Agent memory is still an unsolved problem. Most work on memory falls into one of three buckets: 1. RAG against a static corpus 2. Agentic RAG - a tool call to retrieve from dynamic memory 3. Better indexing for either of the above But none of these are how human memory actually works. Human memory isn't a slow-moving corpus. It's fast-changing. And critically, we don't *fetch* memories by posing carefully curated queries. Subconscious association surfaces the right context at the right time, automatically. Imagine a coworker who acknowledges something you said, then forgets it 30 seconds later. It'd feel broken. Yet that's exactly how most agents behave today. The hard problems few people are talking about: fast-changing memory that stays coherent, and associative retrieval that doesn't require the agent to "know what to look for." This is what we're working on at Run. If these problems interest you, we're hiring.