A weekend on the cheap tier built enough of a platform's features to make it useful to him
Used the AI on the 20 dollar tier in a weekend to build good enough coverage on Floci features to make it useful to him; others then continued the work.
A random mix from the whole library. Shuffle for a new set.
Used the AI on the 20 dollar tier in a weekend to build good enough coverage on Floci features to make it useful to him; others then continued the work.
Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
A small contracting business owner, replying to a day to day uses thread, says he has the AI updating his QuickBooks from his online receipts. Bookkeeping from scattered receipts is the classic end of week chore for a small contractor; his agent pulls the receipts and keeps the books current.
He talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
Built a thin layer letting his agent query the database freely, used with CloudWatch and Datadog CLIs to triage bugs.
Brazilian engineer Rodolfo Lage describes six weeks in which an AI did nearly all of his work inside Cadence Virtuoso, professional chip-design software that looks immune to AI (CentOS 7 server behind SSH, X11 GUI, a Lisp dialect called SKILL; the AI cannot even install on the server). Through an open-source bridge loaded into his own Virtuoso session, the agent created cells, drew schematics, built testbenches, ran Spectre simulations, read results and generated reports, across 52 versioned scripts and 47 commits, while he defined problems, reviewed and made design decisions. Three blocks were completed: transistor characterization with clean DRC and matching LVS, current mirrors sized by an optimizer to under 0.005% current error, and a common-source amplifier reaching 26.8 V/V gain and 109 MHz gain-bandwidth. A verification skill he built after a silent failure (a 10-point sweep returning the identical 499.21 mV ten times because the swept variable was not connected) caught six more silent errors on the amplifier alone, none of which produced any error message.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
She used AI to build a web app with a moving visual target that works like the light bar used in EMDR therapy, instead of buying the equipment. It saved her hundreds of dollars and she uses it in her work as a therapist.
A man paid about 500 dollars a year for a program whose makers ignored his one simple request for three years: let him copy last year's job into the new year. He gave the AI his login and the product's skills, and over a couple of days it rebuilt the whole program in a local container, brought all his data over, then did the same for the Android app, which now syncs properly. The rebuild cost about a tenth of one year's subscription.
Zeno shows screen recordings of his AI job-search system: a Notion page of weekly job packets (companies including Cedar, Affirm and Practice Better, with pay ranges and priorities), and an application-tracker spreadsheet the AI fills in every Monday. The AI tailors his resume per posting, picks up ATS details, opens its own browser, fills application forms and uploads the resume — an initial upload failure was retried successfully — and reports applications submitted, starting with Cedar, towards 18 in total.
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.