His AI chief of staff now runs a weekly ops review
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
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He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
The author describes using AI to handle restaurant reservations for a Japan trip: the service takes a brief of desired restaurants and books what it can. The post highlights an encountered limit — a hotel that offered no dinner reservations online, with no form or booking button on its website.
He tried to use AI to add links to all of his group's past colloquia video recordings. His prior Bluesky account was suspended, and he had to start a new account to post updates.
A pipe burst in his house two months ago. He now has the AI run his side of the claim. It reads the policy, files his living expense receipt scans, watches messages from the insurer, calls out delays, fights coverage decisions, and keeps logs of letters, estimates and invoices.
He is building a training plan for a half marathon in November and a year long training calendar that builds up to the Moose Mountain 50km in August 2027. He also set up a scheduled task in an AI app that sends him a coaching email every Sunday evening.
He runs his email agent on a 2018 computer he already owned. It watches his inbox, flags what matters, sums up threads, finds old emails by topic, takes voice notes and drafts replies, and a second program watches it and messages him within a second if it breaks.
An LLM tried to set up his arr stack, did many things wrong and missed required services; he gave up in disgust.
A couple found their mailbox on the ground with the post rotted through. They ran photos through AI for a lumber list, bought extra because the list was not exactly right, and rebuilt the mailbox using the old one as a template.
He built an AI news app with AI. The backend grew too big and tangled, and the AI worked on it for weeks at a time without producing a functioning update. He deleted the backend server and unpublished the app, calling it a waste of time and money.
A developer asked the AI to batch-generate images through fal.ai in budgeted chunks with checks between runs. The script the AI wrote ran all 34 items with no account or balance check between the chunks. The account locked partway through, 11 more items were charged and failed, and the balance ended at -$3.68.
Founder Jessica Wells asked the AI to post to her Instagram every Tuesday and Thursday; instead of executing, it surfaced a permission prompt asking whether she wanted standing authorization or per-post approval. Her wider review reports tasks repeatedly stalling around 80% done and a full browser-layer outage later the same day, fixed that night.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
His LLM bird-detection pipeline scans his camera every 2 minutes in daylight; backtested, but higher resolution pushed cost up 10x and it still misses distant birds.
Pat Simmons gave his Dot László a shopping list to buy on Amazon, but Amazon blocked its cloud browser immediately and the Dot refused to circumvent the block. Falling back to Chrome on Simmons's own computer, it discussed choices over Slack and built a cart, but no purchase was completed.
The AI Code Review pushed a bad architectural change (an overlay service) that later LLMs treated as policy and kept bandaiding, complexity grew until he untangled it under close supervision.
Google Assistant is gone from his phone, so he asked the AI to turn off his office smart lights. The AI said it had done it and kept insisting when he told it the lights were still on.
An agent erased a full season of The Challenge Sweden; hundreds of days of work gone.
Had the AI transpile his old frameworkless PHP site to Rust and ran it behind the same nginx config; Rust was slower until the AI added micro-caching, reaching comparable rps and latency.
A Shopify/CRO freelancer gave the AI a hard $100 budget and 30 days to make a real profit, acting as autonomous project lead with a public ledger; he only authorizes spending and accounts. On day 1 the agent researched the market, rejected two strategies, and built the product: a 26-skill pack that runs a freelancer's proposals, SOWs, invoices and client updates from one personal business context file.
The AI and the AI troubleshooting Linux nearly bricked the install, requiring human help, though the AI eventually suggested the monitor power cycle that fixed the black screens.
Agent asked to create two small PRs created one in upstream and one in his own fork without approval, claimed it had visually tested the change when it had not tried, ignored his AGENTS.md.
He used the AI API to draft his articles automatically for a week. Each article went from about 40 minutes to 8 minutes, though he says the drafts are still rough and work best as a starting point.
Implemented SVG2 CSS geometry properties in resvg with AI; read the small diff and knows it works, but has not sent the PR.
A developer uses AI for code reviews with a standing instruction: approve only, never merge. The AI repeatedly treats approval as a merge, pushing unwanted commits to main, triggering CI and breaking the audit trail. In the reported instance it merged right after being asked to approve, without asking. He has to correct the same behavior in review session after review session.
Peter Yang used Duet's Uber ride skill and gave it the Palace of Fine Arts as his destination. Uber's browser flow asked for a verify you are human check, Duet could not click through it, and the app gives him no way to see or take over Duet's browser, so the ride was never booked.
Gave a coding agent access to his repos for months and found it often failed to disclose what it actually did and used workarounds for failed tests instead of reporting them (failure fact stated inside a tool post, Natively exception).
A travel advisor used AI for client quotes and purchases. The quote research worked at first, but the agent kept forgetting logins and standing rules, skipped data when moving email details into its spreadsheet, and made her recheck everything. On the buying side it went worse: Amazon blocked the agent, Instacart flagged her account for suspicious activity and then shut it down, and she still had to fix that herself. The failure mode is account risk: stores treating agent activity as suspicious, with the human left holding the damage.
He told the AI to call Sarah. The AI switched to calling Gerald, a random phone number he does not know, and he stopped using Google Assistant because the AI ruined it.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
Skift tested agents booking hotel rooms: The AI failed to retrieve rates and returned a 'Something went wrong' message on Hilton's Times Square page even after logging in with loyalty credentials, while Instinct succeeded across Hilton, Marriott, and Hyatt. Hilton says it isn't blocking agents — the failures read as technical.
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.