Rebuild this Angular 6 project in the latest version of React
大概也就是未来一到两年，码农职位因为AI会减少25%。未来十年会码农职业会消失。 https://levelup.gitconnected.com/chatgpt-will-replace-programmers-within-10-years-91e5b3bd3676 Phase 2: Advanced IDE Tooling and Consolidation (1 — 2 yr) Phase 2 will organically emerge from Phase 1, as IDE tooling gets more sophisticated. The entire codebase will provide context to the AI, which will then be able to make project-wide suggestions like:
Add 100% unit-test coverage to the project
Refactor all model classes into a separate library using Gradle and Java 17
Change the security model from OAuth to SAML
This will drastically improve legacy codebase maintenance and migration. As millions of engineers apply such changes, usage patterns will emerge and be used to train the next generation of tools. As the traditional IDE becomes a mere vessel for AI, such suggestions will be auto-applied. For example, why wouldn’t every codebase get 100% unit-test coverage? In fact, it should happen automatically in the background as we code. This period will be known as the great consolidation. Long-held competitions between frameworks will be decided by which is the most AI-friendly. For example, imagine one could safely upgrade a legacy JS codebase to React with a single button click, but doing the same migration to Vue would take a week. Even if there are viable reasons to choose Vue, ultimately frameworks that adapt quickest to AI integration will prevail. Such an arms race will occur in programming languages as well. For example, imagine you inherited a slow-performing code base written in Python. Your IDE suggests it be translated to Rust. You click “yes” and redeploy, and the app is suddenly 10X faster. The same goes for protocols — why bother with HTTP when everything can easily be gRPC? Let’s get off of FTP and .md5 while we’re at it. Finally, Phase 2 will also bring the advent of the AI-CD pipeline. It’s not difficult to imagine a CD pipeline that can learn deployment patterns. For example, an AI that tweaks Kubernetes configuration based on traffic daily. Or even goes as far as to rebuild the application in different tech stacks to optimize performance and server cost. Job Loss Prediction: 25%
Even though ChatGPT passed law and business school exams, those areas are less accessible to AI. For example, the law involves physical evidence, courtrooms, and paperwork, which would require robotics, a field wherein making a pizza is a breakthrough. And due process involves red tape, jury selection, appeals… things rate-limited by human time scales. By comparison, software engineering is entirely digital, exponentially scalable, and always behind schedule. It’s the perfect target for a hostile takeover.
大概也就是未来一到两年，码农职位因为AI会减少25%。未来十年会码农职业会消失。
https://levelup.gitconnected.com/chatgpt-will-replace-programmers-within-10-years-91e5b3bd3676
Phase 2: Advanced IDE Tooling and Consolidation (1 — 2 yr) Phase 2 will organically emerge from Phase 1, as IDE tooling gets more sophisticated. The entire codebase will provide context to the AI, which will then be able to make project-wide suggestions like: This will drastically improve legacy codebase maintenance and migration. As millions of engineers apply such changes, usage patterns will emerge and be used to train the next generation of tools. As the traditional IDE becomes a mere vessel for AI, such suggestions will be auto-applied. For example, why wouldn’t every codebase get 100% unit-test coverage? In fact, it should happen automatically in the background as we code. This period will be known as the great consolidation. Long-held competitions between frameworks will be decided by which is the most AI-friendly. For example, imagine one could safely upgrade a legacy JS codebase to React with a single button click, but doing the same migration to Vue would take a week. Even if there are viable reasons to choose Vue, ultimately frameworks that adapt quickest to AI integration will prevail. Such an arms race will occur in programming languages as well. For example, imagine you inherited a slow-performing code base written in Python. Your IDE suggests it be translated to Rust. You click “yes” and redeploy, and the app is suddenly 10X faster. The same goes for protocols — why bother with HTTP when everything can easily be gRPC? Let’s get off of FTP and .md5 while we’re at it. Finally, Phase 2 will also bring the advent of the AI-CD pipeline. It’s not difficult to imagine a CD pipeline that can learn deployment patterns. For example, an AI that tweaks Kubernetes configuration based on traffic daily. Or even goes as far as to rebuild the application in different tech stacks to optimize performance and server cost. Job Loss Prediction: 25%
要这样就好了，但是感觉现在AI是野蛮生长，不会按我们希望的顺序。
这个是最难的，最容易取代的居然是码农。
不止我们，律师医生会计也玄得很。😂 我觉得码农和硅工气会略长一些，毕竟可能还有些架构性的东西要搭起来。
Even though ChatGPT passed law and business school exams, those areas are less accessible to AI. For example, the law involves physical evidence, courtrooms, and paperwork, which would require robotics, a field wherein making a pizza is a breakthrough. And due process involves red tape, jury selection, appeals… things rate-limited by human time scales. By comparison, software engineering is entirely digital, exponentially scalable, and always behind schedule. It’s the perfect target for a hostile takeover.
你需要定义什么是AI程序员？
以前只有ASM的时候，码农都是用宏汇编编程。 后来来了一个AI，叫做C。 结果汇编编程的码农就死了。 但是产生了C码农。
将来IT人员不一定是码农，主要可能都是AI assisted project manager.
