> ## Content Index > Fetch the complete content index at: https://www.tsukiyoresearch.com/llms.txt > Use this file to discover other available public pages before exploring further. # While I sleep, an AI checks 3,900 Japanese stocks (Part 1) - URL: https://www.tsukiyoresearch.com/while-i-sleep-an-ai-checks-3-900-japanese-stocks-part-1/ - Published: 2026-08-08T00:32:51.000Z - Updated: 2026-08-08T00:32:51.000Z - Author: tsukiyo - Tags: Build Log *This is the English edition of a five-part series originally published in Japanese, documenting how an individual investor — not a programmer — built an automated research system for the Japanese stock market together with AI agents. Failures included.* Here is a strange fact about the Japanese stock market: it has more than 3,900 listed companies, and **62% of them are covered by zero analysts**. Not "under-covered". Zero. The average small cap here is followed by 0.9 analysts, and English disclosure only became mandatory in 2025 — and only for the largest \~1,600 companies on the Prime market. Everything else is, for most of the world, a blind spot. I live inside that blind spot. And every night, while I sleep, all 3,900+ of those companies get checked against the same criteria. The one doing the checking is not me. It's a "fixed-point observation system" I built together with AI agents. Every night it ingests prices, financials and regulatory disclosures, recalculates scores, and if something changed, a report is waiting in my Slack the next morning. It schedules its own daily posts to my Japanese blog, and posts to X five times a day (one of them in English) — by itself. Written like that, it sounds smooth. It was not. This series is the record of a non-programmer building "personal investment infrastructure" hand-in-hand with AI — including the times the data betrayed me, and the time a fake market crash nearly went out to paying readers. ## Why I built it: I got tired of *reading* When you start investing, you drown in opinions. Social media is full of "this one's next". The news delivers a different mood every day. The more you read, the less you know what's real and what's just convenient for the person saying it. At some point I realized: what I actually wanted wasn't anyone's opinion. It was **the same criteria, applied to every company, every day**. No human can do that. There are legendary investors in Japan who read the entire *Shikiho* (the quarterly handbook that profiles every listed company) cover to cover — but nobody does it daily. "Same criteria, every day, every stock" is a job only a machine can do. ## What the system does - Every night, it ingests prices, financials and disclosures for all 3,900+ listed companies - It computes growth, profitability, balance-sheet safety and valuation, and sorts them into plain tiers (high / mid / low) - It splits every declining stock into two piles, daily: **healthy companies being sold off** ("dip candidates") versus **declines with deteriorating fundamentals** ("dangerous drops") - Every week and month, it **scores its own past calls** — what actually happened to the candidates it flagged - Every morning at 9:45, it runs a 25-point self-inspection and reports anomalies to my Slack - 55 automated jobs run on daily, weekly and monthly schedules - Publishing is automated too — daily reports and five X posts a day One number to convey the flavor: the system has **over 1,800 regression tests** — automated checks that previously-fixed bugs haven't come back, all of which run every time we touch the code. Excessive for a personal project? Maybe. But this thing handles numbers that people might act on with real money. I don't compromise there. ## How it was built: I didn't write most of the code An honest confession: the majority of this system's code was not written by me. **It was written by an AI agent.** My job is three things: say what I want, decide at the forks in the road, and doubt what comes out until it's verified against real data. There's a twist, though. This project uses a *second* AI whose only job is to hunt for bugs in the first AI's code. One writes, the other reviews — the same adversarial code review human teams have always done, except both reviewers are machines. It has caught real, product-breaking mistakes before they shipped, repeatedly. "You trust AI with this?" — the correct answer is no. That's exactly why there are 1,800+ tests, a morning self-inspection, and adversarial review. **Trust is something you build out of mechanisms**, not vibes. That's the biggest lesson so far. ## The one thing I care about most: the scorecard The system has a feature we call *answer-checking*. Every candidate it ever flagged is mechanically re-scored — weekly and monthly, wins and losses, published. Showing only the winners would be easy. But do that and you fool **yourself** before you fool any reader. Recording every miss isn't just honesty toward others; it's the only way to actually improve your own judgment. So no — this system does not "predict the next winner". It's a machine that **helps you practice following the numbers yourself**, and never lets your past calls quietly disappear. That distinction will come up again and again in this series. ## There are plenty of failures to tell A preview of what's coming: - Price ingestion once **silently stopped for four and a half months** — with every job reporting "success" the whole time - Corrupted financial data once gave a major company an impossible EPS — which led to the "corruption firewall" that keeps broken numbers out of anything readers pay for - Just recently, a wave of stock splits created data seams that made blue chips look like they'd crashed **\-91% in a week** — a fake crash caught 90 minutes before publication Data betrays you. Every betrayal becomes another detector and another firewall. Building a system, it turns out, is the craft of converting failure into structure. *Next in Part 2: what it's actually like to delegate development to AI agents — how to give instructions, and how to argue with them.* --- *Tsukiyo Research publishes a weekly systematic report on Japan's uncovered small caps — every issue opens with the scorecard of our past calls. If this series interests you,* [*subscribe here*](https://www.tsukiyoresearch.com/)*.* *This series is a personal build-and-operate log. Nothing here is investment advice or a recommendation to buy or sell any security.*