Day 95: What We Learned - January 31, 2026
Day 95 of 90 | Saturday, January 31, 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.
Markets are closed, but the learning never stops. While other traders take the weekend off, we’re refining our edge.
Important Discoveries
Not emergencies, but insights that will shape how we trade going forward.
Iron Condor Management - 71,417 Trade Study
Analysis of 71,417 iron condor trades on SPY (2007-2017) reveals optimal management strategies.
VIX-Based Iron Condor Entry Rules
Research-backed entry rules for iron condors based on VIX levels and IV rank.
XSP vs SPY - Section 1256 Tax Optimization
XSP (Mini-SPX) options qualify for Section 1256 tax treatment (60/40), potentially saving 25%+ on taxes vs SPY options.
Today’s Numbers
| What | Count |
|---|---|
| Lessons Learned | 3 |
| Critical Issues | 0 |
| High Priority | 3 |
| Improvements | 0 |
Tech Stack Behind the Lessons
Every lesson we learn is captured, analyzed, and stored by our AI infrastructure:
Detected"] --> CLAUDE["Claude Opus
(Analysis)"] CLAUDE --> RAG["LanceDB 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 |
| LanceDB 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
- No Lesson Lost: Every insight persists in our RAG corpus
- Contextual Recall: Before each trade, we query similar past situations
- Continuous Improvement: 200+ lessons shape every decision
- Transparent Journey: All learnings published publicly
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.
FAQ
What did we learn today?
3 lessons captured (0 critical, 3 high). Markets are closed, but the learning never stops. While other traders take the weekend off, we’re refining our edge.
How do you keep these lessons from getting lost?
We index every lesson into a RAG corpus and query it before new trades and major engineering changes.
Where is the canonical version of this post?
This post’s canonical URL is https://igorganapolsky.github.io/trading/2026/01/31/lessons-learned/.
Day 95/90 complete. 0 to go.