Guardrails.
The expensive mistakes came from process gaps, not the model. These are the guardrails that close them.
Posts here are the site's slower layer: the guardrails you keep. The checklists and frameworks that decide how AI fits into a decision, and where it doesn't get a vote. Less what I ran this morning, more what I run every time. Want the quick version? The seven paste-in checks live in the guardrails toolkit.
That includes the whole method in four questions, run end to end on one everyday example, and how to tell if an AI answer is true in 30 seconds. It also covers the money decisions: the five questions I put to AI before buying any stock, the thesis audit I run before selling, and why most AI tool comparisons end in verdicts you can't act on.
The common thread: the discipline matters more than the model. The expensive mistakes in my own record came from process gaps, not tool gaps: holding through an earnings release with no written sell trigger, buying without a thesis I could state in three sentences. The guardrails here exist to close those gaps. The AI checks the work; the checklist makes sure there's work to check.
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How to tell if an AI answer is true in 30 seconds
Two questions, and a prompt you can copy, that catch a confident, wrong AI answer before you act on it. No jargon, no AI knowledge needed.
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Make it show its working
An AI hallucination is a model blending what it knows with what it invents, in one tone. One prompt sorts the two into separate lists, so you see the guesses.
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The whole method, in four questions
The four questions I run any AI answer through before I trust it, shown end to end on one everyday example, with a prompt you can copy. No jargon.
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Where I actually use this
The two-question check works on any decision that matters. Here's where I push it hardest, and where I wrote down what AI got wrong as well as right.
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The AI prompt I run before every sell decision
Every other sell-decision prompt asks AI whether to sell. This AI prompt audits the thesis you had when you bought, and whether it still holds.
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What every AI stock research comparison gets wrong
Most AI stock research comparison pieces test retrieval and issue verdicts about reasoning. Five failure modes, and what a comparison should measure instead.
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AI covered calls: when NOT to sell another one
The AI doesn't pick the trade, it stops you making a bad one. Five rules that say wait, the prompt that runs the check, and six real trades behind it.
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AI's limits in options trading: 6 numbers it invents
The limitations of AI in options trading: it can't see live prices, so it invents them. Four jobs it helps with, six where it makes the numbers up.
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5 questions to ask AI before buying any stock (2026)
Five questions to ask AI before buying any stock, for the hour before you commit capital, when the research is done and the decision is about to be made.
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