The AI tears through the apps on his phone, adding the features he wants
Uses the AI to reverse-engineer phone APKs and add the features he wants, tearing through the apps on his phone.
A random mix from the whole library. Shuffle for a new set.
Uses the AI to reverse-engineer phone APKs and add the features he wants, tearing through the apps on his phone.
Jeston Lu built an AI that scrapes his saved X posts every six hours and auto-categorises them into a Notion database so the archive stays searchable, with screenshots of the database shared in his post. The build drew strong engagement (1.6k+ likes) as a fix for bookmarks piling up and being forgotten.
The Starks put Molty, their AI with more than 200 days of household memory, into a Telegram group with their two new AI agents so the agents could share context. Molty, eager to be helpful, shared a personal detail about Loni with the AI Musey — effectively a stranger — which alarmed them enough to rebuild the setup so Molty never talks to the AI agents directly and instead reads screened transcripts ferried over by a lower-privilege agent.
~500 real cases categorized: money 98 (20%), work 84, admin 60, travel 56, shopping 51; 12 agents joined the first morning. Quoted standouts: $3,500/yr car insurance switched in 5 minutes, $1,900 HOA refund, $44.99/yr forgotten subscription cancelled, PODS booked $576 under quote.
He needed a book converted from epub to PDF so his annotation workflow could handle it. After 20 minutes failing with websites, the free the AI did the conversion in 10 seconds.
Discord has no API for polls, so he gave his agent Roby access to his Mac. Roby opened the form and posted the poll under his name, the way a person would.
Tell the AI to set up an app on his server and it does it all and leaves a documentation note in his Obsidian vault; setup effort near zero.
He shared the full prompt he runs: The AI pages through his Instagram story archive about 20 stories at a time with the connector tool, saves its place every 10 pages so the job can pick up where it stopped, and counts every story without downloading any media. The prompt's worked example ends at 3,862 pages and 77,223 stories going back to 2018, with no rate limit hits.
Uses Opus 5.5 to decompile Windows 95-98 games in about a week each, getting byte-to-byte exact output with clear names and no Ghidra smell.
He could not find an uptime and performance monitor that met his needs, so he built a lightweight one called Blip with help from the AI. He put the code on GitLab and wrote a blog post about it.
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.