AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review

Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review

Date: January 9, 2026
Severity: CRITICAL
Category: Trust/Operations/Strategy
Triggered By: CEO statement "I don't trust you anymore!!!!"

Root Causes of Trust Crisis

1. Paper Trading Broken 4 Days

• Evidence: Last trade date = 2026-01-06 (system_state.json:726)
• Impact: Cannot validate Phil Town strategy without trades
• Root cause: GitHub secrets may not be configured for $5K paper account

2. Phil Town Rule #1 Violation

• Evidence: avg_return = -6.97% (system_state.json:204)
• Impact: System is LOSING MONEY despite 80% win rate claim
• Root cause: Win rate metric is misleading (only 5 trades)

3. Stop Loss Too Loose

• Evidence: 200% stop loss (system_state.json:443)
• Impact: Allows positions to lose 200% before triggering
• Root cause: Conservative setting not aligned with Rule #1

4. Not Continuously Learning

• Evidence: Last vectorization = 2026-01-06 (vectorized_files.json:799)
• Impact: Not ingesting 2026 YouTube content, blogs, white papers
• Root cause: weekend-learning.yml not running automatically

What We Have vs What We Claim

Infrastructure (EXISTS)

• Phil Town knowledge base: 279 lines of strategy
• 20 YouTube transcripts vectorized
• 13 Phil Town blog articles
• Trailing stops script (221 lines)
• 64 test files (22,105 lines)
• Progress dashboard working

Execution (FAILING)

• Paper trading broken 4 days
• Avg return: -6.97% (NEGATIVE)
• Continuous learning not running
• No trades to record in RAG

Compounding Reality

$100/day requires ~$50,000 capital:

Capital	Target Date	Daily Target
$30	Today	$0 (accumulation)
$500	Feb 19, 2026	$1.50
$5,000	Jun 24, 2026	$15
$50,000	~2028-2029	$100

With compounding: $5,089 by Jun 2026 (+93% vs deposits alone)

Immediate Actions Required

Priority 1: Fix Paper Trading (CEO ACTION)

1. Go to: https://github.com/IgorGanapolsky/trading/settings/secrets/actions
2. Add: ALPACA_PAPER_TRADING_5K_API_KEY = PKMSWXVRXU6CYXOAIVVJVCMSWL
3. Add: ALPACA_PAPER_TRADING_5K_API_SECRET = 4KsCY4Qbb7RXILb459MXCuTi43iWkERBr3jgarkqudRx
4. Trigger: Actions → daily-trading.yml → Run workflow

Priority 2: Tighten Risk Management

• Change stop loss from 200% to 25-50%
• Verify trailing stops on all positions

Priority 3: Enable Continuous Learning

• Configure weekend-learning.yml to run automatically
• Ingest 2026 YouTube content

Prevention Protocol

Every session MUST verify:

1. Paper trading workflow ran (check last trade date)
2. RAG vectorization is recent (< 3 days)
3. Avg return is POSITIVE (not just win rate)
4. Stop losses are tight (< 50%)

Key Insight

Having infrastructure is NOT the same as executing correctly.

We have Phil Town knowledge but are violating Rule #1 by losing money.
We have trailing stops scripts but no positions to protect.
We have RAG but no trades to record.

Tags

trust-audit, phil-town, rule-1-violation, paper-trading-broken, evidence-based

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This lesson was auto-published from our AI Trading repository.

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