I've been doing something similar specific to my interests so far. Will check yours out.

Here's my "Planet AI": https://grokify.github.io/planet-ai/

And some selected article/discussion analysis: https://grokify.github.io/frontierpulse/

1. The code generated should be available to use. Some languages are simple enough there is an obvious way to do it. Many companies have developer programs with staff producing code intended to be used in the form of open source SDKs, example code, and tutorials.

2. If on the off chance, there is code that shouldn't be there, people should use DMCA. Anthropic, GitHub, and others support this.

3. At the macro level, it's hard to know know where this is going, so we should look to bellwether apps with more attention for guidance.

As for Mickey, is the difference from Oswald enough today?

When there is no spec for REST APIs, I built a tool that can convert HAR files, Postman collections and other data to OpenAPI spec from which I build client SDKs for coding agents to use.

More on the 19M+ commits here:

https://news.ycombinator.com/item?id=47501348

Stars will likely go up over time, but more than the stars it's the testing and maintenance over time that's valuable. There's little promotion right now, but there are already some stars, PRs, and issues. In fact, I'm working on merging PRs now.

The benefits to publishing AI generated code as open source are immense including code hosting and CI/CD pipelines for build, test, lint, security scans, etc. In additional to CI/CD pipelines, my repos have commits authored by Claude, Dependabot, GitHub Advanced Security Bot, Copilot, etc. All of this makes the code more reliable and maintainable, for both human and AI authored code.

Some thoughts on two recent posts:

1. 90% of Claude-linked output going to GitHub repos w <2 stars (https://news.ycombinator.com/item?id=47521157): I'm generally too busy to publishing code to promote, but at some time it might settle down. Additionally, with how fast AI can generate and refactor code, it can take some time before the code is stable enough to promote.

2. So where are all the AI apps? (https://news.ycombinator.com/item?id=47503006): They are in GitHub with <2 stars! They are there but without promotion it takes a while to get started in popularity. That being said, I'm starting to get some PRs.

Of note, I've found this to be very important with AI generated code, where it's easy to grok and refactor AI code.

While not revolutionary, a recent improvement is AI-based review, which is much appreciated for it's near instant review.

From a transformative perspective, I like the AWS Skill Builder SimuLearn classes. They say teaching is one of the best ways to learn, and I found the chat-based role play where you are the expert to be very interesting.

I've found kin-openapi to be very usable for Go:

https://github.com/getkin/kin-openapi

OpenAPI Spec and auto-generated API clients are very useful when multiple languages need to be supported, like when running a developer program. I've worked at companies that both use OpenAPI Generator for official clients and ones that wrote our own tools for API client SDK generation (with different design philosophy). I've used a number of generators myself to compare and submitted fixes / enhancements to OpenAPI Generator. I used the Go client generator a while back and compared it to others, and recently started using the Crystal one.

To get the most the project, the following is useful: (a) need to support multiple languages, (b) ability to update the generator's code, both in Java and templates (Mustache or Handlebars), and (c) ability to discuss design in GitHub issues and the Slack channel.

The nice thing about OpenAPI Spec is that there is an ecosystem of tooling to support it, including rendering API references (HTML and PDF), API explorers (HTML pages to execute API calls), API clients, etc. But there is a learning curve. For writing specs by hand, I use and favor the Stoplight Studio IDE ( https://stoplight.io/studio ). For programmatically analyzing and editing specs, which is especially useful for finalizing auto-generated specs, I've built an OpenAPI Spec SDK library to make this easier ( https://github.com/grokify/spectrum ).

I received a full tuition scholarship to BU.

Comments URL: https://news.ycombinator.com/item?id=24758007

Points: 1

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That said, I miss SuperShuttle because I met some really interesting people on it in the SF Bay Area. Some of the more notable people I talked to included one of the original engineers on the Apple Lisa and one of Larry Ellison's private plane pilots. It was neat to listen to stories from both.