botbook/src/05-multi-agent

Chapter 5: Multi-Agent Orchestration

Build complete applications through natural conversation. Describe what you want, and the system creates it automatically.

The AutoTask system uses an LLM-powered intent classifier to understand your request and route it to the appropriate handler. Whether you need a full web application, a simple reminder, or automated monitoring, you describe it in plain language.

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Intent Types

Type	Example	What Gets Created
APP_CREATE	"create app for clinic"	HTMX pages, tools, schedulers
TODO	"call John tomorrow"	Task saved to tasks table
MONITOR	"alert when IBM changes"	ON CHANGE event handler
ACTION	"email all customers"	Executes immediately
SCHEDULE	"daily 9am summary"	SET SCHEDULE automation
GOAL	"increase sales 20%"	Autonomous LLM loop with metrics
TOOL	"when I say X, do Y"	Voice/chat command

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Quick Start

Create an app for my clinic

10:30

Done:

patients table created

appointments table created

App available at /apps/clinic

10:31

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Architecture Overview

One bot equals one database. All applications within a bot share the same data tables, tools, and schedulers.

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File Structure

Path	Description
.gbdrive/apps/{name}/	Generated web application
.gbdrive/apps/{name}/index.html	Main HTMX page
.gbdrive/apps/{name}/assets/	CSS, images
.gbdialog/tables.bas	Database schema definitions
.gbdialog/tools/	Voice and chat commands
.gbdialog/schedulers/	Timed automations
.gbdialog/events/	Event triggers (ON CHANGE, ON EMAIL)

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Creating an Application

I need an app to track customers and orders

10:30

Done:

customers table created

orders table created

App available at /apps/store

10:31

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Modifying Your Application

Use Designer to change anything about your app through conversation.

Add a phone field to customers

14:20

Phone field added to customers table.

14:20

Change the submit button to blue

14:21

Button color updated to blue.

14:21

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Adding Automation

Every day at 9am, send me new orders by email

09:15

Scheduler created: daily-orders-summary.bas

Schedule: Every day at 9:00 AM

09:15

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Keywords Reference

Keyword	Purpose
TABLE	Define data structure
FIND	Search records
SAVE	Create record
UPDATE	Modify record
DELETE	Remove record
TALK	Send message
HEAR	Wait for input
SET SCHEDULE	Create automation
ON CHANGE	Monitor for changes
ON EMAIL	Trigger on email received

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Next Steps

• Designer Guide — Edit apps through conversation
• Data Model — Understanding tables
• Task Workflow — How tasks execute
• Examples — Real-world applications