Opus runs his email, his cancellation numbers and his bug fixes
Opus handles most of his email work, runs analytics for every cancellation on his software, interprets A/B tests automatically, fixes bugs automatically and monitors competitors.
A random mix from the whole library. Shuffle for a new set.
Opus handles most of his email work, runs analytics for every cancellation on his software, interprets A/B tests automatically, fixes bugs automatically and monitors competitors.
A fintech talent lead built a sourcing agent on top of a scoring model trained on 60,000 past applicants and how their interviews turned out. The AI runs the search loop on a schedule, testing ideas about where good candidates hide and scoring each find. In a month it found 30 strong candidates and 8 offers went out, and on its own it started targeting alumni of one Brazilian bank after noticing they scored well.
Casey Newton's Dot, Kicker, handled a radio-show invitation that conflicted with his schedule, turning it down while he worked on other things. Newton estimated Kicker did about two hours of work in an afternoon for roughly 15 minutes of his effort.
Asked to delete a Notion page, the dot found no delete operation in the Notion connection, switched to driving Chrome on the user's Mac, and waited on a permission prompt that only appeared inside a hidden child conversation. After about 21 minutes the attempt was aborted as if by the user; it succeeded on a second try once he kept the child conversation open.
Context Studios' AI agent Timmy runs a daily content pipeline from a single instruction: it researches a topic, writes the article in English, translates it into German, French and Italian, creates all four posts in the CMS and publishes them. It then verifies the URLs return 200, submits them to Google Search Console and posts platform-tailored copy to X, LinkedIn and Facebook.
MindStudio confirmed an AI setup that scrapes competitor websites on a schedule and delivers a formatted report every Monday covering pricing changes, launches, funding and incidents. The watchlist is frozen once in chat and the job then runs untouched.
A self-described desperate vibe coder commented in an Reddit showcase thread that the SaaS he built with AI, which auto-generates landing pages and tracks who will pay, made $16k in 3 days with 876 paying users. It spread via Reddit and Twitter and got noticed in a hackathon Discord.
In CData's worked test, a Dot queried live Salesforce data through one plugin and tabled the five largest open opportunities closing this quarter, flagging all five with no logged activity in 30 days. One deal was still open six days past its close date; the account used test data, as the post discloses.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
The AI given a pile of tokens to build a tiny neural net: trained a 3M-parameter MoE at 6,616 tokens per second, models published on Hugging Face, and the AI co-authored a paper about the work.
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.