An American marrying in Mauritius, with guests who had never been to a Hindu wedding or the island, built an AI concierge for his own wedding. He put their wedding details in a database, connected an agent with tools to it, and gave every guest an invite link, so guests could ask questions on the day instead of asking him.
He helped his brother with the website of Ichtus Vlaanderen, an NGO he used to work for. Using the AI through the WordPress.com MCP connector, he fixed design problems like a messy photo section and buttons that were too big.
A Reddit user needed to change something on his home insurance but faced the insurer's press-1-press-2 phone maze. He told the AI to call the toll-free number, work through the menus until a human representative was on the line, and then call his phone — the AI did it, and he made his change talking to the rep with no hold time of his own.
Nijel B Murray (verified, 130K followers) created an AI called 'Winningston' to manage his 'one big to-do list' of living alone in his 20s. Screen recordings show him asking Winningston to review his week and catch missing items; the AI identified a Thursday scheduling conflict between a flight and a briefing call and, after his approval, rescheduled the flight.
A user ran a recurring agent loop that reads his Gmail in Chrome through desktop automation. He then joined a live Google Meet job interview in the same browser window. On its next tick the loop addressed the active tab instead of its own Gmail tab and navigated the interview tab to the inbox, kicking him out of the call. Its attempted undo navigated away a second time, and restoring the Meet link reloaded it a third time. Each reload wiped the live captions he was relying on, and the caption history is lost permanently.
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2026), blogger Tony Xu describes running the AI Agent on Telegram since April 2026 as his personal errand-runner: persistent memory, skills, terminal/file/browser/GitHub/Gmail/Calendar tools and cron jobs, with morning and evening briefings, email sorting and follow-up, and calendar work. His two standing rules: low-risk tasks it does itself, high-risk tasks it must ask about first; and stay silent when everything is fine. In October he consolidated the AI, the AI and his coding-agent setup into AI, because three systems meant three separate states and memories to track.
The author describes using AI to resolve a six-month-old travel medical insurance claim with Cigna. The AI called the insurer, was transparent about being an AI, conducted the call politely (impressing the representative), and — because final consent was required — called the author's phone and connected the parties so he could approve verbally.
The AI prepared and filed Australian visitor visas for a couple travelling to Brisbane, and caught a placeholder birthdate in the details before submission, confirming the correction over WhatsApp.
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.
A man testing the AI as an email triage agent found it had buried an urgent warning, that his Railway and Anthropic keys had been leaked and needed rotating as soon as possible, under 50 routine deploy and admin email notifications.
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