**Opus**: Maintains context, commitments, and style across long conversations. Self-consistent even when revisiting earlier topics. **Haiku**: Context retention degrades over turns. May: - Contradict earlier statements - Lose track of established facts or agreements - Reset persona or tone mid-conversation - Forget constraints established in early turns **Mitigation**: Re-inject critical state at each turn. For API-based multi-turn: ``` <state> Established facts: - User's name: Alice - Projec...
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# Multi-Turn Consistency
**Opus**: Maintains context, commitments, and style across long
conversations. Self-consistent even when revisiting earlier topics.
**Haiku**: Context retention degrades over turns. May:
- Contradict earlier statements
- Lose track of established facts or agreements
- Reset persona or tone mid-conversation
- Forget constraints established in early turns
**Mitigation**: Re-inject critical state at each turn.
For API-based multi-turn:
```
<state>
Established facts:
- User's name: Alice
- Project: Q4 dashboard redesign
- Constraint: Budget is $50K
- Previous decisions: Chose React over Vue (turn 3)
Active rules:
- Respond in 2-3 sentences per turn
- Do not suggest solutions over budget
</state>
[New user message here]
```
For single-prompt tasks that simulate multi-turn reasoning:
- Do not rely on Haiku maintaining context beyond 3-4 exchanges
- Build each step's output as input to the next step explicitly
- For chatbot applications, implement a state summary that gets
prepended to each turn
For persona consistency: re-state the role in the system prompt
AND reference it in the first user turn.
