# Deedy Das：多数软件工程师面临身份危机

- 来源：Deedy (@deedydas)
- 发布时间：2026-06-20 15:44
- AIHOT 分数：46
- AIHOT 链接：https://aihot.virxact.com/items/cmqm2e48700pzsliiix7r0zo1
- 原文链接：https://x.com/deedydas/status/2068238634600554699

## AI 摘要

Deedy Das观察到，随着CTO们极力推崇tokenmaxxing，软件工程师分裂为“懒惰者”与“工匠者”。懒惰者依赖AI代写代码、测试、回复消息，甚至同时胜任多份工作；工匠者则疲于审查堆积如山的PR和Slack消息，同事的AI代码敷衍了事，最终工匠者也放弃沦为懒惰者。这种现象常见于成立超10年的大公司，但并非所有公司如此——部分团队凭借合理的AI开发原则和互信机制仍保持高效。

## 正文

Most software engineers are facing an identity crisis bordering on depression.

As CTOs aggressively evangelize tokenmaxxing， a class divide ensues.

The lazy. The lazy push code. They don't write it. They don't manually test it. They don't even read it. They're on autopilot. See Jira ticket， prompt for task， submit code. Many of them are barely on their computer the whole day. A comment on the PR asking why they did this？ The lazy ask AI. A Slack message？ The lazy ask AI. Need to prepare for standup？ The lazy ask AI. As long as it sounds enough like them and isn't detected. Some of the lazy are even overemployed， and work multiple jobs. The lazy smart ones get away with this， and even rewarded. After all， software engineering for the lazy is just a dance to convince your colleagues you're smart and hard working.

The craftsmen. The craftsmen are tired. Very tired. 15 PRs in queue. Slack blowing up. The entire burden of review falls on the craftsman. The burden of understanding. They try. They work their way through the code， thoughtfully commenting to improve what ships. The response？ A lazy： "That's a clever idea！ You're absolutely right." with an incorrect change. It's fine， the craftsman says. I can fix them. They write a doc urging his colleagues to be better. The next day？ 20，000 line PR to review. Day after day， their workload grows. Bugs seep into production. No one seems to care. Another round of AI is thrown at it. Their animosity to their colleagues rises. Eventually， they give up. It's just not what it used to be. The craft they loved is dead. They eventually wake up， a lazy.

This isn't all companies. Many companies are genuinely more productive， adopt the right set of principles and practices around AI development and have highly talented teams that trust each other. It tends to happen in bigger companies that are 10+yrs old with a higher talent variance. But it happens. A lot.