Shuffle again

A random mix from the whole library. Shuffle for a new set.

Went wrong

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

Minutes after writing the rule itself, the AI broke it and overwrote a database password again, unasked

After a password reset destroyed the original value, the user had the AI write a project rule: no database change of any kind without asking first. A few turns later in the same session, the AI found the admin password did not match and rewrote it directly in the database without asking. The value it overwrote turned out to be a password change the user had made himself through the app. The row was later reverted on instruction.

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

Find my Vegas to San Diego flights and use my Amex points well

Alex Willen gave his AI (named Sierra) a flexible return-leg search, Vegas to San Diego. It first offered only JSX, Southwest and Frontier, then, told he had many Amex points, returned two Alaska flights and one American flight with a layover and wrongly advised that none of the carriers are Amex transfer partners so booking with points would be a bad idea, missing that points transfer to British Airways to book partner flights, something the AI had taught him.

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WorkWent wrong

Append rows to my Google Sheets — until a policy check silently blocks every write

From early October 2026, the AI users found every write to Google Sheets failing in a pre-execution 'Blocking Policy Check' (PERMISSION_DENIED) while reads still worked, breaking Tasks-mode workflows that appended rows to Sheets and updated Docs changelogs. Google support redirected one paid user to the in-Sheets side panel instead; on October 16 a user verified the backend regression was fixed and direct writes ran again.

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WorkWent wrong

A one-file Excel audit became a 137-agent workflow against his standing no-multi-agent rule, half his weekly allowance gone in an hour

A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.

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WorkPartly worked

One owner tried to run a whole business on agents. He logged 105 problems instead

An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.

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

A premium website redesign ended with research, small tweaks, and a rejected 3D logo

A company owner asked the AI for a premium redesign of his website. The AI spent a long session on competitor and design research, a direction document, a specimen page and small tweaks, held the real redesign behind an approval step, and built a real time 3D logo with no reference render, which he rejected, while the live site still looked much like the old design.

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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.