Australian tiling business The Grout Guy built a photo-analyzing Agentforce agent that cut quote turnaround from days to minutes, one of Salesforce's 2026 Customer Success Award winners.
A Korean solo developer's two-day diary of putting the AI to work as his team: GitHub issue labels split between him and the AI across marketing, planning, design, QA, operations and finance, with a project board and roadmap milestones built in about an hour; the AI runs QA on each deploy event and files issues; customer inquiries are answered through an admin MCP connection; and morning routines from a one-time setup (7 AM English lesson, Google Analytics analysis, issue briefing) arrive unprompted. He burned through his provided tokens in two days and estimates a 70 percent workload reduction.
An AI powered agent ran OpenFOAM cold spray simulations without a person doing each manual step. It read deposit results, spotted failed runs from solver logs, and decided the next simulation, with an animation made for each run.
Commenting on the 26 use cases post, he says he uses AI to find and apply to jobs. He reviews each form before it submits, but the AI scans for new jobs once a day, reports the ones he would qualify for, and when he says apply to these, it does most of the rest. It remembers his preferences, like salary range. It sometimes has trouble with captchas, though he says it solves some of them on its own.
Employees at Swiss sportswear brand On launched no-code the AI Enterprise agents themselves. The agents handle knowledge extraction, executive reporting, research, scheduling and onboarding materials.
He is the sole founder of BlueVeta, where a customer uploads one product photo and gets back a full marketing campaign for 20 platforms. Every part of the company runs as its own AI session, the sessions message each other and share docs, and nothing is built, deployed or spent without his OK first. The company has real paying customers through Stripe, and the AI does about 75 percent of the work in each customer pack.
A builder whose wife was laid off by Indeed built a job search platform with AI, then a connector that brings it inside an AI app: search about 15,000 new jobs a day for free, drop in a resume for matches and tailored versions, and have the service submit applications on employers' own sites once the user approves. It launched the week before his October 14 post and already has 450 users with 75 active daily; paid users on autopilot are seeing 83 interviews per 100 subscribers.
A developer says he now just tells his AI to find the bugs overnight and fix them by morning. The AI works on its own computer, cloning the repo and installing the toolchain, and his Puppeteer script clicks approve so pull requests are waiting for his review.
His company is pushing staff to use AI. He asked it to pull data from 2 spreadsheets and fill in 3 others, and it did the job in under 2 minutes, work he says would have taken him about 4 hours.
A solo developer is building an independent Rust blockchain from a white paper. AI coding agents write most of the code under his direction, and AI models review it. An agent implemented the fix for a stake counting overflow in the consensus check, and the developer decides what merges and runs the tests.
A perpetual the AI thread in his llama.cpp checkout periodically sweeps PRs and research, rebuilds llama.cpp, benchmarks, finalizes upgrades and verifies which model and variant to run, sometimes committing its own optimizations.
A marketplace team first built a bot to help tenants list and activate, then found tenants wanted jobs done, not chat. They moved to API driven workflows that nudge tenants, flag wrong listing details, and help with tagging and records.
This only partly worked. Worth knowing before you try it.
He has worked in SEO since 2009 and has no coding background. He shipped a SaaS with paying users anyway. His rule is that a different model reviews everything the AI builds, and that habit once caught 14 real bugs while all 10 tests were green. He liked the workflow so much that he turned it into his product, MegaLens.
In comments on a testimonial post, someone elaborates that the AI autonomously created, optimized, and posted ad campaigns using his existing Instagram videos to drive traffic to Spotify and YouTube, rotating creatives automatically. Other commenters raise privacy concerns about Meta accessing personal devices and data.
A Korean essay analyzes a public user case in which the Aside AI browser migrated 110 Brunch posts into Naver Blog in 2 hours 40 minutes, carrying formatting, images and links intact; the posts drew 260 views the next day. Brunch, Naver Blog and Maily offer no posting API, and the user had previously tried AI with Playwright, which was slow and often gave up; Aside instead inherits the user's already logged-in browser session.
A shirt shop is run by an AI agent named Cosmo. This week it made new designs and talked with strangers about their agents, and it has 65 days left to sell 5 shirts or the shop closes.
This only partly worked. Worth knowing before you try it.
Pointed Opus with TLA+ at company clustering and failover logic and found and prevented a catastrophic bug no unit test would have caught; Opus also wrote the invariants.
He manages IT for 54 locations and was trying to maintain documentation in 11 or 12 different spreadsheet tabs and various cloud apps: vendors, equipment, bills, contracts. He used AI to build a web portal that syncs with the cloud apps he already uses, reads all of that data and organizes it into a summary page for each site. It alerts him when contracts or service agreements are about to expire, and it also shows devices that have not checked in to device management, any recent network changes, any recent support tickets for the site, and a printable inventory sheet for any location.