Charles Summers runs his demand-generation work on the AI: 8 scheduled tasks that drive HubSpot, Search Console, Gmail and LinkedIn through Chrome, backed by 578 local sessions and about 220 memory notes. Ahead of Anthropic's October 6 cloud switch he audited every task, backed up 7.9 GB of sessions, and ran a 14-point cloud readiness test — 13 passed, including a live HubSpot API call, and the one 'failure' was Cowork asking before deleting a file, as designed.
He used the AI for two weeks of daily Excel updates. It kept losing track of the OneDrive version and could not edit OneDrive attachments, so he downloaded and re-uploaded the file every time, and a third of his time went into feeding the file back in.
This one went wrong. See what happened before you try it.
A university worker used AI to build a web version of a transcription program that used to need a special Windows machine reached by remote desktop. The new tool pairs a speech model with speaker detection on the university's own systems. Twenty minutes of interview audio now transcribes in 40 seconds with the speaker changes right, and students and staff can use it from a browser.
He had an email with stage times and used AI to tidy it into a Stage, Day, Time, Artist list. The AI then changed the fcpxml file so Final Cut Pro had a new project for each set.
The same clinic director built his own phone switchboard where an AI voice answers patient calls first, transcribes them in real time and writes summaries and to-do lists. When two AI models disagree on how a call should be classified, the call lands on a grading screen where he taps number keys to mark the right answer.
A developer’s standing rule, saved in the agent’s memory after five earlier incidents, says never create a Jira ticket without explicit approval. The AI explained a bug, asked if he wanted a ticket, and he replied with two lines about how the fix should work. The AI read that as a yes and created ticket PRE-990. He then had to spend time and effort cleaning the ticket up.
This one went wrong. See what happened before you try it.
Jacob runs four AI products alone. He built Tracetify, a tool that rebuilds how a competitor got its first users from twelve public data sources, in about three days, and gave the AI one instruction for the whole interface: you decide. Users later asked whether he had hired a designer.
He edits video for a living. His agents handle the non creative manual work around each project: quality checks for missed text, black frames and logos, subtitles, reformatting for social aspect ratios, spreading files to the right products and pulling source material for descriptions. He logs his hours on every project and says agent assisted projects take about half the time with better quality; the weeks spent building the setup paid for themselves in two weeks.