After enough conversations this month, a pattern starts to show itself. It’s not loud, and it’s not framed as a big migration announcement, but it’s real. Teams building AI agents that originally launched on Base or Arbitrum are quietly shifting parts of their stack to Kite’s L1. Sometimes it’s a full move. More often, it’s spinning up a parallel deployment just for agents.
The reason isn’t ideology. It’s workload.
Base and Arbitrum are very good rollups. Low fees. Fast confirmations. Huge liquidity. Strong backing. If you’re building a consumer-facing app or a standard DeFi product, they’re hard to beat. Most of these teams still use them for exactly that. But once the users stop being humans and start being autonomous agents, the tradeoffs change.
Agent workloads look nothing like normal dApp traffic. You’re not dealing with someone clicking a button every few minutes. You’re dealing with thousands of processes firing constantly. Agents paying for compute slices. Pulling data. Settling per-task fees. All in small amounts, all in real time.
On Base, even cheap gas starts to hurt when an agent network is pushing ten thousand or more transactions a minute. During busy periods, latency creeps up and fees spike just enough to break assumptions. Builders end up batching payments or adding retry logic. That keeps things alive, but it also slows agents down and makes behavior brittle. What was supposed to be autonomous starts to feel scripted.
Arbitrum runs into similar limits at scale. It handles human-driven throughput extremely well. But bursty, machine-driven micro-payments are a different shape of traffic. Sequencer delays, variable costs, and timing uncertainty show up exactly where agents are most sensitive.
Kite was built around that pattern instead of trying to adapt to it later.
Blocks are predictable and fast. x402 keeps micropayment fees flat and tiny even when volume spikes. Session-level execution lets agents act on their own without pulling the root wallet into every call. The three-layer identity model makes delegation precise and revocation immediate. Stablecoin liquidity is deep enough that settlement doesn’t become a bottleneck. And because it’s EVM-compatible, most teams aren’t rewriting contracts to try it.
The feedback from builders has been consistent.
One compute grid operator told me they were losing close to ten percent of micro-jobs on Base simply due to failed settlements during congestion. On Kite, that dropped to zero. Agents could bid and pay instantly without extra guardrails. A task marketplace team said they finally stopped batching payments once they moved agent settlement to x402. Sub-cent fees and sub-second finality made per-task payouts viable. A research bot developer mentioned that while Base felt fast for humans, Kite’s predictability mattered more when agents were chaining dozens of external calls together without timeouts.
What’s important is that most of these teams aren’t abandoning Base or Arbitrum. They’re splitting responsibilities. User-facing contracts stay where the liquidity and wallets are. Agent coordination and payment loops move to Kite, where speed and cost matter more than ecosystem breadth. Bridging tools make that division manageable.
You can see the shift in Kite’s community spaces. Developers comparing real gas costs, not estimates. Node operators talking about handling agent-driven traffic spikes without stress. Governance discussions focused on throughput and x402 optimizations instead of surface-level features. It’s attracting builders who think in terms of systems rather than apps.
The KITE token is starting to reflect that usage. Early incentives helped get the network moving. Now actual agent activity is generating fees that flow to stakers and governance. As more workloads migrate, the token captures value in the way it was designed to.
This isn’t hype-driven. No one is chasing points. Builders are responding to simple economics. Agents need payments that are cheap, fast, and reliable at scale. Base and Arbitrum do an excellent job serving people. Kite was built to serve machines.
When your users are AI agents firing off millions of tiny transactions a day, “almost works” isn’t good enough. That’s why teams are moving. Quietly, deliberately, and with code rather than announcements.
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