Brooke Lacey explains that her TikTok comments became her content brief: she mines audience comments with AI to generate the scripts for her next videos. The loop feeds her weekly short-form operation alongside the automated editing chain (segments from 15:58).
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.
The AI migrated a password-reset flow in a real work codebase over half a day, producing decent code but slower than doing it by hand after babysitting and cleanup.
This only partly worked. Worth knowing before you try it.
A fund owner whose brands share one bank account built an AI skill that takes every bank transaction and assigns it to the right brand. Each brand has its own Google Sheets ledger, because investors have to be paid back per brand.
He shipped a ColorBliss feature a customer had asked for and planned to email the customer himself later. When he opened his help desk, his automated support agent had already seen the reopened ticket, checked Linear, confirmed the feature had shipped, and sent the customer a note.
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.
Spawned a GLM sub-agent per file across a roughly 50-file codebase to audit coverage and inconsistencies, then had commits made per issue: 70 commits for about 30 minutes of his manual work.
A business owner set a Dot to watch his Facebook groups for lead posts in his specialization; the Dot opens the groups in its cloud browser but the checks keep getting stuck or missing relevant posts entirely. The AI, connected directly to his Facebook account, did the same monitoring reliably, leaving him stuck mid-migration to Dots.
This only partly worked. Worth knowing before you try it.
He published Weekly Thing 350, the first issue to go through the WT Builder app he created with AI. Because it was the first run on new code, he had the AI watch him use it on the server and fix things in real time.
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.