A random mix from the whole library. Shuffle for a new set.
Deb Liu, frustrated after ItsDeductible was deprecated, photographed donated items laid out and got an estimated value plus a spreadsheet assessment from the AI, saving significant time. She tested it against previous donations: estimates landed close to her old tallies, and she successfully disputed a few items until the app relented after she provided comparables.
A local model helped build a self-hosted services wiki and dataset in an Obsidian vault so his partner could keep systems running if he died, set up in a few hours.
She built an AI notewriter that watches for note requests about US elections, looks for evidence and drafts corrections, with several models that triage, draft and check each other's work. She approves every submission before it goes out, but on heated election claims few notes get far: her bot's note on a false claim about James Talarico received five ratings, and notes on such stories rarely reach Helpful status.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
A church volunteer runs a weekly hybrid workflow: The AI translates six Chinese daily spiritual messages (Monday–Saturday) into structured JSON under strict rules — Bible quotations in NASB 2020 rather than translated, hymns left untranslated, ministry terminology matched — then Python inserts the text into a PowerPoint template, merges a bilingual twelve-message deck, and converts it to HTML for the church website. He keeps theological review, visual checks and final publishing approval human on purpose.
His claim was too small for a lawyer and the insurer had frozen it at $4,430, so he worked it himself with AI holding every letter in order. The agent surfaced six dated contradictions in the adjuster's own letters, including a legal basis for denial that changed three times, and reviewed each of his drafts as opposing counsel before anything was sent. After his letter quoting their own paper back at them, the offers climbed: $6,500, then $8,000, then $8,750, and the insurer accepted his split of the last gap the same morning, at $10,250.
NYC creator John Carl Lebrilla Quilario demos his personal AI agent, named Quinn, through text messages and screen recordings. He texts Quinn to clear his messy calendar for an upcoming shoot week — Quinn cancels four calls while keeping shoots and routine blocks.
Ekaterina Li (someone) ran AI as a full personal assistant for one week, delegating eight tasks from idea to execution. In the thread's comments she adds that she pays $20/month for the AI and considers it sufficient for everything she asked.
Hemant Kadam, demonstrating his 'craziest use case' after a couple of days on the AI, opened the app to a Sarvam DevOps Engineer application page. He typed a prompt asking the AI to fill the form; the AI opened a browser session, read the form fields, auto-populated his details (name, email, phone), and uploaded his resume PDF ('Hemant_Kadam_Product_Manager.pdf').
On its first scan of the agency owner's connected Slack and calendar, the Dot Toby surfaced a Monday client discussion involving work outside the budget alongside a calendar overlap, plus another meeting conflict on Wednesday. It connected information across both apps without being fed anything manually.
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.