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