4 engineering patterns behind the strongest AI Agents Challenge submissions

We just wrapped the Google for Startups AI Agents Challenge with thousands of builders shipping agents from around the world, and our panel scored submissions across three tracks.

The “multi-agent-system” was probably the most frequent claim across the submissions, and on closer inspection, some actually were truly sophisticated multi-agent solutions while some others turned out to be a single model working through a chain of prompts with agent names attached.

Across this spectrum though the entries that actually ranked at the top of each track kept showing the same handful of engineering decisions and patterns. Here are four of them, worth stealing for your own build. They're pulled from real code submissions and described without names, because this isn't about any one team:

• Bidirectional MCP: an agent that's both a client of its own tools and a server other agents can call.
• Event-driven concurrency: agents reacting to a shared signal in parallel instead of waiting in a call chain.
• Same-bar fallback: a smaller model standing in for an overloaded one without a lower quality check.
• Tiered routing: cheap, deterministic checks running before the model gets touched at all.

Most submissions used MCP one direction: the agent calls out to a tool server for data. However, one team extended it both ways. Their agent consumed a telemetry database through its own MCP tool layer internally, then exposed that same reasoning as an MCP server other agents could call, so another agent could ask it a question directly, no chat UI built for humans required.