// PROJECT — AI
Crypto Trade Agent
Solo design, build, and deployment
Most crypto signal tools stop at displaying ideas. Crypto Trade Agent goes further: every setup is automatically validated against live Binance market data and pushed through a server-side risk engine before it can become a (paper) trade. I built the whole system — schema, risk rules, execution loop, and dashboard.
The architecture deliberately separates signal generation from execution, the same separation-of-duties principle you'd apply to any system where one component shouldn't be able to act unilaterally. A Vercel Cron heartbeat fires every minute to drive the ingestion-validation-simulation cycle, with duplicate-prevention guards stress-tested under bursty cron firing so noise never pollutes the trade log. Trades, configurations, and run telemetry live in Supabase behind row-level security, with explicit metadata like market_regime and setup_strength_score recorded on every run so strategies can be analysed — and re-weighted — from real telemetry rather than vibes.
// Built With
// Highlights
- Separation of signal generation from execution — a server-side risk engine validates every trade before it reaches the simulated order book.
- One-minute Vercel Cron heartbeat drives the ingestion → validation → simulation loop, with duplicate-prevention guards stress-tested under bursty firing.
- Telemetry-first schema: market_regime, setup_strength_score, and full run metadata recorded in Supabase so strategy weights are tuned from real paper-trade results.
- Soft-reset workflow preserves historical telemetry across reseeds — strategy analysis survives data resets.
- Premium live dashboard with dynamic trading modes built on Next.js and Tailwind.
Security Considerations
- All exchange API keys live server-side in Vercel environment variables — nothing sensitive ships to the client.
- Supabase row-level security on trades, configuration, and telemetry tables.
- Strict 404 behaviour enforced on unknown routes to keep the API surface minimal and unenumerable.
- Anti-spam guardrails rate-limit the execution loop so a misfiring signal source can't flood the trade log.
Project Timeline
Discovery / Goal
Mar 2026Identified a need for a crypto signal terminal that doesn't just display ideas but automatically validates and paper-trades them. The goal was a secure, anti-spam execution loop that simulates real market conditions end-to-end.
Design Decisions
Mar 2026Separated signal generation from execution. Built a server-side risk engine to validate every trade and used Vercel Cron to fire one-minute heartbeat cycles, all while keeping a premium dashboard aesthetic.
Schema & Persistence
Mar 2026Modelled trades, configurations, and run telemetry in Supabase with row-level security. Added explicit metadata such as `market_regime` and `setup_strength_score` to make later strategy analysis tractable.
Implementation
Mar 2026Built the dashboard with dynamic trading modes, layered the risk management rules, and constructed `run-bot` endpoints for signal ingestion, validation, and order simulation.
Testing & QA
Apr 2026Verified the build locally, enforced strict 404 behaviour on unknown routes, kept all API keys server-side via Vercel environment variables, and stress-tested duplicate-prevention limits under bursty cron firing.
Deployment
Apr 2026Pushed to Vercel production with environment variables synced, Cron jobs registered, and Supabase migrations applied through the deploy pipeline.
Iterations
Apr 2026Added a soft-reset workflow to preserve telemetry across reseeds and refined the strength-scoring weights based on the first weeks of paper-trade results.