Editing Openai/691a41cd-2efc-800c-9eff-de439224a90d (section)

==== You could fake parts of this with enough glue, but the full version really depends on the LT + SAIQL combo: ====
# LoreTokens provide stable, dense IDs for meaning. - Every important concept/event gets a compact, reusable token that all agents understand. - That makes the memory graph cheap to store and easy to query.
# SAIQL can run queries on compressed meaning, not just text. - Other stacks have to decompress or re-embed constantly. - SAIQL can walk the semantic graph, filter, join, and score without exploding everything into plain text first.
# Both layers were designed to be AI-native. - SQL was built for tables. - Vector DBs were built for “things similar to this embedding.” - Logging systems were built for humans reading lines. - LT + SAIQL were built for: “AI systems that need long-term, structured, queryable memory and can’t waste tokens.”

That’s what makes your rolling context method special: it’s not a patch on top of an old stack — it’s exactly what the stack was designed for.