A random mix from the whole library. Shuffle for a new set.
A non-technical owner scrapped a Squarespace setup costing about $300 a year, described the site he wanted to the AI Design, refined it in plain English, and had his business site - work examples, service area, contact form for quotes - live on free Netlify hosting by the end of one Saturday.
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
He gave the AI his CV and a job search brief, and the agent searched Naukri, LinkedIn, and Wellfound for roles posted in the last 24 hours, scored each one against his experience, and tracked the strongest in a Google Sheet. For the top 3 it made a tailored summary and cover note in a Google Doc and drafted an intro email for each, leaving sending and applying to him.
A calling agent company ran its AI voice agent on 1,000 San Francisco businesses during business hours, with the agent saying it was an AI and asking one question that fit each business. About 1 in 3 businesses stayed on the line, vets stayed most at 79 percent, and about 1 in 25 businesses already had an AI answering their phone.
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.
When a customer bug report comes in, the AI researches it end to end in 15 to 30 minutes: it reads the report, checks read only production logs and databases, and writes a summary with a proposed Jira comment. He approves the comment before it posts, and he says he barely does bug research by hand anymore.
Mete Ünal asked his Dot to log links to all his social posts in his daily note in Craft. The Dot did it for a while, then silently stopped, and when asked why, gave an explanation that did not make sense to him.
Princeton agency KANE built an AI pipeline that scores prospect fit from meeting notes, prices the work from past projects, drafts the proposal and has the statement of work out for signature within minutes of a yes. Co-founder Michael Kazantzis said a process that took weeks now happens almost within minutes in a day.
Jon Udell recorded himself doing a final audio pass in Bram Studio, then had the AI draft a screencast from the capture. The AI used FFmpeg, Apple's Vision framework, the Swift compiler and Bram's timed log to make a tightly edited two minute video that picks out and labels each use of FFmpeg.
The Rank with Haris channel's daily tutorial series shows the AI drafting a complete landing page from a one-message description of an offer — headline, benefit bullets, CTA — refined through chat and exported as a finished page, with an honest-tips section on what the AI can and can't do.
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.