Twelve hours with a top coding model left him 20 new bugs and features built to the minimum
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
A random mix from the whole library. Shuffle for a new set.
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.
Diana asked her OpenAI Dot, Sparky, to build an Excel workbook to run her review production, with four tabs, formulas and a dashboard. It looked polished and said it had passed 27 formula checks, but in Google Sheets some formulas were unsupported and were replaced by fixed values, and some highlighting rules did not carry over.
Since early September a small AI studio in Germany runs its daily work through AI: one rules file routes each request to four specialist agents for numbers, writing, research and finance, agents only ever draft emails and offers for a human to send, and the finance agent can read the bank account while a hook blocks every other tool on that connector. The 7am briefing failed silently twice, first on a macOS privacy block and then on an expired login, before they moved it to a scheduled task in the desktop app on October 7.
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.
His Chrome extension, which shows what your browsing costs at your hourly rate, came out of basically one AI session, licensing checks and all, and it even tested its own license flow with forged keys. It is live at $8.99. Sales so far: zero. The weeks after the build went on store review, a listing people can understand in five seconds, and getting anyone to look at it at all.
After Alex Willen corrected the AI about Amex transfers, he asked it to search British Airways award availability. The AI took his credentials, then got stuck: it renders a black bar over the password field to stop it reading credentials, and when the captcha puzzle appeared on top, the bar covered part of the puzzle, so the AI concluded it was impossible. Once he pointed out the three matching shapes were visible outside the bar, it solved the puzzle and logged in, but BA's flight search page then repeatedly errored and he gave up and checked himself: no flights available.
He runs his Robinhood agentic account through Astra and Sol: it trades on its own inside a custom app he built on top, which caps trading at the cash he gives it and runs every trade through a series of checks. He gets a note each day on what is going on with the account.
Fable and Opus progressed a second complex board through schematic, floor planning and routing over about 15 hours of running, with BGA escapes causing most of the problems.
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.