Facts as First Class Objects: Knowledge Objects for Persistent LLM Memory
Large language models increasingly serve as persistent knowledge workers, with in-context memory - facts stored in the prompt - as the default strategy. We benchmark in-context memory against Knowledge Objects (KOs), discrete hash-addressed tuples with O(1) retrieval. Within the context window, Claude Sonnet 4.5 achieves 100% exact-match accuracy from 10 to 7,000 facts (97.5% of its 200K window). However, production deployment reveals three failure modes: capacity limits (prompts overflow at 8,000 facts), compaction loss (summarization destroys 60% of facts), and goal drift (cascading compaction erodes 54% of project constraints while the model continues with full confidence). KOs achieve...
| Authors | Oliver Zahn, Simran Chana |
|---|---|
| Primary category | cs.AI |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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