An LLM cut 60,000 useless lines from his test suite and fixed bugs it found, in about 2 hours
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
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LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
The AI release skill monitors canary rollouts, updates the ticket with status, and flags incidents and weird failures during multi-hour releases.
A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.
At the start of a 2 hour 7 minute TGV ride from Paris to Valence, his shop did not exist. Talking with AI, connected through a new MCP link and without opening the WiziShop admin once, the shop was online by the time he arrived.
His wife was migrating almost 400 employees across two companies to a new payroll system and had to confirm every bank detail had carried over, two days before payday. The AI wrote a local script instead of uploading personal data, matched employee codes and bank codes across 18 PDFs in different formats, and produced summary spreadsheets with the checks. The script can be rerun for the next migration.
He built a pipeline review and follow up system in GoHighLevel. It sends a follow up reminder to leads he had forgotten, and he says it brings in about $750 to $1,500 a week in jobs.
As an experiment, the founder told his project-manager bot to ship one secret feature to PromptBase at 4am and deploy it while he slept - the only rule was that it had to benefit the site. Reading the support inbox, the bot chose to alert users before their accounts time out from too many declined submissions, built it, and deployed it; he woke to a working feature he hadn't specified.
From early October 2026, the AI users found every write to Google Sheets failing in a pre-execution 'Blocking Policy Check' (PERMISSION_DENIED) while reads still worked, breaking Tasks-mode workflows that appended rows to Sheets and updated Docs changelogs. Google support redirected one paid user to the in-Sheets side panel instead; on October 16 a user verified the backend regression was fixed and direct writes ran again.
A digital-health CEO reports his businesses have no full-time developers, DevOps, designers, analysts or product manager: scheduled AI agent shifts handle deploys, an agent-built CRM, per-business-line email sorting, meeting scheduling, technical support and publishing news four times a day. The work runs on three $200 AI subscriptions — $600 a month against roughly $38,500 a month at US median pay for the replaced roles.
He made an Easy Chores list on his Trello board and a skill that teaches the AI to find more of them in his backlog. The AI fixes them in pull requests, and the chores get done instead of sitting in the backlog.
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.