Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
His local LLM runs permanently as a Home Assistant agent with agentic access to his sensors, answering voice queries about his solar and battery data and creating automations.
He let GPT-6 Astra work on a few simple features. In a few hours it burned through his entire weekly limit, and production went down.
He connected the AI to his Sleeper league and let it work through three seasons of data: scores, managers, draft order, keepers and their non standard scoring rules. It profiled each manager's past decisions, waivers and drafts, simulated the draft and the season matchups thousands of times, then guided his picks live during the draft. Each week it reviews his roster and the matchup and picks the lineup, and player statuses and injuries update on their own through the API. He is 2-0 and put up the highest weekly score in any match by over 40 points.
Alex (AI investor) saw his AT&T promo expire and his bill rise to $95.28. He used AI to negotiate, dodged upsell traps during the chat, and landed $90/month flat — about $63/year saved in under 30 minutes.
After a fake Cloudflare page tricked him into infecting his own laptop, a man first tried AI, which refused the job. He then ran an agent on DeepSeek v4 Flash through opencode, and it did the full reverse engineering and forensics and deleted every trace of the malware.
Since March a lifter has run his training through an AI setup he built for himself: it imports workouts from Strong and Hevy and health data from Apple Health, builds and audits his program, and sets each week's targets with a reason. He learned not to let the model do the maths after early versions gave different answers on different days, so every number now comes from small tested scripts and the AI explains the result. Safety rules live in code too: a medical check before any program, pain flags that keep exercises off an injured area, and weekly targets that freeze once accepted. He has since shared it as an open source plugin.
Ulta Beauty built Ulta AI on the AI Enterprise to guide shoppers through more than 30,000 products, turning questions into personalized recommendations. Website conversion rates tripled.
She asked the AI to erase her digital footprint. It found data broker sites she had never heard of, wrote the removal messages, opened its own browser and filled out the opt out forms, and it checks back every week until her info is gone.
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.
The AI fixed Steam games and HiDPI and monitor issues on his Linux machine and powers a recurring shell script that checks updates and looks online for potential issues.
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.