Topic

AI Systems Engineering

Engineering AI systems across model behavior, runtime, evaluation, infrastructure, interfaces, and cost.

Why It Matters Here

Most production failures live between layers. This topic keeps the archive centered on systems that survive real constraints.

Programs

This topic is not attached to an active public program yet.

Linked Artifacts

Paper / May 16, 2026

Disaggregated or Colocated? The Cost-Frontier of LLM Serving Under SLO Contracts.

Research Paper #1 in the AI systems engineering wedge. A closed-form decomposition of cost per SLO-compliant served token into a prefill term, a decode term, and a KV-transfer tax. Re-derives published throughput from five 2023–2025 systems papers (PagedAttention, Sarathi-Serve, DistServe, Splitwise, Mooncake) into a common frame, plots the first cross-system Pareto frontier under explicit p99 TTFT and p99 TPOT contracts, and solves the break-even surface between colocated and disaggregated architectures. The frontier partitions cleanly.

Field Note / May 16, 2026

Harvesting Serving Slack. ROSE and the Collapsed Train-Serve Boundary.

A daily field note on Gao, Zhao, Muhtar et al.'s ROSE. Cooperative elasticity for agentic RL rollouts on idle serving GPUs. Why the rollout-cost term in Cost-correct can be priced at the marginal-of-idle rate, and what that does to the inference-frontier threshold.

Field Note / May 17, 2026

The Power-Cap Illusion. SM Clock Locking and the Real Decode Lever.

A daily field note on Ma, Afzal, Eitzinger, and Wellein. Power capping does not bite in memory-bound LLM decode on NVIDIA H200. SM clock locking recovers up to 32% of decode energy. Why the standard energy lever moves the wrong knob, and what that does to the decode-cost term in Cost-correct.