Atos and AWS Put 400 Engineers Into a Scored Multi-Agent AI Contest

Atos and AWS ran a three-day AI League for 400 Atos engineers, turning agentic AI training into a live contest for building multi-agent systems. Participants made autonomous agents navigate a dungeon maze, solve tasks, avoid traps and reach treasure within time and life limits; the leaderboard measured performance and efficiency.

The event drew people with sharply different starting points. Atos reported that 5% had no prior knowledge of agentic AI, while 50% understood the topic but lacked hands-on experience. Another 20% entered with practical experience using agentic AI services.

The maze turned agent design into a set of choices

Participants built agents to choose routes through tiles containing coins, traps and challenges. Correct answers earned points, while wrong ones cost lives; reaching the treasure and keeping lives raised a score. The work covered multi-agent coordination, pathfinding, web retrieval, code execution, memory, prompt engineering, guardrails and model fine-tuning.

5%No prior knowledge

Atos reported that 5% of registrants had no prior agentic AI knowledge.

50%Understanding, no hands-on work

Atos reported that half of participants understood agentic AI but had no hands-on experience.

20%Practical experience

Atos reported that 20% had practical experience with agentic AI services.

Efficiency was a first-class requirement

A working answer was not enough. Concise responses outscored verbose ones, and participants could earn bonus points by fine-tuning specialist small language models. Engineers also had to choose between more specialized or more multifunctional agents, weighing token use, latency and reliability.

Three technical pressure points

• Guardrails: engineers configured denied topics and content filters, while trying not to block legitimate queries.
• Memory: AgentCore memory retained context across interactions, including collected keys and solved challenges.
• Tool use: AgentCore Gateway routed calls through MCP to Lambda functions for pathfinding, web scraping and code execution.

Training for a broader AWS agent push

Engineers used Amazon Bedrock, Bedrock AgentCore, Lambda, Bedrock Guardrails, Kiro and SageMaker. Atos says the event created internal champions and increased confidence in applying agentic AI to client engagements.

The exercise sits alongside Atos’s AgentX, which the company describes as a multi-agent framework powered by AWS agents and purpose-built agents for cloud operations. Atos says AgentX is designed to handle incident triage, investigation, resolution and IT service-management updates.

AWS says the AI League format is available for enterprise events through 2026, as well as at select AWS Summits and virtual events.