#side project话题下的最新新闻、事件- news.news·换个方式看新闻|AI看新闻、实时追踪事件后续

4小时前

晚上继续搞我的 Side Project：用 Swift 重新实现 Beancount。由于之前实现的已经差不多了，我今天决定搞一个延伸版本：用 SwiftUI 重新实现 Fava，利用之前实现的 Swift 的 BeancountKit 库。还是和之前一样，Plan + Implement，本来我今天只是想重写一些 Fava 的核心抽象层的（它基于 Beancount 的核心数据做了更进一层封装），但是你懂的，Claude 总是会过度发挥——直接完成了很多核心抽象层+部分 UI，因为它看到了我创建的 SwiftUI ContentView 之类的东西，就哼哧哼哧的填进去了。因为我还没有对 UI 做任何指示，这个模样是 Claude 自行完成的，我已经很满意了，可以说已经有了一些雏形。看来一款原生+本地的 Fava 客户端会比我预期中的完成要快。

#side project #SWIFT #SwiftUI #Fava #Claude

图拉鼎

1天前

我太容易分心了，我给自己定的目标是一周的工作时间要有 80% 花在那个「主营项目」上，并以每周为单位进行调整。结果我上周临时 Vibe Coding 在一个 Side Project 进入了状态，花了 65% 的时间…我决定放松标准，每周有 60% 的时间花在主营项目上，就算达标了。

#分心 #目标调整 #side project #Vibe Coding #工作效率

Jason Zhu

1周前

大家都爱问“你们现在在搞啥” 但我更好奇这些杂乱无章的 side project 它们什么时候会悄悄变成人生主业？去年我还在喜马拉雅写算法，每天通勤三小时，副业就是倒腾点小项目。身边朋友都劝我专注主业，但我一直忍不住手痒，想试试各种看起来没什么用的小想法。有些 side project 做着做着就荒废了，有的突然爆了，变成收入的主力，甚至影响了职业路径。比如早年间倒鞋，看着像玩票，结果一年赚了近20W；后来开发小工具，本来就是自用，没想到上线后被一堆人买单。主业和副业的界限，有时候真没那么清楚。你永远不知道哪一个不起眼的 side project，会成为你人生的主线。

#AI掘金：知识付费新机，流量为王时代· 123 条信息

#副业 #side project #个人项目 #职业发展 #可能性

XiaoPeng

2个月前

现在AI编程工具这么强大，我需要一个财务模型来评估我如何选择AI编程工具了。原来我只需要大概30刀左右的开销，基本上记为个人日常开销了。如果我算作Side project开销那么我应该谨慎衡量ROI。平均下来，我现在每个月从Side Project分到我个人大概500USD左右。是否应该/值得拿出$100来订阅Claude Max? 如果超了是否可以追加？成本收益如何计算？如果把问题扩大到团队又如何计算？

#AI编程工具 #财务模型 #side project #Claude Max

61

2个月前

放假适合 Side Project，来公司给我的 Side Project 收尾，测试一下同事 In Review 的任务，提交 1.0 审核

#放假 #side project #公司 #测试 #同事 #审核

Prakash (Ate-a-Pi)

6个月前

Deepseek is not a “side project”. At the same time employees are not lying when they say it is. The story they are telling is myth making in the same vein in the Silicon Valley “we want to make the world a better place” but at the same time make billions of dollars. The team obviously had - access to more than ~10k GPUs - according to Scale AI CEO ~50k - was hiring only from top 3 universities from China meaning competitive with Alibaba and Tencent These two facts alone mean that they were clearly commercially successful and well known enough to get access to both those resources Deepseek feels more to me like skunkworks, perhaps a necessary one as the core quant business became less feasible regulatorily. It’s like Lockheed setting up a separate small team to compete with SpaceX because the main United Launch Alliance was not going to work out. It’s also very hard to track costs in China, because the regional governments absorb so much costs. - Early Bitcoin miners had free power because governments built power plants to nowhere and miners were willing to site next to them - Alibaba was able to get regional govt to absorb warehouse construction costs on their balance sheets rather than directly pay for it, and looked extremely asset light and softwarey when it went public Perfectly possible for most of the costs to be parked on a balance sheet outside the core business, perhaps as some form of tech data center construction incentive. Also possible no one except the founder knows all the financial arrangements. Some of these can be absolutely insane handshake deals which get resolved by reputation alone so 🤷‍♀️ This much is clear: - the model is really really good, on par with OpenAI release from 2 months ago - having said that unreleased models from OpenAI and Anthropic are (probably) better - the research agenda is still being set by the US firms, this model was a fast follow on the o1 release - they are working very fast as they are catching up sooner than expected - they are not copying or cheating, this isn’t industrial espionage. At most it is reverse engineering - they are largely developing their own talent, not reliant on US trained PhD’s - they are less constrained than the American firms by IP licensing, privacy, safety, political concerns around wrongly ingesting data from people who don’t want to be trained on. Fewer lawsuits, lawyers and less caution - they also seem to be over the “Tiananmen Square” issue. The model can say it, even if the Deepseek website doesn’t Of these the most significant upgrade is that they are able to develop talent internally without relying on US trained PhDs. That expands the pool significantly. What happens next ?

#DeepSeek #Silicon Valley #side project #myth making #startups