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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.
，更多细节参见新收录的资料
Google promises the new image generator will have more advanced world knowledge pulled from the Internet by the Gemini 3.1 LLM. This apparently gives it the necessary information to render objects with greater fidelity and create more accurate infographics. The days of squiggly AI text were already ending, but Google says Nano Banana 2 has Pro-like text accuracy in image outputs.
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