Overview
Conversation products are orchestration problems wearing a chat interface. The hard part is keeping state, intent, and user trust aligned across turns.
Problem
Teams often optimize single-turn responses while the real user experience depends on repair, escalation, and continuity.
Constraints
- Conversation state must be compact and durable.
- Escalation should preserve context for humans and systems.
- Tool execution needs clear confirmation and recovery behavior.
System Design
The workflow treats every conversation as a state machine with model-assisted transitions. Policy rules handle safety and escalation while models help interpret open-ended language.
Architecture
The system routes input through normalization, intent detection, state lookup, policy evaluation, tool execution, and response generation.
Tradeoffs
Strict flows improve reliability but can feel rigid. Fully generative flows feel natural but need guardrails. The practical middle is a typed workflow with model-assisted edges.
Impact
This approach makes conversational systems easier to test, monitor, and evolve without losing product control.
What I Learned
The best AI interface is often invisible: fewer magical claims, more graceful recovery.
Research Extension
Explore voice-first conversational policies where latency, interruption, and prosody become first-class system constraints.