Writing

Long-form pieces on quantum machine learning, scientific AI, the physics × ML interface, and the methodology questions that show up at all three intersections. Project notes from QMI Lab and AstroLLM land here as they ship.

  • How Lodestar records what an agent believed

     · 21 min read  · AI Agents · Trust · Memory

    Four orthogonal lifecycle axes, the rule that nothing promotes itself, and the audit trail that falls out the other end.

  • The question my coding agent couldn't answer

     · 13 min read  · AI Agents · Trust · Memory

    Agents act, agents remember, but the standard agent stack rarely lets you reconstruct what the agent actually believed when it acted. This is a problem worth a name.

  • Three axes of cost — what a matched-resource baseline actually means in quantum machine learning

     · 9 min read  · QMI Lab · Quantum Machine Learning · Methodology

    Quantum machine learning has a comparison problem. Most published QML results compare quantum methods against classical baselines that have not been given a fair share of resources — and the field is starting to notice. This is the methodology I am holding QMI Lab's Pillar II ...

  • Quantum-safe custody — what changes for hardware-anchored and MPC signing when ECDSA falls

     · 12 min read  · Quantum Cryptography · Post-Quantum Cryptography · Digital Assets

    The planning baseline for Q-Day compressed in March 2026, and the question for institutional digital-asset custody is no longer when, but whether the cryptography can be migrated fast enough. Hardware-anchored signing and MPC have different migration paths — and one will be su...

  • Starting QMI Lab — three pillars, one question

     · 7 min read  · QMI Lab · Quantum Machine Learning · Machine Intelligence

    QMI Lab is an independent research lab studying intelligence, learning, and representation across classical and quantum computation — three pillars at three time horizons, one question underneath. Why I started it, how it is organized, and what is coming.

  • The model I wish I had as a graduate student

     · 6 min read  · AstroLLM · Scientific AI · Domain-Specialized LLMs

    AstroLLM is an open-source, retrieval-grounded language model for astronomy and astrophysics — designed around the workflows researchers actually use rather than the benchmarks frontier models optimize for. Why I started it, where it is, and what is next.

  • Three fields, one question

     · 4 min read  · Project Notes · Cross-Domain · Intro

    A notebook for working out loud across machine intelligence, quantum computing, and the digital-asset infrastructure those two fields are starting to reshape. Why I write here, and what is coming.

A separate /writing/notes/ sub-section will host shorter informal pieces — paper reading notes, conference reflections — kept visually distinct from long-form essays.