Builder (personal research) · 2026–present
Freedom Machine — autonomous research infrastructure
A personal, paper-only research system built as a reliability-engineering exercise — an LLM proposes hypotheses, a separate deterministic layer decides, and a chaos-engineering suite of 3,000+ offline tests proves it fails loudly rather than silently.
What it is
A personal research system that generates and rigorously screens quantitative hypotheses on its own schedule. It is paper-only — no real-money execution, and it makes no financial claims or recommendations. I built it less as a "trading bot" and more as a testbed for a hard systems problem: how do you let an AI run unattended and still trust the output?
The interesting engineering
- LLM proposes, a deterministic layer decides what's real. An LLM generates rationale-first hypotheses on a recurring schedule; a lightweight LLM triage drops obvious duplicates; then a separate, fully deterministic statistical layer — multiple-testing deflation, a hierarchical pilot→sweep protocol, and correlation/redundancy pre-filtering, all pre-registered before any data is touched — is the sole arbiter of whether an edge is real. The model that dreams up an idea never gets to decide whether it survives the statistics.
- Pre-registered, then unattended. A nightly campaign scheduler runs with zero human intervention, gated by statistical templates written before any data is touched, and hard-scoped so it can never reach anything that would matter beyond the sandbox.
- A literature-mining pipeline harvests from OpenAlex, Semantic Scholar, arXiv, and CrossRef weekly, classifies abstracts with a schema-constrained local LLM into a structured research map, and routes anything low-confidence to a human review queue instead of auto-accepting it.
- Chaos engineering, for real. A dedicated fault-injection suite (
tests/chaos/) kills the process mid-critical-section, corrupts checksums, truncates append-only stores, and forces lock contention — then asserts the system surfaces each fault by name rather than merely "not crashing." The full gate runs 3,000+ tests, fully offline (network disabled). - Fail-loud data integrity: append-only ledgers with rotating backups, checksum-verified map files, and crash-safe idempotent daily jobs. Corruption is designed to halt loudly, never to silently return wrong data.
- A daily observability cockpit: one derived health metric plus ~9 traffic-light checks, delivered as a digest, specifically to catch silent pipeline failure — the worst kind.
Why it's here
It's the purest expression of a habit that shows up everywhere in my work: let automation run, but engineer it so you find out the instant it's wrong. Separate the creative part from the deciding part, pre-commit the rules, inject the faults yourself, and make silence impossible.