Hajer Bouafif
OpenSearch Solutions Architect at Amazon Web Services. Works on Personalization and Agentic Memory in OpenSearch, and presented the memory-based approach to search personalization at Berlin Buzzwords 2026.
Her argument is that personalization has been mis-framed as a ranking-and-feature problem. The question a personalized system should answer is not how do we better rank these results but who is running this query, and why now — and the durable answer to that lives in memory rather than in a retrained feature space. She positions memory as the agent’s “source of intelligence”, complementary to grounding: the catalog tells the agent what exists, the memory tells it what this particular user means.
A second recurring theme is operational discipline around agents. Her production guidance keeps LLM reasoning off the query path entirely — preferences inferred offline, profiles cached, retrieval capped at the top 5–10 facts, a small language model online, and a conventional lexical/k-NN/hybrid fallback always standing by for when the agent is slow or misbehaves.
Talks in this vault
- Hajer Bouafif - Personalize Search Results with OpenSearch Agentic Memory — Berlin Buzzwords 2026; the offline/online pipeline split, OpenSearch’s four memory types, and preference inference from UBI clickstream
Topics
- Agentic Memory · Personalization · Query Rewriting — memory-driven query enrichment
- Conversational and Agentic Search — the broader pattern her work sits in
Related
- Amazon Web Services — employer
- OpenSearch — the engine her work is built on
- User Behavior Insights — the behavioural signal source she feeds into preference inference