Muhammed Mustafayev — independent software engineer
Custom platforms for real businesses
Work across Türkiye and Europe
From product architecture to production
AI integrated into practical systems
Next.js · TypeScript · Python · Supabase
Muhammed Mustafayev — independent software engineer
Custom platforms for real businesses
Work across Türkiye and Europe
From product architecture to production
AI integrated into practical systems
Next.js · TypeScript · Python · Supabase
All work
Case Study

AI Trading System

Autonomous trading agents with hard risk limits.

PythonFastAPIOpenAIPostgresWebSockets

Everyone wants an AI that trades. Almost nobody wants what usually comes with it: an AI that loses money at machine speed. This system was designed backwards — risk limits first, intelligence second.

01

The brief

LLM-driven signals are seductive and treacherous: fluent, confident, occasionally catastrophically wrong. The mandate was to build an autonomous trading loop that could act on model-generated signals without ever being able to hurt the account beyond a predefined ceiling. Not 'usually safe' — architecturally incapable of blowing up.

02

The build

Signal generation runs through walk-forward backtesting before any idea touches live capital — strategies must survive data they have never seen. In production, every order passes a per-trade circuit breaker, and a hard drawdown ceiling sits above the whole system with authority to flatten everything and halt. The AI proposes; the risk layer disposes.

03

The payoff

The result is an agent that is deliberately boring: it skips more trades than it takes, and it has never had permission to be reckless. The interesting part is invisible — every skipped trade is a guardrail doing its job. This is a private, experimental system.

The scoreboard

  • Hard drawdown ceiling with kill-switch authority
  • Per-trade circuit breakers on every order
  • Walk-forward validation before any signal trades live

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