BTC 5-min Polymarket Bot

Trading Bitcoin's 5-minute prediction markets is normally a four-person job. This project asks whether one engineer can do it.

Polymarket runs a binary market on Bitcoin every five minutes: will the price be up or down at the close. To trade it you need three things at once: fresh data from many exchanges (because the answer is being decided right now), software fast enough to act inside the 300-second window, and enough verification that you can let it run unattended, with real-money authority one flag away.

That is normally a team's job: a data engineer, a backend engineer, an SRE, and a quant developer. The question this project answers is whether one engineer, working with AI agents under strict review gates, can build and operate the whole thing.

A live Rust system on AWS prices a bet and decides in 21 microseconds, measured, not estimated.

Two always-on Rust services run on a single small ARM cloud instance. The collector connects to 11 venues (Binance, Coinbase, Kraken, OKX, Bybit, Deribit, Gemini, Bitstamp, Chainlink and Polymarket among them) across 49 event streams. On 2026-06-11 it captured 291 million market events, about 3,370 per second, writing roughly 7.7 GB of compressed columnar data that day into a research corpus now spanning about 147 GB.

The trading process consumes that feed over shared memory and decides, on every top-of-book change, whether to place an order. Production tracing puts the full decision pass at a 21 µs median and ~60 µs at the 99th percentile, measured over 506,243 live calls in a single day. A machine-learned model re-scores the market roughly once a second, whenever a fresh exchange candle lands.

It runs in paper mode: every order takes the real signing, risk-check and venue round-trip, then is rejected at size zero by design, so the wire path is exercised continuously without money at risk. Brief operator-funded validations have exercised the real-money path end to end. No trading-performance figures are published.

Nothing polls. Every decision fires the instant a market event arrives, moved between processes in about a microsecond.

Everything is event-driven and there is no polling loop. A venue message arrives, flows through lock-free shared-memory IPC in about 1 µs, and either changes a decision input or it doesn't. Decisions that fire become signed orders pulled from a pre-signed pool, so the hot path never waits on cryptography.

Every order writes an audit trail, a state-machine row for each transition, timestamped, into an append-only journal. Over four recent paper days the bot placed 23,329 orders across 1,067 five-minute markets, and each one can be replayed transition by transition.

A separate probe fires a one-cent test order roughly every second, millions of placements a week, purely to measure how fast each venue acknowledges and cancels. Median acknowledgement is about 38 ms. The 99th percentile stretches past 2.8 s when the market moves. That measured distribution, not a guess, is what the backtester uses to model execution.

13 quality gates block every commit, and there is no flag to skip them.

The operating discipline is the part that makes an always-on system trustworthy with one person behind it. Every commit passes 13 strict pre-commit gates: link and freshness checks, schema-drift detectors, supply-chain audits, and an AI code reviewer that reads each staged file and can block the commit. There are no bypass flags. The suite held 2,948 passing tests at its last recorded full run.

Verification continues after deploy. 102 soak-test runners check the production data (completeness, latency budgets, schema invariants) against a mirror synced every five minutes, and a systemd timer probes process health every minute. Capture coverage over the last 19 full days is 99.8% of all 5-minute partitions. Each deploy ships with a recorded git commit and binary checksum and keeps the previous binary as a one-command rollback. An offline simulator replays recorded data and reproduces every live decision at 100% parity, so changes are proven safe before they ever reach the wire.

3,139 commits and 219,000 lines of Rust in 123 days, solo, with every number measured on the running system.

One engineer shipped this in 123 days: 3,139 commits, 219,000 lines of Rust across 389 files plus 77,747 lines of Python test and operations tooling, with AI agent orchestration as the only toolchain. Capture coverage held at 99.8% over 19 days, and 66 frozen design records explain why each major choice was made, so any future engineer (human or AI) inherits the reasoning, not just the code. The system even watches the market around itself, decoding tens of thousands of counterparty wallets from on-chain settlement events each week to study how the venue actually behaves.

The point is not any single number. It is that every figure above was measured on the running system, and the machinery that measured it ships with the product. The same discipline (spend caps, audit logs, unskippable tests) applies to automation work an order of magnitude simpler.