What context graph and memory architecture is practical?
Why This Question Matters
The conference graph repeatedly asks how agents should retrieve, preserve, update, and reason over context without stuffing everything into a prompt.
Current Working Answer
This page is a first-pass research question, not a final recommendation. Use the linked evidence to refine the answer as more exact session recordings, transcripts, and reviewed slide readings become available.
Source Evidence
- agent memory — Topic synthesis
- agentic search — Topic synthesis
- autoresearch — Topic synthesis
- neo4j — Tool inventory
- zep — Tool inventory
- graphrag — Tool inventory
- 2026 06 29 louis fran ois bouchard context engineering in 2026 compaction memory and cost — Official schedule
- 2026 06 30 gil feig why your company needs a context graph and how to build it — Official schedule
- 2026 06 30 prukalpa sankar wtf is the context layer the missing infrastructure for production agents — Official schedule
- 2026 06 30 stefania druga memory harnesses for long running research agents — Official schedule
- youtube 4sX_He5c4sI — YouTube resource
- youtube 4sX_He5c4sI slides — Slide/OCR evidence
- youtube B9h9ovW5H9U slides — Slide/OCR evidence
Follow-Up
- Extract specific claims from the linked source pages.
- Separate official schedule evidence from supporting YouTube, transcript, and OCR evidence.
- Convert stable answers into playbooks, harnesses, or evaluations where appropriate.