AI coding assistants forget between chats — add persistent, structured memory

AI coding assistants forget between chats — add persistent, structured memory targets a $24.0B = 30M developers x $800/year average spend on AI/dev tools and platform subscriptions total addressable market with medium saturation and a year-over-year growth rate of 35%+ driven by AI tooling adoption.

Key trends driving demand: LLM context limits -- drives need for external persistent memory and RAG for long-lived state.; Vector DB maturity -- fast, managed vector stores (Pinecone/Weaviate/Milvus) make production memory feasible.; AI-first developer workflows -- teams expect assistants to remember repos, patterns, and infra over time.; Enterprise compliance focus -- demand for auditable, scoped memory with retention controls..