Yes, that is great, for people from the US. For people in Europe and other locations, this just proves that they dont really care as the tool is already being used against us. It quite clear to me that anyone outside the US should immediately cancel all contracts with these corporations, as well as work their hardest at blocking their bots online.
Yep, Gemini is virtually unusable compared to Anthropic models. I get it for free with work and use maybe once a week, if that. They really need to fix the instruction following.
Thanks for the long and considered response, but this is a really ugly UX decision.
As others have said - 'reading 10 files' is useless information - we want to be able to see at a glance where it is and what it's doing, so that we can re-direct if necessary.
With the release of Cowork, couldn't Claude Code double down on needs of engineers?
This is great, not 10 minutes before this outage did I present Railway as a viable option for some small-scale hosting for prototypes and non-critical apps as an alternative to the Cloud giants
It always happens that way. I guarantee some people migrated from Heroku to Railway and bragged about future stability to the team, only to experience this.
Everything in plan mode first + AskUserQuestionTool, review all plans, get it to write its own CLAUDE.md for coding standards and edit where necessary and away you go.
Seems noticeably better than 4.5 at keeping the codebase slim. Obviously it still needs to be kept an eye on, but it's a step up from 4.5.
I've been working with a claude-specific directory in Claude Code for non-coding work (and the odd bit of coding/documentation stuff) since the first week of Claude Code, or even earlier - I think when filesystem MCP dropped.
It's a very powerful way to work on all kinds of things. V. interested to try co-work when it drops to Plus subscribers.
I can't remember which paper it's from, but isn't the variance in performance explained by # of tokens generated? i.e. more tokens generated tends towards better performance.
Which isn't particularly amazing, as # of tokens generated is basically a synonym in this case for computation.
We spend more computation, we tend towards better answers.
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