Build Hour: Agent Memory Patterns

Original Description

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