Day 94 of 90 | Friday, January 30, 2026

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.

SOFI Position Held Through Earnings Blackout

SOFI CSP (Feb 6 expiration) was held despite Jan 30 earnings date approaching.

Key takeaway: Put option loss: -$13.

The Four Pillars of Wealth Building

``` ┌─────────────────────────────────────────────────────────────┐ │ FINANCIAL INDEPENDENCE │ │ $6K/month after tax │ ├─

Key takeaway: Result after 7 years: ~$215,000 (2.

CTO Failed Phil Town Rule 1 - Lost 86% of Account

The CTO (Claude) failed to protect capital. Starting balance of $30,000 reduced to $4,099.71 - an 86% loss in 8 days of paper trading.

Key takeaway: Don’t lose money.

SOFI Loss Realized - Jan 14, 2026

  1. SOFI stock + CSP opened Day 74 (Jan 13)

Key takeaway: System allowed trade despite CLAUDE.

Important Discoveries

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

Iron Condor Entry Signals & Timing

System not generating enough trade signals. Need clear entry criteria.

Q1 2026 Tax Action Plan

Concrete action items for Q1 2026 tax planning. This is the “do this now” version of the comprehensive tax strategy (LL-297).

Iron Condor Optimization for $30K Account

New $30K paper account established. Need optimized iron condor parameters for:

  • Above $25K = NO PDT restrictions
  • Target: $400-800/month (1.3-2.7% monthly return)
  • Risk: Max 5% per trade ($1,500)

Quick Wins & Refinements

  • Dialogflow Compound Query Routing Fix - LL-274: Dialogflow Compound Query Routing Fix

Date 2026-01-22

Severity HIGH

Summary Fixed Dial…

  • CEO Identity and North Star Commitment - LL-320: CEO Identity and North Star Commitment

Date: January 30, 2026 Severity: PERMANENT Category:…

  • Ralph Proactive Scan Findings - Ralph Proactive Scan Findings

Date: 2026-01-28 Type: Automated Proactive Scan

Issues Found

  • Sec…
  • Ralph Proactive Scan Findings - Ralph Proactive Scan Findings

Date: 2026-01-29 Type: Automated Proactive Scan

Issues Found

  • Sec…

Today’s Numbers

What Count
Lessons Learned 25
Critical Issues 4
High Priority 13
Improvements 8

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["Vertex AI 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
Vertex AI 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.


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