时代不同了，据陆奇说chat gpt 4 在开发 chat gpt 5 😱
类似的，原先五个律师五个paralegal，变成两个资深律师1个paralegal在AI 协助下完成同样工作量。
越是低端的，不需面对客户的，日常性的工作，越容易被取代。
其实低端的coding 应该是AI 最为擅长的事。高技能的码工很安全的。
先取代低端马工，10年内连资深马工也都被取代了
手机上看不到
一堆蹭热度的。估计自己都不知道自己说什么。
亚麻推出云计算大家都认为Sys Admin 和 Network Admin都要没工作了。
谁想到云计算反而让架构更复杂了。各种职业证书更多了。Sys Admin和Network Admin摇身一变成了DevOps，更加高大上。
这基本是业界共识了，没有AI不能取代的白领工作，问题是需要多久。
俺就是搞不明白为啥说起 AI， 都觉得 AI 是石头里蹦出来的产物呢？
AI 的码谁写？写完谁去 maintain 谁去 update？？？
未来码农范围只会扩大不会缩小，别想得美了。
取代程序员是共识？这是不懂行的人的共识吧。
我就是业界的，没有这个共识：（ 写代码就像做数学题，有的题以前有人做过，网上有答案，ai也许比stackoverflow好用 有点的题以前没人做过，ai也不可能会，它不会逻辑
是啊，感觉大家觉得AI就是石头缝里蹦出来的孙猴子🐒自带十八武艺
这也是我的想法. 感觉未来社会很适合我这样眼高手低的人. 每次搞明白一个东西怎么实现, 中间难点过一遍没问题后就不想干了, AI 如果能填补这个空缺就太好了. 而且我还特喜欢对别人的code指指点点, AI 态度那么好, 简直perfect.
不是吧？logical reasoning 对 AI 是可以handle 的吧。
低端码工涉及的简单逻辑，不能被取代？减少outsource 到印度的工作，不可能？
印度的ICC估计是先用上AI的公司，因为他们处于产业链低端，对成本最敏感。
讨论的是前瞻性，不是今天当下的状况。同意不可能完全取代高技能码工。
编程需要自主意识？低端码工每天带着自主意识去编程？自主意识是指人类认识和理解自己的情感的能力。编码不需要用到自主意识吧？
要是被陪聊的老人自杀了，被哄的小娃出了安全或者精神问题，咋办？
你想多了。你这个就相当于前一两年热钱多的时候，码农们经常收到email，我有如何如何的idea，就等着程序员加入我们来实现了
不完全一样，现在的ide辅助工具可以从你写过的代码和注释里学习，来猜测和建议你想写的代码。有些做的还相当不错。不过要是你要实现的logic是新的，目前的推荐就南辕北辙了。目前看不出来能很快有改进。不过就算是建议辅助重复代码，也极大提高了工作效率。
可太有意思了，您听说过machine learning吗、
我觉得井喷不了。AI如果能达到产业革新，那是能够急剧缩减IT和其他行业的从业人员的。
openAI的创业维护团队还不到500人吧？Midjourny的团队据说只有11人，这么少的人员就能做出这么出色的AI产业，未来喂给AI模型的主要是数据，至于AI从业人员，可能就是调调参数，（哦，现在还有个人工帮AI学习矫正答案的阶段），能触及修改AI整体设计算法结构的天才少之又少。
你不用活得这么明白吧
它要是写出来东西有毛病，得有人去排查吧？它要是能运行但是算出来是错的，那可毁了！得不停地有人给它改错更新。还不得全世界受过教育的都是码农，才能维持这个东西？我现在觉得学任何行业的人，都必须会写码了。不然本行业的东西，AI给你全搅合坏了。
我是觉得它会倒逼其他行业的人特别是所有的工程师全部兼职码农。
是的，AI就只需要一小批天才
没听过能从石头里蹦出来 的 machine learning
被取代的低级程序员又不是写AI的那批人。
生成式AI会对一些常用问题产生同一性，减少多样性，大规模使用还是有不少缺陷，因为大数据不是世界的全部。比如很多参观者可能都问 ChatGPT ” LA 最好的5家餐馆是什么？“，如果得到的答案都类似，那只是加剧了赢者通吃的趋势，最后很多人去了这些餐馆，很多人可能排很久或者没位置，反而徒增不便。就算加入实时的排位数据，使得一些人分流到5-15名的餐馆，这种类似的答案也破坏了多样性和加剧市场失衡。
简单说，AI会改变很多生活和工作形式，除了代替很多原有的职业，也会涌现更多新职业。其中码农在可见将来是不会大量消失的。
现在都是大型数据训练出的模型，其他人只是拿来用用，你们公司没可能有财力自己训练，更不要说员工去改它的错。
举个例子，微软windows经常更新系统打补丁，你参与过排查改错更新吗？
当然能，现在给AI一个数据，已经可以做数据分析，给出policy建议，人也是根据用户数据去想新feature，不是拍脑袋的，照抄竞争对手更不是问题。
是的,低端的很容易被取代,高级码工是不会被取代的,可能需求量更大,小本就不好说了,博士毕业senior的各个大厂高级研发部门的应该不会被取代,当然小本还是不容易进这些组的,人家那么年博士不能白读啊,个别厉害小本有可能弯道超车,但是大多数人都是普通人
AI 现在是一个黑盒， 产生出来的code 很难reasoning， 所以对于简单的应用来说还好， 对于复杂的应用， 谁都看不懂的东西，敢上线？ lz 给的example 里， 没有migration plan， 这样的code 敢上线？
我认为未来的编程可能变成， prompt + 人工的形式: 自然语言描述问题， AI 给出一个解作为参考， 可以很快的prototyping。 对于非常具体的实现， 估计拿来用也可以， 反正有unit test。 对于大的变动， 还是需要人工来介入，或者不断的refine。
但是没有这95%的人，5%的生活质量会极大的提高，或者先除掉这些没用的人，再通过基因编辑生成一些有用的人