{"slug":"memory-retrieval","label":"Memory Retrieval","item_count":3,"day_count":3,"source_count":3,"first_seen":"2026-10-17T05:12:34+00:00","last_updated":"2026-10-29T17:37:21+00:00","generated_at":"2026-10-31T00:13:50.114893+00:00","sources":["arxiv_cs_ai","hackernews_ai","langchain_blog"],"days":[{"date":"2026-10-17","items":[{"title":"EPGM: Execution Provenance for Budgeted Agent Memory Retrieval","url":"https://arxiv.org/abs/2609.25913","source":"hackernews_ai","type":"paper","summary_1line":"EPGM: Execution Provenance for Budgeted Agent Memory Retrieval","why_it_matters":"Matches feed focus: agent, eval.","sid":"cbef01ba5cb1e9c5","published":"2026-10-17T05:12:34+00:00","editor_note":"Frames memory retrieval as a budgeted problem with execution provenance."}]},{"date":"2026-10-23","items":[{"title":"Context Engineering (Agent Memory) for AI Agents Starts with Retrieval","url":"https://www.langchain.com/blog/context-engineering-starts-with-retrieval","source":"langchain_blog","type":"news","summary_1line":"Agents waste time and context on clumsy searches, oversized results and stale data. Learn the retrieval techniques LangChain's Deep Agents harness uses to get the right context in.","why_it_matters":"Matches feed focus: agent, harness, eval.","sid":"b0133c74d1515b7b","published":"2026-10-23T17:00:00+00:00","editor_note":"Practitioner view from LangChain's Deep Agents on failures such as clumsy searches and stale data."}]},{"date":"2026-10-29","items":[{"title":"Retrieval as Traversal: Value-Indexed Memory for Stateful Long-Context Agents","url":"http://arxiv.org/abs/2610.40545v1","source":"arxiv_cs_ai","type":"paper","summary_1line":"Long-context models repeatedly solve closely related retrieval problems. Attention or global retrieval can retain large stores, but each forward pass again searches for what matters. Recurrent compression avoids this...","why_it_matters":"Matches feed focus: agent, eval.","sid":"29a5435531059481","published":"2026-10-29T17:37:21+00:00","editor_note":"Proposes indexing memory by value so retrieval is traversal rather than a fresh search each pass."}]}],"editorial":{"tldr":"An Oct 17 paper (EPGM) proposed tracking execution provenance so agent memory retrieval stays within a budget. On Oct 23 LangChain described the retrieval techniques its Deep Agents harness uses against clumsy searches, oversized results and stale data.","stale":false,"whats_new":"Oct 29: \"Retrieval as Traversal\" proposes value-indexed memory so long-context agents stop re-searching for what matters on every forward pass.","why_it_matters":"Agent memory is shifting from bigger stores to cheaper retrieval: provenance, result sizing and indexing decide context cost and staleness.","take_for_builders":"Audit your agent's retrieval for oversized results and stale data, and log which memory entries each answer used; treat the papers as research until code appears.","status":{"state":"Developing · research","tone":"rising","changed":"2026-10-29","detail":"Two arXiv papers and one LangChain engineering post in 12 days; only LangChain's describes a shipped harness."},"beats":[{"kicker":"PROVENANCE","tone":"launch","headline":"EPGM adds execution provenance to budgeted agent memory retrieval","sids":["cbef01ba5cb1e9c5"]},{"kicker":"PRACTICE","tone":"rising","headline":"LangChain: context engineering for agents starts with retrieval","sids":["b0133c74d1515b7b"]},{"kicker":"NOW","tone":"now","headline":"Value-indexed memory recasts retrieval as traversal","sids":["29a5435531059481"]}],"open_questions":["Do EPGM or the value-indexed memory paper release code or numbers on production agent workloads?","Does LangChain publish measurements of its retrieval techniques in Deep Agents?"],"generated_at":"2026-10-31T00:13:38Z"}}