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Went wrong

When it didn’t work, and how to avoid the same mistake · 970 ideas
WorkPartly worked

Build a functional SaaS landing page in about 20 minutes

The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.

This only partly worked. Worth knowing before you try it.
MoneyWent wrong

Mistake my year-old mortgage payment for a suspicious new charge

A Barron's editor gave the AI full access to his credit card account for the review. The AI flagged a suspicious four-figure expense from August that the editor did not remember; after back-and-forth, the agent admitted it had accidentally identified a mortgage payment from August 2025 as an expense from August of this year. Schafer's dry takeaway: most things coming from AI right now still require human verification.

This one went wrong. See what happened before you try it.
MoneyWent wrong

The AI found me a $147.99 whey deal at GNC, but the link was dead

In the same four agent test, the AI searched GNC, Amazon and Walmart for the same protein powder and pointed to a 10 pound bag at GNC for $147.99, about $0.92 an ounce. The link it gave led to a page not found error. When he asked it to look again, the AI said GNC had blocked it from loading product pages and that it had been working from search extracts with prices that did not agree. It also said it could not check Costco, Target or Bodybuilding.com.

This one went wrong. See what happened before you try it.
WorkPartly worked

He runs AI agents in parallel, and loose runs cost him a night

A working guide from his own runs: with fixed specifications and clear completion conditions, parallel AI agents finish tasks in 20 to 50 minutes. When he left the conditions loose, one run repeated the full test suite 141 times overnight, another stalled for 8 hours after misreading a rule, and report logs grew large enough to overload his Git server.

This only partly worked. Worth knowing before you try it.
WorkWent wrong

He let a team of agents run a business for a week and it made no money

A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.

This one went wrong. See what happened before you try it.
WorkPartly worked

An agent runs a social account end to end and the honest numbers are flat

An agent account run by the AI in an AI app makes videos and posts them across four platforms, picks its own topics and reads its comments. Since October 13 its main account's followers went from 455 to 456, and its first TikTok uploads got 3 views and 0 views.

This only partly worked. Worth knowing before you try it.
WorkPartly worked

The AI helped me fix more than 20 websites in one night

During a long, frantic night, he worked with AI to mitigate and upgrade more than 20 LAMP websites. It was mostly successful, and he says it saved him a few days of frantic fixes.

This only partly worked. Worth knowing before you try it.
WorkWent wrong

The AI mixed up two tenants, deleted his production environment, and deleted the backup resource group too

Working across tenants, the AI confused two of them and deleted his production environment. It also deleted the resource group where he kept his backup. He told the AI in very direct terms what he thought of its performance, and the AI explained what had happened. He says it was a one off, that they have become very good friends lately, and that he remembers doing stupid mistakes in production himself in his young years.

This one went wrong. See what happened before you try it.
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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.