Most questions about ChatGPT and Claude are not about which model is smarter. They are about why the limit is hit again, whether the output holds up and where you should not rely on it.
This hub collects my videos on the two chat assistants I use every day. It is not about benchmarks and not about who is ahead this month. It is about what happens when you actually put them to work: on images, on a channel strategy, on design, on debugging.
Almost every one of these videos got uncomfortable at some point. The web search in ChatGPT Images was not what it appeared to be. The YouTube audit found problems I would rather not have had. And with agent safety the fun ends quickly anyway. Those moments are the point here.
Some videos deliberately appear in other topic hubs as well, where that context also helps.

Nine concrete places where tokens disappear before the actual work begins. The least spectacular one helped me the most.

Four tests instead of demo hype. In one of them the web search turned out not to be what it looked like.

A premortem on real channel data. Eight problems came back, and a few of them I would rather not have read.

Claude Design is not just another model update. It changes where design work starts and who can create first visual drafts.

Part four of the Voicebox series did not go to plan. That is exactly why it is useful: two AI agents debug a real local setup.

Five virtual cities, different models and a hard question: do AI agents stay stable over several days when they get tools and rules?
The question usually misleads. Both are strong, but strong at different things. Claude is more pleasant for me with long context and with code, ChatGPT for images and quick research. More useful than the general question is deciding which one fits the task in front of you.
Usually not because you work too much, but because the workflow burns tokens. Long chats, context dragged along, active connectors and unnecessarily long outputs cost more than the actual question.
Not unchecked. The ChatGPT Images test showed that an apparent web search is not always what it looks like. Anything involving numbers, sources or currency needs a second check.
The version numbers do, the patterns do not. How tokens get consumed, why a premortem asks better questions and where you should not blindly trust an agent all stay true after the next update.
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