Build Hour: Agent Memory Patterns

AI agents don’t just reason — they remember. In this Build Hour, we deep-dive into context engineering techniques that enable agents to maintain short-term and long-term memory, personalize interactions, and operate reliably across long-running workflows.

Emre Okcular (Solutions Architect) covers:
• Why memory matters: stability, personalization, and long-running agent workflows
• Short-term memory patterns: Sessions, context trimming, compaction, summarization
• Long-term memory patterns: state objects, structured notes, memory-as-a-tool
• Architectures: token-aware sessions, state injection strategies, guardrails, and memory triggers
• Live demo: building an end-to-end agent with dynamic short and long term memory
• Best practices: avoiding context poisoning, context burst, context noise and context conflict.
• Live Q&A

👉 Context Engineering Cookbook:
https://cookbook.openai.com/examples/agents_sdk/session_memory /> 👉 OpenAI Agents Python SDK:
https://openai.github.io/openai-agents-python/ /> 👉 Context Summarization with Realtime Cookbook:
https://cookbook.openai.com/examples/context_summarization_with_realtime_api /> 👉 Follow along with the code repo:
https://github.com/openai/build-hours /> 👉 Sign up for upcoming live Build Hours:
https://webinar.openai.com/buildhours/ />
00:00 Context Engineering
10:44 Context Lifecycle Demo
20:13 Context Engineering Techniques
26:49 Reshape + Fit Demo
39:16 Conclusion
42:45 Q&A 🔗 OpenAI


https://www.youtube.com/watch?v=WsGVXiWzTpI&utm_source=dlvr.it&utm_medium=blogger