1Traditional Chatbot:
2User: "What time do you open?"
3Bot: "We open at 9 AM"
4→ Simple Q&A, pre-programmed responses
5 
6AI Agent:
7User: "Book me a meeting with John next Tuesday"
8Agent: 
91. Checks John's calendar
102. Finds available slots
113. Proposes options
124. Books meeting
135. Sends invites
14→ Takes actions, multi-step reasoning

1┌─────────────────┬───────────────────────────────┐
2│ Chatbot         │ AI Agent                      │
3├─────────────────┼───────────────────────────────┤
4│ Answers questions│ Takes actions                │
5│ Pre-defined flows│ Dynamic decision making      │
6│ Single task     │ Multi-step tasks              │
7│ Rule-based      │ AI-powered reasoning          │
8│ No memory       │ Context & memory              │
9│ Limited scope   │ Tool use & integrations       │
10└─────────────────┴───────────────────────────────┘

1Natural language processing:
2- Understand intent
3- Extract entities
4- Handle variations
5- Context awareness
6 
7Example:
8"I need to reschedule my appointment"
9→ Intent: reschedule
10→ Entity: appointment (existing)
11→ Action: Find current booking, offer new times

1Agents can use tools:
2- Search databases
3- Call APIs
4- Send emails
5- Update records
6- Generate content
7- Process files

1Complex task breakdown:
2 
3User: "Prepare my weekly report"
4 
5Agent steps:
61. Query sales data from CRM
72. Calculate metrics
83. Compare with last week
94. Generate summary text
105. Create charts
116. Compile into document
127. Send to stakeholders

1Types of memory:
2 
3Short-term (conversation):
4- Current session context
5- Recent messages
6- User preferences
7 
8Long-term (persistent):
9- User profile
10- Past interactions
11- Learned preferences

1- 24/7 automated support
2- Ticket creation & routing
3- FAQ handling
4- Order status inquiries
5- Returns processing
6- Escalation to humans

1- Lead qualification
2- Product recommendations
3- Appointment scheduling
4- Follow-up sequences
5- Personalized outreach
6- Demo booking

1- Employee onboarding
2- Policy questions
3- Leave requests
4- IT support tickets
5- Training assistance
6- Feedback collection

1- Product search
2- Size/fit guidance
3- Order tracking
4- Returns handling
5- Personalized recommendations
6- Cart abandonment recovery

1┌─────────────┬────────────┬──────────────┬────────────┐
2│ Platform    │ Complexity │ Best For     │ Pricing    │
3├─────────────┼────────────┼──────────────┼────────────┤
4│ Voiceflow   │ Medium     │ Conversations│ Freemium   │
5│ Botpress    │ High       │ Complex flows│ Open source│
6│ Stack AI    │ High       │ Enterprise   │ Paid       │
7│ Chatbase    │ Low        │ Quick deploy │ Freemium   │
8│ Typebot     │ Medium     │ Lead gen     │ Open source│
9└─────────────┴────────────┴──────────────┴────────────┘

1Strengths:
2✅ Visual conversation design
3✅ Built-in NLU
4✅ Voice + chat support
5✅ Great documentation
6✅ Knowledge base feature
7 
8Best for:
9- Conversational AI
10- Customer support
11- Voice assistants

1Strengths:
2✅ Open source
3✅ Highly customizable
4✅ Self-hosting option
5✅ Advanced NLU
6✅ Developer-friendly
7 
8Best for:
9- Complex workflows
10- Enterprise deployment
11- Custom integrations

1Strengths:
2✅ Visual workflow builder
3✅ LLM orchestration
4✅ Enterprise features
5✅ Pre-built templates
6✅ Team collaboration
7 
8Best for:
9- Enterprise automation
10- Complex AI workflows
11- Production deployments

1┌─────────┐     ┌─────────┐     ┌─────────┐
2│  User   │────▶│ Agent   │────▶│ Actions │
3│  Input  │     │ Brain   │     │ & Tools │
4└─────────┘     └─────────┘     └─────────┘
5                    │
6              ┌─────┴─────┐
7              │  Memory   │
8              │ & Context │
9              └───────────┘

11. Input Processing
2   - Text, voice, buttons
3   - Intent recognition
4   - Entity extraction
5 
62. Agent Brain (LLM)
7   - Reasoning
8   - Decision making
9   - Response generation
10 
113. Tools & Actions
12   - API calls
13   - Database operations
14   - External services
15 
164. Memory
17   - Conversation history
18   - User data
19   - Knowledge base

11. What problem does it solve?
22. Who are the users?
33. What actions should it take?
44. What integrations needed?
55. How to measure success?
66. What's the fallback plan?

1Measure:
2- Resolution rate (% solved without human)
3- User satisfaction (CSAT)
4- Time to resolution
5- Handoff rate
6- Conversation completion rate
7- Return users