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Email agents are not about one message. Real work takes days. You send a demo. A prospect replies. You wait. They reply again.
One email is easy. Long conversations are hard. Your agent must remember what it said. It must know where it stands in the process. It must survive server restarts.
Create a durable record for every thread. Use a database. Save these details:
- Thread ID
- Purpose of the chat
- Current step in the workflow
- Number of turns
The step field acts as a state machine. It tells the agent what to expect next.
Follow these rules for inbound messages:
- Use webhooks for speed.
- Ignore messages from the agent. This stops infinite loops.
- Find the record by thread ID.
- If no record exists, triage the message.
For long threads, summarize early messages. Pass only the last few messages to the LLM. This saves tokens.
Build safety rails:
- Set a turn cap. Stop the loop after 10 turns.
- Escalate to a human when the agent is stuck.
- Mark the chat as complete when the goal is met.
- Alert a human if a thread stays silent for a week.
Production tips:
- Batch fast replies. Wait 30 seconds before replying.
- Handle duplicate webhooks. Use locking.
Email threads are better than chat tabs. They do not vanish. Your state machine survives crashes.
Start small. Build the start function. Build the webhook filter. Test it with yourself over two days. Restart your process. See if the agent remembers you.
Source: https://dev.to/qasim157/multi-turn-email-conversations-for-llm-agents-280j Optional learning community: https://t.me/GyaanSetuAi