docs: add ADRs and user stories for real model inference stack (US-011–014)
ADR-0008: binary activation wire format — raw bfloat16 over HTTP, zstd compression,
128-token chunked prefill; replaces base64 JSON (~33% overhead removed).
ADR-0009: coverage-first shard assignment and tracker-as-first-layer-node —
any node serving layers[0..k] becomes the inference entry point for that model;
bin-packing fills all coverage gaps before adding redundancy; tracker issues
LOAD_SHARD/DROP_SHARD rebalance directives; nodes declare VRAM + quantization.
US-011: binary wire format migration
US-012: real PyTorch layer execution (transformers + bitsandbytes, test on GPT-2)
US-013: coverage-first tracker bin-packing with VRAM-aware shard assignment
US-014: tracker-as-node (tracker node serves first layers + handles client requests)
CONTEXT.md: Tracker Node, Coverage Map, Rebalance Directive terms added.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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