Today, WorldClaw launches WorldRouter with @worldlibertyfi, one simple account to access 300+ AI models with competitive fees*. No more jumping between ChatGPT, Claude and all the others. Same power, way cheaper. This is your first step into the WorldClaw AgentOS. 👉 #USD1# #WLFI# #AI# #AgentOS# #WorldClaw# #WorldRouter# *WorldRouter rates shown are priced approximately 30% below the corresponding model providers' published list rates at the time of publication. See website for more pricing details.

Agents need reliable blockchain data to act onchain. Through Circle Agent Stack, @goldskyio lets agents query curated data across 40+ EVM networks and pay per request with Nanopayments, starting at $0.000005 in @USDC. No accounts, API keys, or subscriptions required. Explore the service:

Agents can write code faster than teams can review, deploy, and maintain it. Today we’re introducing the Agent Development Lifecycle and the Cloudflare primitives that underpin it.

Agents need more than just a container to scale. We're introducing @cloudflare/computer, an agent runtime that dynamically orchestrates between fast, efficient isolates and full Linux containers to give every agent a computer of its own.

Agents can compress review time without improving the review process itself. A study of 1.02 million pull requests across 207 GitHub projects tracks the shift from human-only review to LLM-assisted and agentic review. Projects that adopted AI gradually, or moved rapidly to agents, saw review time fall by 2.5 and 4.5 days per KLOC (the code change in thousands of lines of code) in the agent era. Projects that adopted LLM reviewers heavily and early saw no significant efficiency gain. The pull-request interaction patterns explain part of that split. Agent-initiated and multi-agent reviews reached decisions faster than human-only review under gradual and rapid-agent adoption. Agents often performed the initial inspection and summary, leaving the human reviewer with a shorter exchange. But most AI-involved patterns had review smells in 78% to 94% of pull requests, versus 69% to 76% for human-only review. Much of the difference came from repeatedly assigning the same AI reviewer identity, which narrows reviewer diversity. – arxiv. org/abs/2607.13196 Title: "From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality"

Agents and LLMs are still “dumb” in many ways. A 10x engineer who deeply understands computer systems, can easily outperform someone 1000x who has the best model in the world but no real understanding. “You can outsource thinking. But you cannot outsource understanding.”

Agents can now trade onchain like devs do. Introducing 0x AI for Agents: an open-source skill that gives coding agents a standard workflow for swaps across 20+ EVM chains via our Swap + Gasless APIs. Start now: