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The AI Agent Architect
Enterprise-Specific AI Projects
1. Overview
Focus
End-to-end voice-based AI systems, agent-driven workflows, and multimodal customer experiences designed for a specific enterprise use case.
Objective
This AI initiative enables leaders and cross-functional teams to design, build, and deploy enterprise-ready voice AI agents—from core technical principles and knowledge integration to action-capable, agentic systems with seamless human handover.
Target Audience
Interdisciplinary teams from:
Operations
Sales
IT
Management
Prerequisites
Basic understanding of digital business processes
No programming skills required
Interest in AI-powered customer and enterprise solutions
2. Program Structure
The program is designed as a three-day intensive format combining theory, live demonstrations, and hands-on labs, followed by one to three months of applied implementation.
Day 1: Foundations
From Theory to Voice
Architecture
Overall Goal
Demystify AI mechanisms and build the first functional voice-based AI agent.
Morning: AI Fundamentals & Market Context
Session 1: AI, Language Models, and the Multimodal Shift
Topics include:
How large language models work
Tokenization, probabilistic models, and next-word prediction
Differences between text-, voice-, and video-based AI
Real-time processing, latency, and conversational turn-taking
Why traditional chatbots fail in voice scenarios
Prompt design principles
A structured framework covering persona, context, task, and output format
Exercise: The Hallucination Trap
Participants intentionally generate incorrect AI outputs through poorly structured prompts and then correct them using systematic prompt design techniques.
Session 2: The Enterprise Voice AI Stack
Topics include:
Reference architecture of a voice AI system
Core components (reasoning, speech input, speech output)
Orchestration and system coordination
Tool selection strategies
Voice user experience design
Interruptibility, emotional tone, and conversational flow
Afternoon: First Live Build
Lab 1: Logic and Conversation Design
Goal: Model a customer-service triage flow without code.
Activities:
Building decision trees
Defining optimal conversation paths
Handling edge cases such as unclear input or human escalation requests
Lab 2: First Live Call
Goal: Connect the voice agent to a real telephone environment.
Activities:
Linking conversational logic to a voice engine
Deploying a live phone number
Testing latency, interruptions, and real user interaction
Day 2: The Brain
Knowledge Bases and Action-Capable Agents
Overall Goal
Evolve from scripted bots to data-driven, tool-enabled agents capable of reasoning and action.
Morning: Knowledge Integration
Session 3: Enterprise Data and Accuracy
Topics include:
The hallucination problem in language models
Risks of unrestricted model outputs in regulated environments
Retrieval-based techniques to constrain answers to internal documents
Case study demonstrating fully accurate responses to compliance-related questions
Lab 3: The Policy Expert Agent
Scenario: Internal HR or IT support.
Activities:
Uploading internal documentation
Configuring accuracy and response controls
Testing with detailed, document-specific questions
Afternoon: Agentic AI and Integrations
Session 4: Agents That Take Action
Topics include:
Transition from conversational AI to agentic AI
Tool access (e.g., calendars, customer records, messaging systems)
End-to-end workflows from voice input to real-world actions
Lab 4: Workflow Integration Workshop
Scenario: Lead capture or appointment scheduling.
Activities:
Connecting the voice agent to automation tools
Passing structured data such as names and email addresses
Automatically creating internal records
Optional: sending confirmation messages to callers
Day 3: Multimodal Experiences & Capstone Project
Overall Goal
Add visual layers, implement human handover, and solve real enterprise problems.
Morning: Hybrid Models and Visual AI
Session 5: Human Handover (“Soft Landing”)
Topics include:
Limits of AI systems
Detection of sentiment such as frustration or anger
Automatic escalation to human agents when needed or requested
Session 6: Visual Representation of AI
Topics include:
Use of video-based AI avatars
Applications in training, onboarding, and personalized sales
Micro Lab
Participants create a short video follow-up summarizing a previously built voice interaction.
Afternoon:
Department-Focused Solution Hackathon
Lab 5: Capstone Projects (Group Work)
Teams are organized by department:
Sales
Outbound qualification agent
Automated lead calls
Interest discovery and record updates
Operations / IT
Triage agent
Support ticket intake
Knowledge base queries
Automated ticket creation for unresolved cases
Management
Internal analytics agent
Voice-based access to quarterly and company reports
3. Conclusion
Final Demo Day
Presentation of all capstone solutions
Discussion of architectural, user experience, and business decisions
Evaluation based on real-world relevance, scalability, and enterprise value
Program Outcomes
Participants leave with:
A deep understanding of modern enterprise voice AI architectures
Multiple production-ready prototypes
The ability to deploy AI agents strategically, technically, and organizationally within an enterprise
Apply to join:
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