Automate Secure Enterprise Code
This challenge focuses on building a sophisticated multi-agent system for secure, automated software development within an enterprise environment. Participants will architect a team of specialized agents using AutoGen to collaborate on a given software development task, from requirements gathering to code generation, testing, and deployment. The core innovation lies in integrating these agents with enterprise systems (e.g., version control, CI/CD, internal knowledge bases) through the MCP. MCP will ensure secure, audited, and controlled access for agents to sensitive enterprise tools and data. GPT-5 will serve as the primary reasoning engine for complex code generation and architectural decisions, employing extended thinking and adaptive reasoning budgets to tackle intricate problems. This challenge emphasizes production-ready agent deployment, security, and seamless integration into existing enterprise workflows.
What you are building
The core problem, expected build, and operating context for this challenge.
This challenge focuses on building a sophisticated multi-agent system for secure, automated software development within an enterprise environment. Participants will architect a team of specialized agents using AutoGen to collaborate on a given software development task, from requirements gathering to code generation, testing, and deployment. The core innovation lies in integrating these agents with enterprise systems (e.g., version control, CI/CD, internal knowledge bases) through the MCP. MCP will ensure secure, audited, and controlled access for agents to sensitive enterprise tools and data. GPT-5 will serve as the primary reasoning engine for complex code generation and architectural decisions, employing extended thinking and adaptive reasoning budgets to tackle intricate problems. This challenge emphasizes production-ready agent deployment, security, and seamless integration into existing enterprise workflows.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master AutoGen for orchestrating collaborative agent teams with defined roles (e.g., 'Architect', 'Developer', 'Tester').
Implement Model Context Protocol (Model Context Protocol) for secure, controlled, and auditable access to enterprise APIs and data sources.
Build extended thinking pipelines with GPT-5, enabling agents to break down complex problems and iterate on solutions.
Deploy adaptive reasoning budgets for agents, allowing dynamic allocation of computational resources based on task complexity.
Design RAG systems to provide agents with up-to-date documentation, best practices, and enterprise-specific knowledge.
Integrate OpenAI o3 for specialized tool functions within the AutoGen framework, enhancing agent capabilities beyond raw LLM output.
[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
Requires VERSALIST_API_KEY. Works with any MCP-aware editor.
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Key dates and the organization behind this challenge.
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