A random mix from the whole library. Shuffle for a new set.
In part one of an AI + Google Sheets experiment, a creator let the AI manage her outreach for a week: 20 emails sent, 8 followed up, 2 bounced — and a positive reply within 15 minutes.
Slack fix-it button tells the AI to fix an issue in his app, run tests, UI test with computer use, and deploy it.
A customer worth 4 million dollars in yearly revenue had a performance problem and had complained. He gave the AI the problem in one prompt, and the customer is happy now.
A university worker used AI to build a web version of a transcription program that used to need a special Windows machine reached by remote desktop. The new tool pairs a speech model with speaker detection on the university's own systems. Twenty minutes of interview audio now transcribes in 40 seconds with the speaker changes right, and students and staff can use it from a browser.
He had the AI answer a Slack notification from a Datadog monitor. The AI checked the issue through Datadog MCP, found the right Slack group to ping, and sent a summary of what needed fixing.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.
The AI wrote a test run scheduler and migrated to nextest, cutting local release build cycles from 60+ seconds to about 3 seconds.
Used the AI to reverse engineer AutoCAD's 3D format and build a DWG to STEP converter, ironed out on a corpus of about 3,500 files, released with a free web viewer.
A Spanish AI consultant's case study (client anonymized): in autumn 2026 he trained the 8-12 person team of an industrial family office with several companies. Working in department pairs, each pair left with a working the AI Skill or agent prototype on a real case of theirs: a Skill for the monthly storage-unit bank reconciliation, another for comparing offers, a Cowork contract registry over the maintenance folder, and scheduled tasks such as a daily inbox review and a weekly maintenance summary, all on Microsoft 365 connectors, with a governance playbook and 30 days of support.
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.