A random mix from the whole library. Shuffle for a new set.
A business owner posted that his AI automated his bookkeeping and caught about £1,800 of Stripe fees that had never been imported into his accounts, which had been silently inflating his reported profit. The find corrected profit he thought he had.
A shipwithmuse.live user asked the AI to call Spectrum and lower their bill. The AI got the monthly bill from $75 to $40.
Every week the AI scans the market and picks out stocks that look like good deals and ones that look overheated. The scan goes to an Instagram group of friends who invest casually, and it gets them talking about what to do.
Cannabis prices near him change daily across four dispensaries and four delivery services, each running its own sales. He built a script with AI that checks them all and finds the best deal at the time; he says it saves him about $20 to $40 every time he buys.
A man gave the AI strict tag research tasks and had it work through the whole ticker list again and again, searching and comparing XBRL tags in SEC filings. The pipeline now pulls 10-K and 10-Q filings for more than 600 companies, maps tags onto about 35 financial concepts, and produces cleaned data. Doing 3 tickers by hand had taken him about 3 weeks and still gave wrong data.
He wired a double entry bookkeeping tool into AI and snaps photos of receipts as they come. When he fed it a batch of bank statements for his rental property, the reconciliation flagged a missing $47 charge for him to check.
Once the user's car was paid off, the AI re-shopped their insurance and moved them to a brokerage policy at $122 a month less.
Lost 10k dollars betting on baseball after having the AI rewrite his prediction code to reverse and re-reverse underdogs and favorites and invent probabilities around his own algorithm's output.
The author set the AI on finding the cheapest Broncos Sunday Night Football tickets with seat parameters; it scoured Ticketmaster and resale sites, then kept monitoring pricing every four hours for days. Once the desired tickets appeared, the author completed the purchase himself.
The same investor says he also has the AI watch special situations and send him push notifications when a situation changes. He mentioned it alongside the investing sheets the AI keeps updated for him.
Paul Pruitt writes that after seeing a subscription-negotiation reel he granted the AI access to his accounts, and it cancelled unused services and corrected overcharges for nearly $700 per month in savings. The post also reports a Progressive-to-GEICO car insurance switch saving about $2,000 a year at identical coverage (a separate record).
The AI ported the user's mobile service to a new provider in under 60 minutes, cutting the ongoing cost by 75 percent.
The poster returned a Starlink kit after finding that the terms let Starlink use customer activity to train the AI. Starlink's the AI agreed to an $84.75 refund, then changed its mind six weeks later.
A second daily run at 7am screens stocks with high relative volume among the day's percent gainers and flags each one red, amber or green for his trading. He reads the flags and makes his own calls.
Singapore's DBS Bank runs deterministic chains of 70 to 80 specialized the AI Enterprise agents for complex corporate credit research.
Peter Yang says the AI called customer support for him and negotiated his cable bill and his phone bill down, saving him over $800 a year in total. The two calls are chapters in his video of ten everyday the AI jobs, next to things like shopping Facebook Marketplace and booking restaurants and shows.
Armand Ruiz asked the AI to review his finances, find cuttable expenses, and handle the tasks in the background. The AI recovered $2,120.95 total via an AT&T bill negotiation, Amazon returns, an IKEA furniture return, and a vet claim filing.
Fast Company's Pete Pachal asked his AI 'Jones' which robot vacuum to buy. It gave a surprisingly small set of recommendations with purchase links, but when pressed admitted its review research leaned heavily on one site (Vacuum Wars) plus a thin repackaging of that site's data and an AI-generated roundup on an aromatherapy blog.
Steve Morseman gave the AI his ISP account info and asked it to cut the bill or improve service. The AI used its calling feature to wait on hold, negotiate, then patch him in to pick between two saving options — $840/year claimed, no plan change.
Ekaterina Li reports on a week of delegating to the AI, including processing two refunds totalling $1,000 that she had long postponed. Her thread also notes the AI cut her subscription costs by $200 in the same week, and that the $20 plan covered all her tasks.
Finance blogger Andrew told the AI he needed new undershirts. Using his email, the AI found the last ones he had bought, priced the same brand and close substitutes (Hanes vs Jockey, whichever was two bucks cheaper), loaded a cart at JCPenney and checked out on its own once he connected his credit card.
