Dispatches

Blog

Field notes from building the harness — what happens when the model runs inside the application, not behind a network.

How Lloyal turns the model's working memory into agents on the GPU

A walk down the stack, from TypeScript scope to the attention mask — how fork becomes an owner bit per cell, a cohort of agents becomes one batched decode, and the pressure counter becomes an admission controller your code reads.

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You already know this architecture. It shipped in 2007.

Familiar plumbing, novel use-case. Lloyal's serving stack maps noun for noun onto the stack that carried Rails for two decades — Rack→binding, Puma→host, Unicorn→relay, config.ru→driver.

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Shifting the harness left: 10 concurrent GLM-5.2 agents for the compute of one

How we served a deep-research app with 10 GLM-5.2 agents on one deployment — one shared KV context, one llama_decode per step, paid in memory not compute. Full trace, config, and cost receipt published.

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