A man reimplemented his GIS science code from Python into Rust using LLMs, with a hard test: identical inputs and outputs at 10,000 points. Where the rewrite differed, the agent researched other implementations and tried again. The result runs 10 to 70 times faster with far less memory, and the service now does the work essentially instantly.
A business owner's lead profile runs every Monday on its own. It formats his warm leads, finds cold leads that match his criteria across a rotating list of cities and niches, then digs into each business to find what he is missing, owner names and exact contacts, checked against business registries. He gets one standard weekly report: best fit clients, outreach details and the facts to judge each lead.
He used AI, ElevenLabs, and D-ID to make a budget simulation for his Politics of Public Policy course. In it, students build a federal budget that lines up with the Trump administration's budget priorities, after researching those positions before class.
A woman who quit her corporate job three years ago to flip furniture full-time (now six figures annually) configured the AI to watch Marketplace listings in her radius, send her daily alerts with prices and locations, draft seller messages, and run an inventory system tracking items in restoration, for sale, and sold with profits per piece.
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
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Mailing thousands of people brought hundreds of auto replies that nobody read. The AI scanned them read only, flagged who had left or changed roles, and updated Mailchimp, leaving a cleaner list and better deliverability.
Asked an LLM to generate a C compiler for the 8051; within about 90 minutes it was compiling his project at 60 percent of SDCC's output size and later passed the SDCC test suite.
Paired with Zapier, the AI checks his spam folder for mail that should not be there; most scans find nothing, but the few real messages it rescues make it worth running. It also uploads and catalogues invoice payments for the finance team, work he used to do by hand.