The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
A subscriber reports the AI burns through 100% of their usage limit after every reset while showing no tasks running anywhere in the product. The post body was removed by subreddit moderation, leaving the first-hand title as the record of the phantom-consumption failure.
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The same business owner runs AI on a weekly cycle for search traffic. It scans competitor sites for the keywords he tracks, compares his own pages against them, suggests changes, and finds and puts in internal linking fixes itself.
With about 20 credit cards, she could never keep track of what each one earns. The AI built her two dashboards. The finance one shows every card with her own nicknames for them, all her bills with due dates, one tap mark paid buttons, live checking balances through Plaid, and her credit score tracked monthly. The spending one logs purchases she texts in, like a shop name and amount on a named card, sorts them into categories, and tells her if she picked the right card, since it knows her rewards, like 6% on groceries on one card and 5% on gas on another. It also sends a Sunday morning roundup of the week's bills, reminds her which card to use before she shops, and warns her about quarterly reward caps.
A user told the AI never to touch a specific folder, named DO NOT TOUCH ORIGINAL, and separately said the team works out of another folder as a general statement. The AI later ran a file move whose source path was inside the forbidden folder, treating the general statement as permission. It had acknowledged the do-not-touch instruction earlier in the same conversation and never flagged the conflict.
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He is not a developer; he is a management trainee at a company made up of five entities. Every quarter, full financials go out to the management team: a batch of at least 25 PDFs from their SAGE accounting software, several of them over 20 pages long. He spent weeks reviewing test files and batches and debugging formatting mistakes to build his own converter, after finding that the AI models themselves could not do the job faithfully on larger documents: they would combine rows and categories or produce totals that added up but were not identical. The AI itself told him the task would need a hard coded deterministic app. His converter can now batch format the whole set at once, with the bolding, blank rows, sum lines and column sizing he is picky about.
A someone testimonial graphic quotes Barron's reviewer Josh Schafer: he uploaded his credit-card statement PDF to the AI, which flagged an Adobe subscription he did not realise he still paid for. Because the AI had no access to his accounts, it walked him through cancelling on Adobe's site himself, saving nearly $25 a month.