Last May, I wrote a blog post titled As an Experienced LLM User, I Actually Don’t Use Generative LLMs Often as a contrasting response to the hype around the rising popularity of agentic coding. In that post, I noted that while LLMs are most definitely not useless and they can answer simple coding questions faster than it would take for me to write it myself with sufficient accuracy, agents are a tougher sell: they are unpredictable, expensive, and the hype around it was wildly disproportionate given the results I had seen in personal usage. However, I concluded that I was open to agents if LLMs improved enough such that all my concerns were addressed and agents were more dependable.
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不得不承认，Google 团队在训练 Nano Banana 的路线上，采用「文字渲染」作为一项重要指标，是很成功的选择。之前团队在技术分享播客上就曾提到，如果能把图片上的文字准确地生成，那么整个图片生成也会没有太大的问题。
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In the following simplified trace generated by our workflow, a customer uses a 100% off promo code. The business logic calculates the total as $0.00 and attempts to pass it to the payment gateway, but the payment gateway rejects the API call because the minimum charge amount is $0.50, causing a 500 Internal Server Error:，这一点在Line官方版本下载中也有详细论述
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