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Latent SpaceArticle

Using Agents for Long-Horizon Financial Work — Aman Singh, Arca

Agents in financial work are moving from demo to production. Arca's custom harness and persistent state approach suggests the infrastructure bar for multi-step reasoning over extended timescales is becoming clear. The win here isn't the agent concept, it's proving reliability in a domain with real liability. For builders: this is a reference implementation for how to structure agent workflows when mistakes cost money.

arXiv cs.CLPaper

The Hitchhiker's Guide to System 1 Models: Fast Decision-Making Beyond LLMS

This is a useful framing. Most builders use LLMs for everything, but many decisions (routing, gating, scoring) should never go through autoregressive inference. The taxonomy helps you pick the right architecture class for your latency and calibration constraints. Read this if you're designing multi-stage AI systems and keep the five families in mind when you hit performance bottlenecks.