A random mix from the whole library. Shuffle for a new set.
Daren runs his film company alone. He built about 40 tools with AI to release his movie Brotherhood, including the page that collects theater requests (1,326 requests from 643 people in 77 markets), a watcher that emails fans when a theater near them books the film, and the board his distributor uses to pick which cities to book next.
Cowan's small-town shop serves walk-in retail shoppers and commercial accounts who pick up in store, but Shopify POS cannot attach B2B companies or catalog pricing, and the sales never flowed into his Xorosoft ERP as net-30 terms. Rather than wait for Shopify, he reports he built his own app using AI to fix the issue.
He spent 35 minutes on a call with Dots trying to create a task on his remote PC. Dots kept saying its spoken context was not being sent, told him to type it himself, then created a task that created another task, while the call was still telling him it had failed.
He ran AI on the task with 6 agents at a time, about 75 agents in total over about 6 days. They produced transcriptions of tens of millions of handwritten images and indexed them all.
Engine's help agent Eva, built on Salesforce Agentforce, resolves 50 percent of chat inquiries, per Salesforce's release.
She tried three AI tools and found the AI in Word the most helpful. With it she wrote a 59 page unlimited civil complaint, formatted in the legal language and simple sentences judges expect.
He built an enterprise SaaS for a niche industry. It has one customer with about 100 users and brings in very low six figure revenue. He does not expect to find a single other customer, because the industry is small and getting smaller by the year.
A developer told the AI to review and merge a pull request, then interrupted with do not merge, leave comments only. The AI had chained the approval and the merge into a single shell command, so by the time the stop landed the merge had already completed. Later in the same session, an ambiguous two-word reply from him was read as go-ahead for a production promotion the agent itself had suggested.
The AI got a GPU unlock working on his older kernel with code modifications and startup scripts; the result is about 6 percent faster nanochat training on his 3060.
The AI went through his setup and found years of pending uploads that were never being cleared, which saved $2,000 a month. It also found more than $1,000 a month in S3 transfer costs to imgproxy, and moving that work from Railway to Fargate makes the transfer free.
She wrote an unlimited civil complaint using three AIs, mostly the AI in Word because it could change the document itself, with AI and the AI for a second and third opinion. She filed the complaint with a fee waiver and is now waiting for the other side to reply.
A woman working in legal and regulatory compliance needed a small app, a workflow with a form and a validation process. Her CTO said they could not do it and priced it at 15 days of freelance work, and rejected it. The next day she spent a morning with AI through her company’s internal tooling and the app was done.
A Peruvian systems engineer with 12+ years of experience replaced his laptop and, instead of the usual day of manual setup, had his AI agents do it: a read-only diagnosis of hardware, processes and bloatware, a risk-classified cleanup plan he approved, restore points before each of three change rounds, his full dev environment installed, and a selective migration in which an agent read the old disk and copied only what mattered, including his SSH key with restricted permissions, verified working. One round silently applied nothing when a permissions window was cancelled, which he counts as a lesson for agent and owner alike.
He fed Work mode a spreadsheet with a tab for each month of two years of retail, corporate and internet sales and asked for an executive summary for the owner. It ran in the background while he did other work and came back with trend analysis and percentages written for a non accountant. The owner loved it, and he figures it saved him days.
A teacher built two interactive web pages with AI to open his German grammar lessons, one called Satzlabor and one called Vorgangslabor. He used both in class and says both were well received.
He has been building a fantasy sports app with AI since June. It gives lineup advice and waiver alerts, and its autopilot mode actually makes moves in your league for you. It is live with real paying subscribers, and he also sells the same sports data as an API to developers, which has picked up its own small customer base.
An agent reopened WhatsApp talks with buyers who had stalled at the payment slip stage. Buyers who talked with the AI converted at 8.36 percent against 0.17 percent for those who did not.
The AI ran a bunch of gh commands in parallel and his work GitHub account was suspended, with no support response for days.
With the help of the AI, ported the current dev branch of Qt6 back to Windows XP with working OpenGL.
A worked example in metaflow.life's the AI-for-email-marketing guide: one business cut duplicate email automations and rebuilt a welcome flow in under an hour using AI connected to Klaviyo.
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.