The AI redlined the supplier contracts and caught things his lawyer had missed
The AI redlined OEM contracts through the first three negotiation rounds, finding things his lawyer missed, with the lawyer only doing the final check and money saved.
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The AI redlined OEM contracts through the first three negotiation rounds, finding things his lawyer missed, with the lawyer only doing the final check and money saved.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
A LaTeX user's copied table code did not fit his page size at all. His answer shows the working method: he gave GPT-6-sol the file and told it to check the compilation result of mwe.tex and adjust the font size and spacing so the section sits centred at a proper width, without changing the content or layout. The answer posts the adjusted code that came back.
He edits video for a living. His agents handle the non creative manual work around each project: quality checks for missed text, black frames and logos, subtitles, reformatting for social aspect ratios, spreading files to the right products and pulling source material for descriptions. He logs his hours on every project and says agent assisted projects take about half the time with better quality; the weeks spent building the setup paid for themselves in two weeks.
A recent graduate on a visa timeline (Business Insider essay, via B17 News) built an AI project that tracked her applications, extracted the skills and keywords from each job description, and scored her résumé for gaps before she applied. The dashboard she had the AI build shows the funnel that ended in a job: 186 applications, 44 cold outreaches, 19 interviews, six take-home assignments, three final rounds and one offer.
Added the AI rules and skills to split Terraform PRs into the smallest mergeable units, resulting in cases like 40 PRs with 38 approved and merged immediately.
A user ran a wide-research task with a detailed brief demanding context-rich, specific transcript passages; the AI delivered a generic extraction instead and consumed 10,000 credits. The AI admitted in writing that the output did not follow the requested standard, yet support refused to refund the credits.
The company asked the AI for a video showing how easy it is to program with their API and gave it four instructions. The AI put the rest together itself, and made and published the post.
Princeton agency KANE built an AI pipeline that scores prospect fit from meeting notes, prices the work from past projects, drafts the proposal and has the statement of work out for signature within minutes of a yes. Co-founder Michael Kazantzis said a process that took weeks now happens almost within minutes in a day.
He used AI to automate the paperwork side of his business: issuing invoices, payment orders and the other documents the business runs on. The work used to take a whole day. Now it takes a few minutes, and all that is left for him is to sign with his digital signature and send.
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.