Loop Attractors Across Three Prompts | Generated by AI

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Here’s the analysis of all 3 new prompts:


PROMPT 8: DIGITAL BANKING PLATFORM

Input: 70 words. Digital banking in SE Asia, 12M customers, $14.6B payment volume, NIM 3.2%.

Generated output (first ~400 tokens):

Key failure: Loop attractor on “Net interest income [direction] $X million, or N%”


PROMPT 9: MUTUAL FUND OPERATIONS

Input: 75 words. Asset mgmt division, 147 strategies, $89.4B AUM, $6.2B inflows, 18.4% return.

Generated output (first ~500 tokens):

Key failure: Mode collapse into table generation + “Cash and” repetition sink


PROMPT 10: FINANCE LEDGER ADJUSTMENTS

Input: 73 words. General ledger platform, 45K journal entries/month, 340 entities, maker-checker controls.

Generated output (first ~500 tokens):

Key failure: Strongest loop attractor of all 3 — “$0.X million in sales and” dominates entire output


SUMMARY ACROSS ALL 3

Pattern Prompt 8 (Banking) Prompt 9 (Mutual Fund) Prompt 10 (Ledger)
Input echo quality Excellent Excellent Excellent
First continuation Good Contradicts input Good
Loop phrase “Net interest income” “Cash and” “$0.X million in sales”
Domain drift Banking stays Drifts to balance sheet Sales/rev stays
Table generation No Yes (full balance sheet) No
Scale consistency Collapses to $1-31M Plausible but wrong Collapses to $0.1-0.7M
Numerical logic Same year vs same year Internally inconsistent No logic, just repetition

All 3 follow the same pattern as the original 5 prompts: strong echo, rapid loop attractor, scale collapse. The finance ledger prompt (10) has the most extreme repetition — the model found “sales and $0.X million” as an even stronger attractor than the bank-related prompts.


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