World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

Solving AI Amnesia: Building "Infinite Memory" for Agents without the RAM

Expanding LLM context windows bankrupts infrastructure. Discover how Memanto.ai moves vector storage out of RAM to grant your autonomous agents infinite, persistent memory without the astronomical costs.

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#1 about 2 min

Cost limitations of continuous memory for autonomous agents

Storing billions of vectors in standard databases causes prohibitive infrastructure costs for long-running processes.

#2 about 1 min

Introducing open source agentic memory with serverless infrastructure

Deploying a serverless vector search backend solves agent amnesia by retaining data across sessions without relying on static context.

#3 about 2 min

Six core principles for building effective agent memory

Designing reliable memory systems requires prioritizing relevant facts, updating stale information, tracking sources, and preventing conflicting data.

#4 about 3 min

Navigating the interactive dashboard and command line interface

Managing history and resolving conflicts visually enables developers to monitor agent states and execute manual retrieval tasks easily.

#5 about 1 min

Integrating persistent memory across various artificial intelligence frameworks

Connecting extended memory capabilities natively into development tools supports continuous histories across diverse workflow frameworks.

#6 about 2 min

Analyzing feature comparisons and state of the art benchmarks

Evaluating semantic ingestion against standard performance metrics demonstrates high recall efficiency compared to alternative storage options.

#7 about 2 min

Engaging with the open source agent memory community

Executing a simple installation command allows developers to initialize persistent memory backends and participate in ecosystem projects.

Matching moments

1:30 min

Empowering autonomous agents with persistent relationship memory architectures

Gal Shubeli

Gal Shubeli · World Congress 2026 Europe

1:15 min

Equipping AI agents with memory and context

Oren Penso

Oren Penso · World Congress 2026 Europe

1:24 min

Designing short-term and long-term memory for intelligent agents

Zaid Zaim

Zaid Zaim +1 · World Congress 2026 Europe

2:36 min

Exploring the core architecture and components of AI agents

Jörg Neumann

Jörg Neumann · World Congress 2025

3:50 min

Autonomously diagnosing delayed memory and performance issues

Daniel Oh

Daniel Oh · World Congress 2026 Europe

1:44 min

Missing standards for identity and memory in AI agents

Raffi Krikorian

Raffi Krikorian · World Congress 2026 Europe

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Upcoming sessions on this topic

World Congress 2026 North America

September 24, 2026 · 10:20–10:50

Stage 5

Vector, Graph, or Key Value? Choosing Your Agent's Memory

Elizabeth Fuentes Leone

AWS - Developer Advocate/SDE, GenAI

Elizabeth Fuentes Leone

World Congress 2026 North America

September 25, 2026 · 16:10–16:40

Stage 3

Building World-Aware Robots with Agent Memory and Context Graphs

Zaid Zaim

Developer Advocate EMEA at Neo4j | Microsoft AI MVP

Zaid Zaim

World Congress 2026 North America

September 24, 2026 · 17:30–18:00

Stage 6

No Single Model to Rule Them All: Building Resilient AI Agents Across Open & Closed LLMs

Emmanuel Acheampong

Senior Manager Developer Relations at Crusoe AI

Emmanuel Acheampong

World Congress 2026 North America

September 23, 2026 · 13:15–15:15

Stage 9

DeepAgents: Build Multi-Agent AI Systems That Actually Work

Anagha Rumade, Anjana Umapathy, Apoorva Jaiswal

Anagha Rumade

Anjana Umapathy

Apoorva Jaiswal

World Congress 2026 North America

September 25, 2026 · 11:40–12:10

Stage 1

Context Engineering: How machines remember and forget

Emre Okcular

Solutions Architect at OpenAI

Emre Okcular

World Congress 2026 North America

September 24, 2026 · 16:10–16:40

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Responsible AI Architecture with Zero Trust Agents

Ashok Prakash

Staff ML Engineer at Apple

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