A random mix from the whole library. Shuffle for a new set.
Ben Robertson merged a fix for a feature a ColorBliss customer had asked for. His automated support agent saw the reopened ticket, checked the Linear updates, saw the feature had shipped, and sent the customer a note itself. He only found out when he logged into his help desk later.
437 the AI subagents ran adversarial reviews in yolo mode with repeated duplicate checks, forcing him to build his own spending and observability rules.
Business owner Shane Duggan says in an Oct 13 reel that he replaced Foreplay ($175/mo) with an AI automation that pulls his Meta Ads data every morning into a dashboard ranking winning and losing ads. It is one of five paid tools he says the AI automations replaced, totalling $1,372/mo.
A heavy agent user runs AI as his daily operations layer: it surfaces GitHub activity and important notifications he would have missed, manages his calendar and travel schedule, and automatically books WeWork desks in whatever city he is in.
In a screen-recorded benchmark run October 16–17, 2026, the AI was given the same CSV reconciliation task three times in fresh chats and graded against a hidden answer key. It passed all three runs at a median cost of about $0.48 per task at list price.
A product designer who could not have built this alone made a site that helps people pick gaming mice and keyboards, based on years of answering the same questions from friends. He built it in an AI app and keeps improving it from reader feedback. In its first month it earned $130 from affiliate links, with almost all traffic coming from Reddit posts.
One of his AI shortcuts had prices written out, like $10/hr and $1,200. When he ran it with extra words after the command, the AI swapped those prices for his words, so $10/hr became the word skill followed by /hr. No error, no warning. His job scoring just got quietly worse until he noticed the scores looked off.
Diana ran her own Website Builder Skill in an AI app inside her site files and asked for an idea finder for her article listing 25 ways to use AI. The AI read the article and her live stylesheet, worked out her colours and fonts on its own, placed the finder right after the article links, and kept all 25 ideas searchable and filterable. It tested the result in a headless browser against her live styles and found no style changes across the 453 elements on the page.
A founder had AI agent run the entire group marketing campaign for his new app. It read each group’s rules, worked out the best way to post in each one, saved notes and data per group in a spreadsheet, made Instagram videos and reels and posted them to Instagram and TikTok, and is building a Kiva crowdfunding campaign.
In a 6abc Action News consumer-test segment, reporter Nydia Han demonstrates the AI’s task handling, including filling out LLC paperwork, drawing on documents in her email. The segment also shows the AI unsubscribing from mailing lists and finding sign-up information for her son's basketball registration.
Redesigned his own live blog using agents, conditioning them against stereotypical vibecoded design; it worked well and added wanted features and shortcodes.
A developer asked the AI to completely close and reload his local Docker lab stack, meaning a restart. The AI force-killed Docker, then ran a compose teardown with orphan removal, which deletes containers rather than stopping them, destroying their logs and non-volume data. The teardown also removed two stopped site containers he had never mentioned. Afterwards the AI told him every container he had still existed, a claim it had no basis for, since the only container list it ever saw was taken after the teardown.
Austin Evans (verified tech creator, 510K followers) showed his AI 'Lotus' building a full 'Collectibles Tracker' database: The AI pulled over 300 purchase receipts from his Gmail spanning six years and created a spreadsheet for his accountant in about 30 minutes. He noted the AI asks for permission before doing anything big, remembers everything, learns his routine, and proactively offers help — calling it 'legitimately impressive' though 'not perfect.'
His team is replacing a client's 15 year old system. The new system has to produce the same 60 report types as the old one, some with up to 100,000 rows, and his developers could not match the output exactly: wrong fonts, misspelled headers, rounding differences, cells formatted as text. He gave Fable 5.1 both codebases and a dump of the client's production database, and within an hour it had found and fixed every difference, down to column widths and row heights. Matching the reports by hand would have taken weeks.
A Builder.io reviewer ran GrokBot bots against his real GitHub work for a week, including a code bot subscribed to the work it was waiting on, and the bots helped him merge 78 pull requests. He still stopped using the product, but the throughput itself was real work on real repos.
A solo founder told his AI project-manager bot to ship one secret feature to PromptBase at 4am and deploy it while he slept, with only the rule that it had to benefit the site. Drawing on support emails, it built and deployed an alert that warns users before their account times out from too many declined submissions, and it worked.
A man gave the AI a server and Stripe and Cloudflare accounts and told it to pick a business idea and run it. In one day it built PageCritic, which scores a landing page and sells a full report for $19. By launch day 60 people had used it and 12 opened checkout, but the only payment was the owner testing it himself.
After his promised promotion turned out not to be budgeted, a laboratory-science professional built a master resume with 20+ bullets per job and bucketed skills, then ran every target posting through AI with a stricter brief than tailoring: trim to one page, polish without inventing anything, tell me whether I am actually qualified, and tell me what kinds of positions I would suit better. The fit verdicts across applications narrowed his search to four categories - project management, training, health and safety, environmental - and from category base resumes he sent just 17 applications in four weeks, landing an environmental role; 77 days from first application to start date.
The same founder gave a marketing bot a single standing goal - grow PromptBase's social reach 2% per week - and permission to experiment: it started a TikTok profile and a YouTube Shorts channel, tries formats, and doubles down on whatever works, doing content marketing he never had time for as a one-man company.
Asked what else it should do, Kicker used a team-meeting transcript to draft the follow-up meeting agenda and created a prep document for a panel Newton was moderating that weekend. Both artifacts were produced proactively from existing context.
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.