galsapir

We're evaluating agent frameworks for a health AI product and leaning toward Anthropic's Claude Agent SDK. Did a quick POC and liked the simplicity: clean @tool decorator, native MCP support, flat mental model. But I'm finding fewer production case studies compared to LangGraph or similar. Curious about:

Multi-turn conversation handling, does it manage state well or do you thread history manually? Long-running tasks (minutes/hours), any gotchas with timeouts or checkpointing? The latency overhead people mention (~12s per query per one github issue). is this still an issue or has it improved? General production rough edges we should know about?

For context: most of our context is pre-computed, occasional JIT tool calls. Comparing against Pydantic AI and LangGraph but trying to avoid over-engineering. Appreciate any war stories.