Genuinely curious if five specialized agents beat one well-prompted model here, or if most of the win is structured prompts in an agent costume. For a hackathon either way ships though.
Building ATLAS: How I Built an AI-Powered Multi-Agent Travel Assistant During HACKHAZARDS '26
Public
10 conversations
15 thoughts
3 upvotes
0 downvotes
0 series
11 views
What if planning an entire trip took just a few minutes? I built ATLAS, an AI-powered multi-agent travel planning system that generates personalized itineraries, optimizes budgets, and adapts to changing travel conditions. Here's the journey behind building it during HACKHAZARDS '26.
In groups
Thought
Thought
Genuinely curious if five specialized agents beat one well-prompted model here, or if most of the win is structured prompts in an agent costume. For a hackathon either way ships though.
Post content
Building ATLAS: An AI-Powered Multi-Agent Travel Planning System
When planning a trip, most of us end up juggling multiple apps—one for flights, another for hotels, another for maps, another for budgets, and yet another for recommendations. While each platform solves a small part of the problem, none of them acts as a true travel companion.
That question inspired me to build ATLAS (Autonomous Travel Intelligence & Adaptive Planning System) during HACKHAZARDS '26.
The Problem
Travel planning is time-consuming and fragmented. A traveler typically needs to:
-
Research destinations
-
Compare accommodation options
-
Plan transportation
-
Estimate budgets
-
Discover attractions
-
Adjust plans when things change
This process can take hours or even days, especially for longer trips.
I wanted to explore whether AI could automate much of this work while still keeping the traveler in control.
The Idea
ATLAS is an AI-powered travel planning platform built around the concept of multiple AI agents working together.
Instead of relying on one AI model to handle everything, ATLAS assigns specialized responsibilities to different agents, allowing each one to focus on a specific task.
These include:
-
Destination Research
-
Budget Optimization
-
Itinerary Planning
-
Attraction Recommendations
-
Dynamic Trip Adaptation
The result is a more structured and intelligent travel planning experience.
How It Works
The user simply provides information such as:
-
Destination
-
Budget
-
Travel duration
-
Interests
-
Preferred travel style
ATLAS then generates a personalized itinerary that balances time, budget, and user preferences.
If travel conditions change, the system can adapt recommendations and update the itinerary instead of forcing the user to start over.
Technology Stack
I built ATLAS using modern AI and web technologies:
-
Next.js
-
React
-
TypeScript
-
Tailwind CSS
-
Vercel AI SDK
-
Workflow SDK
-
OpenAI APIs
-
Firebase / Supabase
-
REST APIs
The architecture is designed to support modular AI agents, making future improvements easier to implement.
Challenges
Like any hackathon project, there were several challenges:
-
Designing communication between AI agents
-
Structuring prompts for different travel scenarios
-
Managing travel context efficiently
-
Creating an intuitive user interface within limited time
These challenges pushed me to think beyond simply calling an LLM API and instead focus on system design.
What I Learned
Building ATLAS taught me valuable lessons about:
-
Agentic AI
-
Multi-agent workflows
-
Prompt engineering
-
Product thinking
-
Rapid prototyping
-
AI-powered user experiences
It also reinforced an important realization:
Great AI products are not just about powerful models—they're about combining the right architecture with a great user experience.
What's Next?
I plan to continue improving ATLAS by adding:
-
Real-time travel updates
-
Voice interactions
-
Offline support
-
Flight and hotel booking integrations
-
Collaborative trip planning
-
Smarter personalization
Final Thoughts
Hackathons are not just about winning—they're opportunities to learn, build, and share ideas with the community.
ATLAS represents my journey into Agentic AI and intelligent software systems, and I'm excited to keep improving it beyond the hackathon.
If you're building something interesting for HACKHAZARDS '26, I'd love to see it.
Happy building! 🚀
Project: ATLAS – Autonomous Travel Intelligence & Adaptive Planning System
Thoughts
-
Did you test this with real travel data, or mostly built with examples from the API docs?
-
The 36-hour crunch forcing you to design the system first instead of just calling an LLM is honestly the win here. That kind of thinking sticks with you.
-
repo says v0-atlas, so how much was v0 scaffolding vs hand-wired after? asking as someone who leans on it more than i admit
-
The multi-agent part is what I'd poke at. When the budget agent and the itinerary agent disagree, who wins? A coordinator, or do they just pass a shared context blob and hope it converges?
-
Genuinely curious if five specialized agents beat one well-prompted model here, or if most of the win is structured prompts in an agent costume. For a hackathon either way ships though.
Related discussions
-
I can only write false things. And I write poorly.
If anything can be posted here, then a few ramblings from someone who's confused won't do any harm. My English is poor; I use an external app.
-
MY RUBBISH TALKS ABOUT MY LIFE
just sharing my personal experience about my life happening throughout if you are intrested thats great and thank you first thing i dont know how to blog whatever but as you know why not try so i just started i even dont know what im intrested in but one thing i know is we live in a unintrested politicians who doesnt care about india whats in the point that i have no intrest in anything whatever i think you understand what im telling to go and this point you akready uderstand how lazy im most…
-
Patient as a tiger.
I am far from my goals, even though I try to achieve them. I am like a climber at the foot of Mount Everest. I need to be patient, as patient as a tiger stalking its prey. I need to be as patient as planet Earth has been for billions of years. I may fall along the way, but I will always get back up. I am like a climber at the foot of Mount Everest. I need to be as patient as planet Earth has been for billions of years. I may fall along the way, but I will always get back up. Patient as a tiger
-
Stay solid on your faith
People !!! Please stop worrying … instead keep your faith solid .. always remember we have the sun and the moon for a reason and they both have their fair share of work . What I mean is bad days…
-
Who is this?
When your regrets meet you in the mirror, will you recognise who it is?
-
AI Knows Your Work Better Than Your HR Department Does. That Should Terrify Everyone.
AI already tracks your work patterns better than your HR department does, yet most HR teams still run on spreadsheets and outdated policies. The trust gap between employees and HR makes AI adoption even harder, because most tools are built for employers, not employees. The smarter approach is flipping the model — giving employees direct access to AI-powered career tools, compliance calculators, and resume builders first, so trust and adoption follow naturally.
-
What are your goals, and how can this community help you achieve them?
Share your goals, ask questions, and connect with a supportive community. Together, we can learn, grow, and help each other succeed through education, career guidance, and personal development.
-
Friends do you know
Friends do you know