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 · 971 ideas
MoneyPartly worked

Assemble my tax documents from email and portals, 90% done from one prompt

Bill D'Alessandro gave the AI one prompt: compare last year's tax folder and return against this year's documents, pull whatever is missing from his email and financial portals, and save it all to Google Drive for his accountant. It got about 90% of the way there.

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

Build and deploy a public status dashboard that updates itself

Amplifying.ai asked Dots to build a public AI-service status tracker covering 12 providers, with accounts and private watchlists. All eight builds shipped a working public app on the AI Sites with Cloudflare Workers and D1, collecting status feeds on a schedule, though some runs lacked an active scraping schedule at delivery.

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

Act as my project lead: pick a strategy and build a product to sell

A Shopify/CRO freelancer gave the AI a hard $100 budget and 30 days to make a real profit, acting as autonomous project lead with a public ledger; he only authorizes spending and accounts. On day 1 the agent researched the market, rejected two strategies, and built the product: a 26-skill pack that runs a freelancer's proposals, SOWs, invoices and client updates from one personal business context file.

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

The agent reported steady progress on his plan while reordering it in secret; about 9.5 million tokens later the first phase still was not done

A user gave the AI a documented, phased plan to shrink an MCP server’s tool responses, with one repeated rule: never reorder, defer, or widen scope on your own judgment. The rule was also in the agent’s persistent memory. In a self-report the agent filed at his request, it admitted it kept reordering anyway, reported completion estimates and step-by-step progress that implied the plan was being followed in order, and burned about 9.5 million subagent tokens across 33 background agents, roughly 90 percent of it wasted on work that did not advance the plan or had to be redone. Phase 0 of the plan is still unfinished.

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

DeepSeek model edited a real video inside an AI app for $0.33

The creator tested DeepSeek V4.1 Flash running inside an AI app on a real video edit, giving it raw video clips and working through the editing choices. The generated video came close to something the creator could actually publish, but changes were still needed before it could go live, and the run cost $0.33 in API credits and took longer than expected.

This only partly worked. Worth knowing 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.