Week 1: Setting the Baseline

What We Did This Week

Week 1 was about laying the foundation. The bot is now running 24/7, polling market data every 15 minutes across crypto and Polymarket. All 9 strategies are calibrated and actively scanning for signals.

Setup Checklist

• Infrastructure: Bot deployed on WSL2, running in a persistent tmux session. Telegram bot connected for alerts. Dashboard live at hub.tacavar.com.
• Data Feeds: 12+ APIs integrated — crypto prices, Polymarket odds, Twitter sentiment, news feeds, and on-chain data.
• Strategy Calibration: Each of the 9 strategies has been backtested on historical data and tuned for current market conditions.
• LLM Integration: Qwen3.5-plus wired into the decision loop. The model reviews every signal and provides confidence scores.
• Safety Gates: dry_run = true at multiple levels. Position limits (5% max per trade), circuit breakers (3 consecutive losses = pause), and daily budget caps ($1.50 simulated fees) all active.

Signals Fired, No Trades Taken

The bot identified 14 potential trade setups this week. Zero executed. Here's why:

• 8 signals were rejected by the LLM due to low confidence (<65%) or conflicting technical indicators.
• 4 signals fell into the "queue for review" range (65-84% confidence). These require human approval before execution.
• 2 signals hit the auto-execute threshold (85%+) but were blocked by the regime detector — market conditions flagged as "elevated volatility," which triggers tighter risk controls.

This is exactly how the system should work in early days. We'd rather miss opportunities than take dumb trades.

What We Learned

1. Regime detection is working. The bot correctly identified that we're in a choppy, directionless market. Mean reversion strategies are being upweighted; momentum strategies are being dialed down. This is the kind of adaptive behavior we built for.

2. The LLM is a good brake pedal. It's not great at predicting price direction (nobody is), but it's excellent at spotting contradictions in its own analysis. When the LLM says "I'm not sure," that's valuable information.

3. Polymarket liquidity is thin. Several potential arb opportunities disappeared when we factored in slippage. The bot now uses a more conservative liquidity model for prediction markets.

What Broke (Because Something Always Breaks)

Issue: The Polymarket WebSocket connection kept dropping after ~2 hours. Turns out we weren't handling the heartbeat properly.

Fix: Implemented automatic reconnection with exponential backoff. Max 3 retries before falling back to REST polling.

Issue: Dashboard showed stale data for ~30 minutes on Day 3. The static site build wasn't revalidating.

Fix: Switched to client-side fetching with 60-second polling. Live data now.

Week 2 Focus

• Fine-tune confidence thresholds based on signal quality
• Add correlation checks between strategies (avoid overlapping exposure)
• Improve LLM prompt to reduce "queue for review" ambiguity
• Stress-test the reconnection logic under network instability

The Bottom Line

No trades. No P&L. But the system is running, stable, and making smart decisions about when not to trade. That's a win in our book.

Week 2 will tell us more. If the bot starts taking trades, we'll publish the full breakdown: entry, exit, reasoning, and outcome. Win or lose, you'll see it.