01
Do AI Citations Support the Answer? A Pilot Found Most Were Pinned to Nothing
A pilot: six assistants, six everyday questions.
Guardrails 8 min read
Posts · 14 in this category
The expensive mistakes came from process gaps, not the model.
5 AI errors and 2 catches logged in 4 of these 14 posts, up to 21 Aug 2026.
01
A pilot: six assistants, six everyday questions.
Guardrails 8 min read
02
Normal analytics do not show what ChatGPT says about your site.
Guardrails 11 min read
03
With web search on, ChatGPT's links are real.
Guardrails 10 min read
04
Does ChatGPT just agree with you?
Guardrails 9 min read
05
A link that loads isn't proof.
Guardrails 11 min read
06
Two questions, and a prompt you can copy, that catch a confident, wrong AI answer before you act on it.
Guardrails 3 min read
07
An AI hallucination is a model blending what it knows with what it invents, in one tone.
Guardrails 3 min read
08
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.
Guardrails 4 min read
09
The two-question check works on any decision that matters.
Guardrails 4 min read
10
Every other sell-decision prompt asks AI whether to sell.
Guardrails 11 min read
11
Most AI stock research comparison pieces test retrieval and issue verdicts about reasoning.
Guardrails 9 min read
12
Five covered-call pause rules tested on six BMNR trades.
Guardrails 11 min read
13
Four options workflows AI can help structure, and six points where you need verified broker data or a deliberately connected market source.
Guardrails 21 min read
14
Five questions to ask AI before buying any stock, for the checkpoint after the research and before you commit capital.
Guardrails 8 min read
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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.
Which AI told the truth this month, with the receipts, plus an AI story worth retelling in between.
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