[FEATURE]: Implement Ultra-Fast Bitmask Snapshot Compression Layer for In-Memory State Buffers

Problem

Caching multi-gigabyte agent memory context bit arrays continuously into in-memory ring buffers creates massive memory pressure and triggers sudden user-space OOM-kill exceptions under massive multi-tenant scale boundaries.

Proposed Solution

Develop a zero-copy context compression layer under internal/storage/compressor.go:

1. The Line-Rate Bitmask Zipper: Integrate a low-overhead run-length encoding (RLE) bit manipulation algorithm designed to snip and squeeze active transaction state matrices on-the-fly inside host registers without hitting heavy memory heap bounds.
2. Parallel Cache Splicing: Chunk the compressed bytes natively into lock-free atomic block stores, reducing overall physical memory footprint delta by over 65% cleanly.

Use Case

Unlocks direct sales pipelines inside massive enterprise segments, ensuring that clusters can operate seamlessly without requiring explosive hardware storage budgets.

Start by reading internal/storage/compressor.go and tracing how in-memory ring buffers store agent context bit arrays. Clarify the existing buffer and concurrency interfaces before designing the RLE and lock-free block-storage approach. Done should mean the compression layer is integrated and demonstrates the requested reduction in physical memory footprint without the stated OOM pressure.