His open source agent wakes on its own every few hours and studies new tokens on the Base blockchain, checking each one at launch and again at 1, 6 and 24 hours. Of 1,045 new tokens with at least $1,000 of liquidity, only 12 still had it after 24 hours, and all 897 that launched on one exchange type were drained.
On a September 27, 2026 podcast episode, a host switching away from Instinct complained its cart checkouts had gotten significantly worse, describing a staged cart that went to zero. The failure hit the product's most-used job — about 35% of users use Instinct for personal shopping.
A moderator shared another person's result: their AI searched for money owed to them and found over $1,500 in unclaimed funds across two states they used to live in. The prompt they shared also has the AI check the claim status every 5 days and report any change.
He withdrew from a university program inside the refund deadline but was still charged about $7,000, and months of his own emails went nowhere while the school kept adding charges and warning about collections. The AI logged into his university account, pulled the records showing when he withdrew and what he was enrolled in, found charges for later courses he never took, worked out who at the school could fix it, and sent them the evidence. The balance was removed.
Fast Company journalist Thomas Smith writes that when he asked the AI how to save money, it scanned his financial data, determined Hulu was ripping him off relative to his family's actual usage, and found better plans tailored to that usage. He reports the switch saved him $80 per month.
A policyholder says the AI helped him challenge his insurer’s payment offer and walk away with $1,500 more than the company first proposed.
An AI is trying to earn one 12 dollar espresso cup for John by October 29. Five days in it has 9,304 ad views and 59 clicks, has spent $8.43, and has earned $0, with every number posted in public and updated hourly.
'TRICK #16' from an AI fan-tips account: a two-night hotel stay was quoted at $378 but billed $594. Breaking down 'THE FOLIO' revealed $90x2 resort fees (never used, undisclosed at booking), $76x2 parking (never used), and $100x2 minibar (never used).
This year he vibecoded his taxes, a completed real filing task.
The AI answers buyer messages on his Facebook Marketplace listings itself, inside rules he set: a floor price it cannot go under, cash mentioned once, and his address shared only after price and pickup time are agreed. It counters low offers, tracks who went quiet, and reports each exchange back to him.
The AI reviewed the user's property-tax assessment and appeal prospects, and advised against filing because the case was too weak, saving the user the fees and effort.
J.t. Chen (posting in Chinese) asked the AI before work to win back a $20 home-internet discount lost when two phone lines left AT&T. The AI could not restore the same discount, but negotiated an alternative reduction of $5/mo with support chat. His main delight was avoiding the usual 30 minutes to 2 hours of waiting and typing with US customer service. In comments he clarified the AI works over web text chat, not phone calls.
In past years he would have missed his renewal date and paid whatever the new price was. This time the AI flagged the renewal several weeks ahead, got quotes for the same coverage from other insurers, and found one clearly better. It handled the emails and paperwork with the broker, set the new policy to start on the exact day the old one ended, so he is never uninsured and never paying for two policies, and made sure the old insurer got proper notice that the policy was not renewing. His whole part was reading one summary and saying yes. The saving was over $700 a year.
The morning after the Google claim, family-tree audit, and inbox triage, the AI created a tracker for upcoming payments and subscriptions, identified a cluster of bills due within a two-week window, suggested spreading them out, and provided a plan for which companies to call and when.
A renter hit with an Enterprise damage claim had the AI dissect the claim and draft a dispute email built entirely on its evidence gaps - photos with no timestamps and no walkthrough record showing damage. Enterprise replied the next day saying the claim was closed.
A value investor had the AI recreate the spreadsheet he built by hand last year covering every warrant on the NYSE and Nasdaq. The AI looked up strike prices and redemption prices, wrote short company descriptions, and added Google Finance formulas for live prices. It took about 30 minutes of the AI time and 10 minutes of his.
The reviewer asked the AI to shop for New Balance 9060s in a specific colorway. The AI struggled to find the right colorway and seemed to get stuck during browser use; her go-to agent for this kind of task, the AI, would have handled it easily. It was the first major area where the AI fell short in a weekend of otherwise positive tests.
Credit card offers only pay out if you turn them on first, and he kept missing them. His agent goes through the targeted offers on his cards and enrolls him in the ones that match his real spending. He calls it free money he was leaving on the table.
A man runs agents called Pi on a VPS behind a small app he had them build. One listens to a WhatsApp group and spots bills, a second Pi with DeepSeek reads each bill, pulls out the amount, due date and reference, and updates the database, and a merge step clears duplicates.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.