@Col_ASY Great question. Compression is a side effect. The objective is to preserve semantic structure so the artifact can be reused across sessions and multi-agent workflows.
Try the examples in the repo with your favo LLM—I’d love to hear where it works well & where it breaks.
Most AI workflows waste tokens re-reading the same documents.
I built shorthand-mem: a compact, AI-native format for turning PRDs and BRDs into reusable memory artifacts.
Early results: 60–85% compression.
https://t.co/G51ezfh6sN
Example:
PRD: "Customers should be charged only once for duplicate usage events. Processing latency must remain below 50ms"
shorthand-mem:
REQ: max_latency<50ms
RULE: duplicate_event→drop
OBJ: usage_billing_pipeline
This can be applied to entire PRDs, arch docs, and workflows
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