
DATA SOURCE    Dyno telemetry (live integration)
02

Procurement, publishing workflow, research pipeline, scheduling, communication — every back-office function in QCG runs through an AI operations layer. This is not interesting because it's innovative. It's interesting because it works, it's documented, and it demonstrates what a zero-waste organizational architecture looks like when you build with AI from the foundation.

The QCG Academy educational modules teach from this system. Interns don't study AI in theory — they operate inside a real AI-integrated organization and observe where it works and where a human has to step in.

Status: Operational · Documented · Used as curriculum case study in QCG Academy Module 02

A crew chief makes forty or more split-second decisions per race. Pit timing. Fuel strategy. Tire management. Caution responses. The AI Crew Chief is a real-time decision-support system that processes telemetry, historical track data, competitor positions, and fuel/tire models to surface the optimal decision at each decision point.

The human crew chief is in command. The AI does not make the call — it surfaces the information in a format that allows the human to make the call faster and with more complete data. The override architecture was the first thing we built. That's not a limitation — that's the design.

What the system doesn't do: It does not predict tire failures. It does not account for incidents it hasn't seen. It does not override the crew chief. When the model is uncertain, it says so.

Status: v0.1 · First live data run completed February 2026 · Training on 2025 CARS Tour season data