A random mix from the whole library. Shuffle for a new set.
Three days into AI Duet, the time saved came from it acting first. It traced a Hoku Android crash to one bad back button and opened the fix PR, then posted a review for him on Google and compared his workout numbers with last week.
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
Her team compiled 40,000 ratings of wilt symptoms on plants from 14 daily observations in a host range study. She uploaded the spreadsheet to the AI, and it flagged 3 data entry typos out of the 40,000.
Creator Amie Tollefsrud gave the AI access to her Instagram analytics and asked for growth advice; after three clarifying questions about audience and positioning, the AI delivered an 'Instagram Growth Plan' PDF. Screen recordings show an executive diagnosis (1.85M accounts reached), audience positioning, four content pillars, keyword clusters, carousel and story blueprints, and a 7-day action checklist.
A corporate salesperson who cannot code keeps all his customer files in one folder that the AI reads directly. Before a meeting it pulls out up to three things to check, and after a meeting it turns his voice memo into minutes and a thank you email and files them.
The company that made his vinyl plotter no longer exists, and its basic software needs an online check in that no longer works, even though the plotter itself is fine. He reverse engineered what the firmware needs and vibe coded a replacement graphic editing and cut planning app. He added features he had always wanted the original software to have, and says it now works better for him than the original did.
Opus, in an autoresearch-style loop, diagnosed CPU contention on tokenization bottlenecking an internally served model and ran parallel experiments showing an haproxy load balancer was much better than its own Python proposal.
Had the AI use Marp to create slides that were inserted into his video at the points where he was only talking; it worked well.
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.
He runs all the steel on a large construction job. The AI builds him a packet for each item from the project document database, and reads the specs and codes to work out which one takes precedence when they conflict. He says it saves him at least 15 hours a week.
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.