Sean Howell
researcher // engineer // technical leader
Los Angeles · San Francisco Bay Area
writing
2026-08
Why the harness discipline forming around coding agents has to be rebuilt for agents that do science, and what five months of benchmarks, automated harness search, and gated laboratory control did to the framework.
2026-04
On the recursive structure of machine learning and quantum computing, and why a new result on quantum oracle sketching gives the second half of the loop a rigorous foothold.
2026-03
Why the biggest machines of the next decade will be inhabited by dense ecologies of small machine intelligences, and why the organizations that matter should start cultivating them now.
2026-02
Why utility-scale quantum computers, autonomous laboratories, advanced fabs, and large robotic systems will need advanced AI built into the machine as an operating layer.
2025-05
A short note on the spirit of the era, written to no particular age of reader, chronological, spiritual, biological, or cybernetic.
publications
- H. Levine, A. Haim, et al. Demonstrating a long-coherence dual-rail erasure qubit using tunable transmons. Physical Review X, 2024.
- Y. Baum, M. Amico, S. Howell, et al. Experimental Deep Reinforcement Learning for Error-Robust Gateset Design on a Superconducting Quantum Computer. PRX Quantum, 2021.
- Y. Baum, S. Howell, et al. Reinforcement Learning for Error Robust Control on Cloud-Based Superconducting Hardware. Bulletin of the American Physical Society, 2021.