Conversation Patterns

Conversation between humans and AI follows predictable structural patterns. Designing these deliberately — rather than leaving them to model defaults — is core interaction design work.

Turn-Taking Structure

Every human-AI conversation has a rhythm. The designer decides:

• Turn length: Short exchanges (chatbot-style) vs. long-form (essay generation). Match turn length to task complexity.
• Turn initiation: Who speaks first? Does the AI greet, or wait? Does it ask a clarifying question before acting?
• Turn boundaries: How does the user signal "I'm done"? How does the AI signal "I need more"?

Repair Sequences

Conversations break down. Repair is how they recover:

• Self-repair: The AI detects its own error and corrects ("Actually, let me revise that...")
• Other-repair: The user corrects the AI ("No, I meant the other one")
• Clarification requests: The AI asks for disambiguation before proceeding
• Graceful misunderstanding: The AI acknowledges confusion without frustrating the user Design repair sequences explicitly. Don't rely on the model to improvise them.

Grounding

Grounding is how participants establish shared understanding:

• Confirmation: "Just to confirm, you want me to..."
• Summarisation: "So far we've covered X, Y, and Z"
• Reference resolution: Handling pronouns, anaphora, and ambiguous references
• Context anchoring: Reminding the user what the AI knows and doesn't know

Dialogue Structure Patterns

Common structural patterns for human-AI conversation:

• Interview: AI asks questions, user answers, AI synthesises
• Co-creation: Turn-by-turn collaborative building
• Instruction-execution: User gives command, AI performs, user evaluates
• Exploration: Open-ended back-and-forth to discover possibilities
• Guided workflow: AI leads the user through a multi-step process Choose the pattern that matches the task. Don't default to instruction-execution for everything.

Design Artefacts

• Conversation flow diagrams showing turn sequences
• Repair protocol specifications
• Grounding checkpoints mapped to conversation stages
• Turn-taking rules per interaction context