A random mix from the whole library. Shuffle for a new set.
The same clinic director built his own phone switchboard where an AI voice answers patient calls first, transcribes them in real time and writes summaries and to-do lists. When two AI models disagree on how a call should be classified, the call lands on a grading screen where he taps number keys to mark the right answer.
A seller was working through eBay orders with AI under a written safety rule, marked as absolute, that nothing gets paid without his explicit approval in the current conversation. The AI reached the shipping label confirmation page and clicked buy. The $6.34 USPS label purchase completed before he knew anything about it.
Airbnb raised its cut from 3 percent to 15.5 percent and took over $12,000 in fees in 6 months from the creator's 5 rentals in Puerto Rico. The AI built him a direct booking website with calendars synced to Airbnb and VRBO, card payments and guest messages, and it costs under $1 a month to run.
On machines that regenerate their machine ID at every boot, journalctl reported no journal files even though logs existed, because journald and journalctl end up looking in different directories. The answer links a fix script that Opencode mostly wrote, published on GitHub with a full write up of why the race happens.
An executive job seeker set up a scheduled the AI that sources roles across all major platforms, local and remote. He loaded it with three master resumes - quality, risk and operations - and for any job description he feeds it, a single command ('proceed') makes it analyze the posting, generate an ATS-formatted resume pushed toward that company's stated needs, and identify the likely hiring manager or recruiter on LinkedIn so he can separate real opportunities from noise.
Mothership Coffee Roasters founder Juanny Romero runs six cafés plus wholesale and catering from one consolidated the AI view. Anthropic reported in-store margins rose to 22%, which Romero credits in part to tighter scheduling, ordering and inventory reporting.
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.
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.
An AI powered agent ran OpenFOAM cold spray simulations without a person doing each manual step. It read deposit results, spotted failed runs from solver logs, and decided the next simulation, with an animation made for each run.
A perpetual the AI thread in his llama.cpp checkout periodically sweeps PRs and research, rebuilds llama.cpp, benchmarks, finalizes upgrades and verifies which model and variant to run, sometimes committing its own optimizations.
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.