𝗩𝗼𝗶𝗰𝗲 𝗔𝗜: 𝗗𝗶𝗮𝗹𝗼𝗴 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 - 𝗧𝗵𝗲 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗼𝗿

We've talked about how Voice AI listens (ASR) and understands (NLU).

But once the system understands the user, there's a harder question:
👉 What should happen next?

This is where Dialog Management comes in.

It's not about generating responses - it's about orchestrating decisions across multiple turns.

E𝘅𝗮𝗺𝗽𝗹𝗲:
👤 "Book a flight to Paris"
🤖 [dest: Paris, origin: ❓] → "Where from?"
👤 "New York"
🤖 [all slots filled ] → "NYC → Paris. Confirm?"

That decision flow? That's Dialog Management.

𝗨𝗻𝗱𝗲𝗿 𝘁𝗵𝗲 𝗵𝗼𝗼𝗱, 𝗶𝘁 𝗵𝗮𝗻𝗱𝗹𝗲𝘀:
→ Tracking conversation state across turns.
→ Knowing what's been said vs what's missing.
→ Deciding when to ask vs when to act.
→ Handling corrections and errors.
→ Executing actions and tools safely.

This is what turns one-shot commands (from the user) into real conversations.

Modern Voice AI agents may use LLMs here - but structure is still essential for reliability and safety.

Without dialog management, even the best models feel unpredictable.

➡️ Next up: How Voice AI remembers - context & memory management.