Your agent just ingested 214KB of server logs. No errors, no warnings, looks like it worked. But the response is garbage. The context window silently overflowed, data got truncated, and your agent confidently answered from incomplete information. Tool outputs have no size limits by default, so one API call can return megabytes. Overflow throws no exception, it just degrades quality, and multi-agent systems multiply the problem as data passes between agents with no size controls. The Memory Pointer Pattern fixes this. Store large tool outputs in agent.state via ToolContext instead of returning them, then hand back a lightweight 52-byte pointer to the stored data. Use invocation_state for shared access across agents in Swarm systems. A live demo compresses 214KB to 52 bytes and runs a 3-agent Swarm processing 145KB+ logs in roughly 14 seconds. You'll walk away with: • A working Memory Pointer implementation using ToolContext and agent.state • Multi-agent state sharing patterns using invocation_state • Techniques for detecting silent context overflow in production • Open-source demo code processing 145KB+ logs across multiple agents

Outline: • The Silent Killer • Memory Pointer Pattern Deep Dive • Multi-Agent State Sharing • Production Patterns • Advanced Techniques and Wrap-Up