Day 90 of 90 | Monday, January 26, 2026

Answer Block

Answer Block: 0 days remaining in our journey to build a profitable AI trading system.

0 days remaining in our journey to build a profitable AI trading system.

Today was a wake-up call. Two critical issues surfaced that could have derailed our entire trading operation. Here’s what went wrong and how we’re fixing it.

The Hard Lessons

These are the moments that test us. Critical issues that demanded immediate attention.

Paper Trading Blocked by Overly Strict VIX Threshold

Paper trading phase went 5 days (Jan 22-26) with ZERO trades executed. The system was “working as designed” but the design prevented any trading during the validation phase.

CI Scripts Failing + Orphan Positions Blocking Trades

After fixing VIX threshold (LL-316), iron condor trades were STILL blocked because:

  1. 3 orphan option positions from Jan 22 crisis were blocking new trades
  2. The manage_iron_condor_positions.py sc

Important Discoveries

Not emergencies, but insights that will shape how we trade going forward.

CTO Violated Directive 3 - Asked CEO to Do Manual Work

CLAUDE.md Directive #3: “Never tell CEO to do manual work - If I can do it, I MUST do it myself.”

Crisis Prevention Systems Audit - Jan 26, 2026

Audit of all crisis prevention systems implemented after the Jan 20-22, 2026 position accumulation crisis. All major safeguards are in place and functioning.

RAG Hooks Audit - SessionEnd Hook Ineffective (FIXED)

Audit of RAG hooks against official Claude Code documentation revealed that capture_session_learnings.sh is configured as a SessionEnd hook, which cannot inject context to Claude. This means les

Quick Wins & Refinements

  • PR & Branch Hygiene Session - Jan 26, 2026 - LL-316: PR & Branch Hygiene Session - Jan 26, 2026

Summary Completed PR management and branch clea…

  • CTO Session - Wrong Repo Confusion & RAG Query Protocol - 1. CEO asked “How much money did we make today?”…
  • Execution Readiness Checklist - Jan 26, 2026 - CEO Directive: “Execute” - Stop researching, start trading….

Today’s Numbers

What Count
Lessons Learned 8
Critical Issues 2
High Priority 3
Improvements 3

Tech Stack Behind the Lessons

Every lesson we learn is captured, analyzed, and stored by our AI infrastructure:

flowchart LR subgraph Learning["Learning Pipeline"] ERROR["Error/Insight
Detected"] --> CLAUDE["Claude Opus
(Analysis)"] CLAUDE --> RAG["legacy RAG
(Storage)"] RAG --> BLOG["GitHub Pages
(Publishing)"] BLOG --> DEVTO["Dev.to
(Distribution)"] end

How We Learn Autonomously

Component Role in Learning
Claude Opus 4.5 Analyzes errors, extracts insights, determines severity
legacy RAG Stores lessons with 768D embeddings for semantic search
Gemini 2.0 Flash Retrieves relevant past lessons before new trades
OpenRouter (DeepSeek) Cost-effective sentiment analysis and research

Why This Matters

  1. No Lesson Lost: Every insight persists in our RAG corpus
  2. Contextual Recall: Before each trade, we query similar past situations
  3. Continuous Improvement: 200+ lessons shape every decision
  4. Transparent Journey: All learnings published publicly

Full Tech Stack Documentation

The Journey So Far

We’re building an autonomous AI trading system that learns from every mistake. This isn’t about getting rich quick - it’s about building a system that can consistently generate income through disciplined options trading.

Our approach:

  • Paper trade for 90 days to validate the strategy
  • Document every lesson, every failure, every win
  • Use AI (Claude) as CTO to automate and improve
  • Follow Phil Town’s Rule #1: Don’t lose money

Want to follow along? Check out the full project on GitHub.

Day 90/90 complete. 0 to go.