Fetch.ai says LA Hacks project MultiEval used specialist agents to test multi-agent delegation
Fetch.ai said a winning LA Hacks project called MultiEval used its specialist AI agents to test how multi-agent systems should delegate work, with the system running a 50-agent simulation of the US economy overnight.
50 specialized AI Agents ran a simulation of the US economy overnight.
A winning @LAHacks project, MultiEval, used @Fetch_ai's specialist agents to test how multi-agent systems should delegate work.
This system autonomously improved another Agent harness and was used to run a…
— Fetch.ai (@Fetch_ai) August 20, 2026
In a post on the company’s official X account, Fetch.ai described MultiEval as a project that used its specialist agents to evaluate other agents and improve an agent harness autonomously. The company said the setup ran through ASI:One and framed the process as “agents evaluating agents.”
How the LA Hacks project was described
According to Fetch.ai, MultiEval was used to test delegation inside multi-agent systems, with specialist agents helping run the benchmark and improve the harness used for the simulation. The company did not provide additional technical details in the post about the exact structure of the evaluation or the full scope of the overnight run.
The post adds to Fetch.ai’s broader LA Hacks presence, but the central claim is limited to the project’s use of specialist agents, the 50-agent simulation and the ASI:One workflow described by the company.
Fetch.ai also has a LA Hacks event page on its official site, which places the project in the context of its hackathon participation and agent-focused materials.
