Latest Articles
These 21 original articles form the LuckyToKnow AI launch evidence library: a deliberately bounded first collection of controlled tests, synthetic datasets, public-source analyses, workflows, and safeguard frameworks. New work will follow at roughly two or three manually reviewed articles per week; nothing is published automatically.
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A Reproducible Benchmark for Testing AI on Financial Questions
Thirty synthetic questions, a fixed rubric, and a scored result that rewards correct caution as well as arithmetic.
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Agentic AI for Money and Business: What It Can Do and What Still Needs a Human
An 18-task capability and risk matrix that separates automatable preparation from consequential approval.
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How to Verify an AI Update Before Changing a Money or Business Workflow
A ten-check release-verification method applied to the current OpenAI tool documentation, with a stop/go decision tree.
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A Privacy-First Way to Categorize Expenses With AI
Forty synthetic transactions compare unredacted and minimized inputs, including the accuracy cost of removing identifiers.
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I Tested AI on a Variable-Income Freelancer Budget
A Tunisia-oriented synthetic 12-month budget shows where a fluent plan helps—and where it misses seasonality.
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Why AI Stock Picks Can Sound Convincing and Still Be Wrong
Fifteen fixed market claims reveal stale facts, missing time stamps, and fabricated certainty without making a recommendation.
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Can AI Summarize an Annual Report Accurately?
A claim-by-claim audit of a public Form 10-K summary shows why citations need section-level verification.
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Can AI Spot a Financial Scam Message? A Controlled Test
Forty synthetic messages expose false negatives, false positives, and the danger of treating a classifier as a guarantee.
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Building a Cash-Flow Forecast With AI Without Trusting the Numbers Blindly
A synthetic 12-month case separates formula accuracy from assumption risk and tests three scenarios.
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AI Invoice Categorization: A 50-Transaction Accuracy Test
A synthetic small-business dataset shows 88% exact-label accuracy and six errors that still require review.