AI trading agents face a reliability bar human apps never did
Picture two AI trading agents running the same model and the same strategy. A signal arrives during a fast market, both send an order, and one platform answers in milliseconds while the other times out. Same intelligence, different result.
The difference sat in the plumbing. As agents take on more of the work of trading, the infrastructure connecting them to markets plays a growing role in what they can actually deliver.
The Constraint Is Moving From the Model to the Pipe
For a consumer app, reliability is a user-experience problem. A delay means a spinning wheel, and the person taps again. For an agent it turns into a correctness problem. An agent making hundreds of automated calls reads a timeout as missing data, so it may act on stale account information, skip a check or retry an order into a worse price.
That gap is drawing money. Arcade raised...
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