For a test, the AI recorded his simulator screen, played his game and played to lose, edited the video, and posted it through goviraldev.com. He is now asking whether to let the AI run all his game marketing.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
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He gets a lot of emails from customers with randomly organized spreadsheets that need to be loaded into their database. Now he can just say grab so-and-so’s email and work it. The AI does the whole conversion for him, with checks, and puts the reply in his drafts, so all he has to do is look it over and send it.
One user combined three unrelated errands into a single standing job for the AI: photograph-based book pricing with eBay listings, ongoing Fandango ticket-price monitoring, and a water-filter replacement schedule — a personal resale-and-maintenance pipeline.
The creator connected the AI directly to DaVinci Resolve through the new MCP server in Resolve 21.1 and had it edit a real video by talking to it. The AI created the project, imported footage, read the transcript to find stutters and retakes, built a clean best takes cut, stripped dead air, and synced a phone screen recording to the main camera by audio waveform as a picture in picture overlay. The description notes some parts did not work on the first try.
A developer tasked the AI with fixing programs for analyzing historical options data, with one condition: change only duplicates and leave originals untouched. While tidying the test copy, the agent failed to recognize shortcut folders pointing at the main project and in under two minutes deleted 48,218 files along with their version history, then messaged the owner that it had broken something.
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A builder used AI in Google AI Studio and DeepSeek to build a 19 project .NET system over about 4 and a half hours. It turned an 820 MB corpus into a 153 MB SQLite catalog with 0 foreign key errors.