🤖 Agentic AI for Engineers - Build an AI Travel Planner ✈️ - Part. 2
Details
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Planning a trip can quickly become complex:
- Comparing flights across platforms
- Selecting hotels based on budget and preferences
- Organizing activities and optimizing schedules
While many tools provide partial answers, few are able to combine all constraints into a coherent, optimized travel plan.
This is where Agentic AI systems unlock a new level of automation.
But building a reliable AI travel planner requires more than just querying APIs with an LLM.
How do you design a system that can:
- Retrieve and combine data from multiple sources (flights, hotels, activities),
- Reason over constraints like budget, time, and preferences,
- Plan multi-step itineraries,
- And coordinate multiple agents working together?
In this 60-minute interactive webinar, we’ll walk through the end-to-end design and implementation of an AI-powered travel planner, using advanced agentic design patterns and multi-agent collaboration.
The session will include a live implementation using Python, LangChain, LangGraph, OpenAI, and Google APIs, demonstrating how to orchestrate planning agents, tools, and workflows to generate a fully optimized travel itinerary.
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### You’ll learn
✈️ Core Concepts of Agentic AI for Planning Systems
How planning problems differ from simple Q&A:
- Multi-step reasoning and constraint satisfaction
- Tool usage and API orchestration
- State and memory across complex workflows
- Deterministic vs agent-driven planning
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🧠 Advanced Agentic Design Patterns
Explore key building blocks of modern AI systems:
- Tool-based agents (APIs for flights, hotels, maps)
- Planner–executor architectures
- Multi-agent collaboration (specialized agents per task)
- Human-in-the-loop validation for critical decisions
- Advanced prompt engineering for structured planning
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🔗 Multi-Agent Orchestration with LangGraph
How to structure complex workflows:
- Defining agent roles (planner, search, optimizer, validator)
- Managing state transitions across steps
- Handling failures and retries
- Ensuring consistency across agents
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🌍 Live Demo: Building an AI Travel Planner
Step-by-step walkthrough:
- Connecting to external APIs (Google services, travel data)
- Designing a planner agent to structure itineraries
- Coordinating sub-agents for flights, hotels, and activities
- Optimizing budget allocation across the trip
- Generating a full, structured travel plan
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💡 From Prototype to Real Product
Discussion around:
- Reliability and hallucination control
- Cost optimization (API + LLM usage)
- UX considerations for travel assistants
- Scaling to production systems
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📅 Duration: 60 minutes
🛠️ Tech Stack: Python, LangChain, LangGraph, OpenAI, Google APIs