In early July, we ran two live webinars with our audience. Instead of theoretical tutorials, we built agents together—live, messy, and real.
We shared prompts, ideas, use cases, etc., to make the process frictionless. In a minute, we will share all the tools and resources with you too. Stay with us.
Our approach was simple: The Skeleton Philosophy.
Start with basic ideas and knowledge, create functional first versions that actually work, then iterate toward perfection later.
Using agent.ai's intuitive drag-and-drop interface, even non-technical participants could see their concepts come alive within minutes.
The magic wasn't in the complexity. It was in the momentum.
Once AI-curious folks like you saw their “skeleton agents” work, the perfectionism barrier disappeared. They stopped overthinking and started building.
To make building agents with agent.ai even more exciting, we turned the session into a little challenge - with the winner grabbing a MacBook Air!
So who won?
Before we share winners and their agents, we’d love to congratulate all the participants. Many builders end their pursuit in making the perfect plan, but you have stepped beyond and created your first agent.
Pat yourself on the back! 👏
And now 🥁 Winners of the Agent.ai Challenge
The challenge was simple: create an agent that solves a real problem.
The results exceeded our expectations and we picked one winner and two runners.
Runner Up 1: Learning Coach by Erik Snow
The agent instantly builds a personalized 7-day crash course on any topic you choose. It accounts for your learning style and expertise level, and even conducts daily micro-tests with gamified milestones.
Runner Up 2: Bug Finder by Jadon Amite
The Bug Finder systematically identifies and suggests fixes for code issues.
It has options to explain errors, fix code, and create test cases.
Winner: Stock Trade Analyzer by Pravin Ramasamy Balasundaram
This agent provides technical analysis for traders.
All you have to do is enter the ticker symbol (Example, NVDA) with your query, and it gives a detailed technical analysis of the stock.
MacBook Air is on the way to Pravin’s address.
The common thread among winners?
They didn’t spend hours creating the perfect plan. They started with clear problems and created functional solutions.
When the Skeleton was ready, they iterated it multiple times.
What now?
The challenge is done, but learning never is.
We're sharing our complete resource bundle with you—the same prompts, guides, and frameworks that helped create these winning agents.
Whether you're in marketing, finance, operations, or any other field, these tools will help you build your first skeleton agent.
Access the complete agent-building resource bundle and session recordings (use passcode ?G*2wG=T)