Lesson 628 of 1596
Multi-Turn Conversation Design: Memory, State, and Sessions
Single-turn prompts are easy. Multi-turn conversations require thinking about state, summary, and what to surface back to the model — design choices that determine whether the conversation stays coherent.
Creators · Prompting · ~24 min read
The premise
Multi-turn AI applications are not single-turn applications repeated; they require explicit state design that doesn't come from prompting alone.
What AI does well here
- Design what the model needs to remember vs. what your code tracks separately
- Implement summarization checkpoints so context doesn't bloat unboundedly
- Choose context-window strategies (rolling window, summary + recent, structured state) based on use case
- Build conversation reset triggers (new topic, error recovery, user request)
What AI cannot do
- Get unlimited memory by stuffing context (degrades performance and costs)
- Substitute for actual database state (the model is bad at being a database)
- Replace user-facing controls for managing conversation history
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