[AutoBE Hackathon] AI Chatbot generating Backend Application with AI Compilers ($6,400 Prize Pool)

1. Overview

Wrtn Technologies is hosting the 1st AutoBE Hackathon, a coding competition focused on evaluating AI-generated backend applications.

Event Details

• Participants: Maximum 70 people
• Registration Period: September 5-11, 2025
• Event Schedule: September 12-14, 2025 (64 hours)
• Start: September 12, 08:00:00 PDT (UTC-7)
• End: September 14, 23:59:59 PDT (UTC-7)
• Winners Announcement: September 17, 2025
• Total Prize Pool: $6,400
  • Grand Prize: $2,000
  • Excellence Award: $1,000
  • Participation Prize: $50 (for detailed reviews)
• Token Credits: $350 per participant (no API cost barriers)

The hackathon challenges experienced backend developers to evaluate whether AutoBE’s output meets production standards, examining code quality, scalability, and performance.

2. What is AutoBE?

AutoBE is an AI-based no-code platform for generating production-grade backend applications from natural language instructions.

• GitHub Repository 
• Documentation 

Key Innovation

AutoBE employs a “Compiler-in-the-Loop” approach to ensure generated code compiles and runs correctly. The platform achieves a 100% build success rate with OpenAI GPT-4.1.

2.1 How It Works

AutoBE follows a 5-stage process with specialized AI agents and real-time compiler validation:

1. Analyze Agent: Interprets requirements and defines user roles
2. Prisma Agent: Designs type-safe database schemas using Prisma ORM
3. Interface Agent: Creates RESTful APIs with OpenAPI 3.1 documentation
4. Test Agent: Writes E2E test code for normal, edge, and error cases
5. Realize Agent: Implements NestJS-based backend code

Each stage includes validation through specialized AI-friendly compilers.

2.2 Technical Features

AutoBE’s AI-specific compilers validate syntax, logic, and functionality in real-time. The tech stack includes TypeScript, NestJS, Prisma ORM, and PostgreSQL/SQLite. Compilers use AST-based code generation for consistency across Prisma, OpenAPI, and test domains.

2.3 Live Demonstration

Example applications generated by AutoBE:

• Discussion Board
• To Do List
• Reddit Community
• E-Commerce Platform

Creating a discussion board requires five natural language commands, generating a deployable backend in approximately 70 minutes.

3. Eligibility

Target Participants:

• Experience with Node.js, Java, Python, or similar frameworks
• Relational database design skills
• RESTful API design experience
• Conversational and technical English proficiency
• Technical setup with Node.js, Git, and a code editor

4. How to Participate

4.1 Registration

Apply via Google Forms (registration deadline: September 10, 2025). Limited to 70 participants on a first-come, first-served basis.

4.2 Account Issuance

Participants receive AutoBE access credentials and usage guides via email on September 12.

4.3 Hackathon Process

During September 12-14, participants log into AutoBE and generate two backend applications using two different AI models with different themes. They record conversations, results, and issues.

4.4 Submission

Participants submit two separate reviews to GitHub Discussions by September 14, 2025, providing detailed and specific feedback.

5. Provided AI Models

5.1 openai/gpt-4.1-mini

This cost-effective model suits small to medium backend applications (approximately 20 tables, 150 API endpoints). It performs well for community boards, blogs, or project management tools, supporting CRUD operations, user authentication, permission management, and file uploads.

Strengths include requirements analysis and API design, producing clear specifications and clean RESTful structures. However, it may produce logical errors in complex business logic or fail to fully resolve compilation issues in test code due to its lightweight design.

5.2 openai/gpt-4.1

Available after completing gpt-4.1-mini review. This advanced model optimizes for enterprise-grade backend applications (500+ APIs, 1,000+ test scenarios). It excels at understanding complex requirements and implementing advanced features like real-time notifications, complex permissions, transaction processing, and caching.

AutoBE achieves a 100% build success rate with this model, producing production-ready code with no compilation errors. Generating an e-commerce platform costs $300-400 (150M tokens), so access is restricted to manage expenses.

5.3 qwen/qwen3-235b-a22b

This lightweight, open-source model runs on laptop-level resources. It suits small applications (5-10 tables, 20 APIs) like todo lists or simple accounting tools, handling basic CRUD operations and straightforward logic.

It struggles with complex requirements and often fails to resolve compilation errors. This model is optional and included purely for exploring local LLM performance comparisons.

6. Evaluation Criteria

6.1 Requirements Analysis

• Accuracy of understanding and prioritization
• Logical roles and permissions
• Coverage of non-functional needs (performance, security, scalability)
• Document clarity and detail

6.2 Database Design

• Production-readiness and logical relationships
• Balanced normalization for integrity and performance
• Appropriate keys and indexes for efficiency
• Proper naming, data types, and scalability

6.3 API Design

• RESTful compliance (methods, URIs, status codes)
• Unified endpoints and formats
• Clear OpenAPI specifications with examples
• Adequate authentication and data protection

6.4 Test Code

• Effectiveness in validating business logic
• Coverage of normal, edge, and exception cases
• Clear, independent, debuggable tests

6.5 Implementation Code

• Readability, modularity, and SOLID compliance
• Extensible architecture with clear layer separation
• Query efficiency without N+1 issues
• Strong security and type usage

6.6 Overall Review Writing Guide

Reviews should address AutoBE’s strengths and weaknesses, its impact on development time and code quality, and specific improvement areas with priorities.

7. Prizes and Benefits

• Grand Prize: $2,000 for the best review
• Excellence Award: $1,000 for the second-best review
• Participation Prize: $50 for all submitting detailed reviews
• Exclusions: AI-generated, perfunctory, or plagiarized reviews
• Judging: By AutoBE team and experts, announced September 17, 2025

8. Disclaimer

8.1 Beta Limitations

AutoBE is in beta and may have inefficiencies or errors. These reflect its development stage rather than bugs.

8.2 Code Usage

Generated code isn’t recommended for production without review and audit. Wrtn Technologies assumes no liability.

8.3 Open Source

Reviews and generated code are publicly posted on GitHub Discussions. Participants should avoid including sensitive information.