A random mix from the whole library. Shuffle for a new set.
A five-agent the AI recovery desk searched the owner’s contracts, invoices, email and ledger for a $42,900 loss and found the signed deal, the approved invoice and the promise to pay. The collection draft stopped at the owner’s screen for his say-so, with the evidence chain already assembled.
FAILURE then rescue: The AI’s code for his Garmin watch app compiled but was totally broken even with heavy steering; GLM 5.3 Flash then made it work.
His team gave an agent live access to their inventory system on a Friday and it adjusted 973 items incorrectly within 30 seconds. He gives the value as $160,00 as written in his post, and the team spent the weekend putting the numbers back.
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.
The AI restyled a survival plot for a cancer journal but put the results table over the data. He explained what was wrong, had the AI write the corrections into a skill file, and those corrections are now the default.
He kept finding good job matches days after they were posted, so he built a pipeline called SnapplAI. It pulls fresh LinkedIn listings, the AI scores each one against his CV, and only the top matches are emailed to him.
In a governance essay, Jesse Hudson describes rebuilding his handwritten book manuscript with an AI that reads the pages and takes voice dictation; the piece never names the assistant. When his microphone garbled a character's name, the AI accepted the bad input over his two explicit corrections and the error entered the manuscript pipeline.
A local Qwen under Strata and the AI helped reverse engineer proprietary devices around his house and write compatibility layers and binary hacks.
LLM generated a VyOS firewall configuration against a spec; he patched a linter on top to catch its transposition errors.
Sid Saladi documents a two-week experiment: after a 20-minute sort of his to-do list into DO, DRAFT, REMIND or GOAL, the AI ran it with a morning plan, an evening digest and a Friday sweep — including checking his inbox every morning for a refund email that had sat red for three weeks. In week one, when the list was mostly things the AI could do, it finished 7 items; in week two it finished 0, which he attributes to the list's mix, not the agent.
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.