请问HN：企业在“代币最大化”和代币优化之间的脱节
大约六个月前，我加入了一家财富500强前十名公司的新团队。我的新老板严格要求使用人工智能，核心原则是：“你不应该手动编写任何代码。”
从那时起，我们一直在使用代理、技能、MCP、工具包、自定义内部框架，并且不停地运行Opus 4.7。
现在，在公司层面上，已经安排了一些“鼓励参加”的研讨会，旨在学习如何优化代币的使用，因为API定价在企业层面上逐渐成为常态。
我从直接领导那里得到的指示非常明确。人工智能/代理主导一切，团队的期望是能够快速推进。但实际上，大多数工程师坦诚地承认：我们对这些内容并不完全理解。尤其是因为代理还在生成架构文档、用户故事需求和验收标准的内容。
我感觉这是一个我直接对这些工具的非确定性输出负责的情况。我的主管给我的任何问题的解决方案，归根结底都是“你需要使用代理、技能等。”
还有其他人经历这种拉锯战吗？情况怎么样？
查看原文
About 6 months ago I joined a new team within a top ten F500 company. My new boss strictly mandated AI use with the key principle being: "You shouldn't be manually writing any code".<p>Since then its been all agents, skills, MCP, harnesses, custom in-house frameworks, and running Opus 4.7 high non-stop.<p>Now at a company level, there are "encouraged attendance" workshops getting scheduled to learn how to optimize one's token use now that API pricing is becoming the norm at an enterprise level.<p>The direction I got from my direct leadership was very direct. AI / agents lead everything and the expectation is the team moves as quickly as it has. But the truth is most engineers candidly acknowledge: we don't fully understand anything. Especially because agents are also churning out the content of architectural documentation and user story requirements and acceptance criteria.<p>I feel like this is a situation where I am directly responsible for the non-deterministic output of these tools. The solution I get from my supervisor for any problem literally boils down to "You need to use an agent, skill, etc.".<p>Is anyone else going through this tug of war? How is it going?