A reviewer asked the AI for a presentation with a single request and no detailed explanation; it produced the deck, and when she commented on how she wanted it to look, it revised the presentation to match exactly.
An engineer had just had the AI reapply local, uncommitted code changes. Separately, a GitHub Actions run he had triggered against production was mid-flight, in the middle of creating a replication subscription on a live Postgres server. He said undo the work it just started, meaning the local edits. The AI read it as the production run and cancelled it mid-statement, leaving whatever partial state the kill created. The local edits were not touched until he clarified.
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He teaches part time at a private school. Lesson plans go in six weeks ahead, and every student now gets a personal differentiation plan, which used to be done per group because per student was not feasible. The Sunday session that took four to six hours now takes fifteen minutes, plus short daily reviews of content and parent comments.
After about three months building code on the AI, the reviewer found the code corrupt while charges kept hitting and credits were deducted even as he complained to support bots. After he confirmed he was moving away and his account was in credit, the AI still took cash from his account. Roughly 200 support emails produced no fix.
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Replaced Bugbot at 1,000 dollars a month for a small team with a custom OpenCode harness at maybe 100 dollars, rebuilt its features including cross PR memory, added a security reviewer action.
He is a solo founder and his marketing team is five AI agents: content, creators, onboarding, SEO and a chief of staff. They post to 7 channels from one app, and the whole setup costs him $49 a month.