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Trading Systems

Autonomous trading system architecture — multi-agent decision pipelines, execution infrastructure and risk management, not indicator scripts.

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Overview

I design and build autonomous trading systems as software architecture — a decision pipeline with memory and risk management — not a single indicator-based script.

How I Build This

  • Separated agents/stages for market analysis, risk assessment and execution, so no single failure point controls the whole pipeline.
  • Persistent knowledge storage (graph-based structure plus vector-based similarity memory) so the system can reason about market conditions, not just react to the latest price tick.
  • Direct integration with real exchange APIs (e.g. Bybit) for live and paper-trading execution.
  • Containerized, reproducible deployment — the same system runs the same way in development and live.

This is the architecture behind S.A.M.S., a live multi-agent trading system for crypto markets.

Who This Is For

Traders and firms who've outgrown a single strategy script and need a system that can hold state, manage risk explicitly, and be audited after the fact.

FAQ

Do you build strategies, or the system around them?

Both — but the emphasis is the system architecture: how analysis, risk and execution are separated and coordinated, which is what makes a strategy survivable in live markets.

Which markets/exchanges do you work with?

Crypto markets via exchange APIs such as Bybit; the same architecture generalizes to other venues.