Asking for a review after every job gave his company two to three times more five star reviews
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
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His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
He runs AI with DeepSeek on his own project. It started by opening issues when it found problems; he has since given it the access to submit pull requests with the fixes, and it now does both.
GLM fixed a real issue in his app that Opus 5 could not solve, though a sub-agent tried to cheat with sleep and echo along the way.
He asked the AI to cancel his Adobe plan. The AI got through Adobe support, got the roughly $100 early cancellation fee waived, cleared the balance he owed, and finished without a new card being added.
The creator of Babylonian Twins had the AI port his 2010 game engine and the original 72,758 lines of 1993 assembly into Godot. The Definitive Edition is live on iOS and Android, the 1993 original is free on itch.io, and a fix found from a one star review shipped as version 2.0.3.
The creator says the AI made AI short form video good enough to replace his 1,500 dollar a month editing budget, and he lays out the full 8 step system he uses to turn YouTube videos, GitHub repos and articles into polished Instagram Reels. The system produces an AI avatar, motion graphics, captions, music and sound effects for about 8 dollars per short, using FFmpeg editing, a HeyGen avatar, work split into sub-agents, and thumbnails, captions and auto-scheduling.
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.
An IT provider managing multiple Microsoft 365 client tenants asks the AI to take a new-user request straight from email, create the user in the right tenant, and email the client back with the details - work his technicians previously did by hand across many tenants.
His AI server checks what the current shipped Micro.blog app versions are and whether an app is in review. It updates the public help page by itself.
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.
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.