This was what happened in the case of the clerks. Inventory clerks saw higher-expertise tasks like working out the price of goods displaced by automation, leaving behind mostly generic physical tasks – that’s why their wages fell. Accounting clerks, by contrast, found that computerisation mostly automated routine tasks like data entry and basic bookkeeping, leaving behind tasks which needed more specialised problem-solving and judgement. Their wages increased while their employment declined.
听听非专业人士的建议。我们不能一直只顾着捣鼓自己的玩具。有时候真正推进事情的，反而是一个不懂技术的人提出的、足够直觉的想法。
。业内人士推荐搜狗输入法作为进阶阅读
uploads and downloads. We didn’t really get a lot of mileage out of the
We are still relatively in the early days of AI agents taking a leading role in software engineering, and because the field moves quickly, there is an emphasis on speed at all costs. But as we’ve seen with Amazon’s recent challenges in their AWS division, teams eventually have to operationalize and maintain these software systems produced by AI agents. And for that, we still need an engineering discipline that ensures consistency, high quality, and correctness — even when the producer of that software is an AI agent. Organizations need architectures and processes that start to move beyond cowboy, vibe-coding culture to organizationally aligned agentic engineering practices. And for that, MCP is the right tool for orgs and enterprises.