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The article centres on how Arca uses AI agents in wealth management: a persistent per-client memory system, a custom harness that routes tasks across frontier models, and multi-day workflows with human advisors making final trading and money-movement decisions. For AI readers, the useful takeaways are the practical design choices: owning the orchestration layer to avoid lock-in, and keeping agents limited to analysis and proposals. The article is company-sourced and light on performance data, so its claims about benefits are unverified.
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Source coveringLatent Space
Agents Prompt People: Using Agents for Long-Horizon Financial Work
Latent Space3 min read
Arca's head of AI discusses persistent memory, the benefits of a custom harness, and agentic workflows that span days.
At AI Engineer New York this month, we sat down with Aman Singh, the lead AI Engineer at Arca, an “AI-native” company providing wealth management services. We discovered that while agents do most of the background work in the firm, there are guardrails in place to ensure that human advisors are making the final decisions.…
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