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.

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AI agents initiated 16.2 million transfers through the x402 protocol over the past 30 days, according to a Token Terminal post. The data breaks down the activity across chains, with Base accounting for 9.5 million transfers and Polygon for 5.6 million.https://twitter.com/tokenterminal/status/2090165191489270116

The figures add fresh volume to x402, which describes itself as an internet-native payment standard for AI and agentic payments on its official dashboard. The headline metric points to measurable usage rather than a purely conceptual payment layer, although the data shown in the post is limited to transfers and does not by itself explain who the agents were or what kinds of payments they made.

The chain split also suggests the activity is concentrated rather than evenly distributed. Base led the tally by a wide margin, with Polygon also accounting for a large share of the reported transfers.

For now, the clearest takeaway is narrow but concrete: x402 is seeing repeated transfer activity from AI agents, and the recent count gives a cleaner snapshot of where that usage is showing up onchain.

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Aptos said Confidential APT is now live on mainnet, bringing opt-in encrypted balances to the network while keeping wallet addresses visible. The feature is positioned for compliant use cases including payroll, treasury and business-to-business settlement.https://twitter.com/Aptos/status/2084481961553445096

The Aptos account said transactions are verified with zero-knowledge proofs, allowing the network to confirm that transfers are valid without exposing the underlying amounts. The update is meant for users who want confidentiality for specific transfers rather than full anonymity across the network.

A separate governance page tied to the rollout shows the proposal as executed, matching Aptos’ public statement that the feature has been enabled on mainnet. The material linked from that page describes Confidential APT as part of Aptos’ on-chain privacy features.

How the feature is framed on Aptos

According to Aptos, Confidential APT is opt-in, so users can still use standard transparent transfers if they prefer. The company’s framing focuses on enterprise and institutional settings where transaction amounts may need to be hidden while counterparties remain identifiable.

The launch adds a privacy layer at the transaction level, but it does not by itself indicate broader usage or adoption. It does, however, give Aptos a live mainnet mechanism for hiding balances on selected transfers.

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