Inspect the House, Not the Neighborhood: What Actually Makes an AI Model Risky
Asked whether the company uses Chinese AI, most teams lack a clean answer, and a country-of-origin ban says little about what actually makes a model risky. Nicky Pike, Field CTO (Americas) at Coder, proposes inspecting the model as a house in three layers: the wiring (what was baked in during training, including research-demonstrated backdoors), the contractor (what model files and setup scripts can run when loaded, including confirmed malicious models on public hubs), and the doors (what data can leave and what an agent is allowed to do). He sets out practical steps for pulling from public hubs, shows where bans fit and where they do not, and describes how Coder routes every agent through workspaces and one gateway so a model can be shut off or swapped. Attendees will leave with a way to answer, for one model, everywhere it runs.
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