For Netflix, the streaming industry's biggest player with more than 300 million customers, buying the film and streaming division would have bolstered its movie offerings, while heading off any potential rivals looking to get their hands on the Warner Bros content.
The same issues exist on the WritableStream side. A WritableStream has a highWaterMark and desiredSize. There is a writer.ready promise that producers of data are supposed to pay attention but often don't.
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Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.
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"tengu_mcp_tool_search": true,