Two AI21 engineers, Yuval Belfer and Asaf Gardin, detailed two production bugs in vLLM that produced confidently wrong model output with no crash, no warning, and no error, both around the Mamba state cache in AI21's Jamba hybrid model and both found through log-probability forensics rather than conventional debugging. Belfer framed these as engineering problems where the model has high confidence but bad output, with a silent failure mode offering no signal to alert on. The first bug, the "imposter request," surfaced during GRPO on Jamba and occurred in roughly 1 in 1,000 requests, only in vLLM, and required sustained workload. Gardin reproduced it by reducing the GPU memory utilization flag from 90% to 20% and firing many simultaneous requests, at which point request number 8,854 returned gibberish; sampling all batches at temperature zero made the failure deterministic. Hugging Face Transformers served as a baseline because it holds a "very vanilla and plain implementation" of the Mamba kernels, with the comparison methodology running prompts through vLLM's generate, capturing responses and log probs, then running the full sequence through Hugging Face's forward pass.