Grokify

Working with LLMs feels more like management when I'm working with multiple LLM coding sessions on the same code base, either multiple LLMs making commits to the same repo, or LLMs doing code review on another LLM's work.

Leadership is more about setting vision and goals. The more agents are given agency to achieve goals, the more it feels like leadership.

This seems to be primarily an issue with a few specific package management solutions that have suffered SCA vulnerabilities recently, not generaly across the board.

Stack Overflow was a nice experience for me because I was able to hit 2k reputation fairly quickly, in just 30 days of posting and 6 weeks calendar time. That being said, it never had the community feel of places I spent during my formative years, which were more on forums and IRC.

Here's a conference talk I gave on how to gain Stack Overflow reputation from back in 2018, selected out of 5 submitted talks. It's amazing how fast times have changed from before, during, and now after.

https://grokify.github.io/stackoverflow-the-hard-way/

Digg was a major site that had a surprisingly fast turn of events. There are some good lessons from that.

Good reference, along with the article. I built a SVG sanitizer in Go and will look to these to make it more strict.

That's a great idea and a very nice project. It's great that to move back to curated blog lists from thoughtful authors.

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/

That's not the intention. The intention is:

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.

Agree it will be interesting to see how things play out. There's enough permissive open-source licensed code available that using that only could be an option.

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

I've found that for API integration, developing against a spec, like OpenAPI, and using/building an auto-generated SDK is still very useful for coding agents.

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.

Given that Claude is attributed to 19M+ commits on GitHub, it will be interesting to see where this ends up. Specifically on copyright, it will be interesting to see if any DMCA takedown notices are filed, including popular projects such as OpenClaw, GSD, Gas Town, Vibium, and others.

More on the 19M+ commits here:

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

If there's any stolen code generated by AI, it's certainly not intentional and a DMCA notice would be appreciated. It would be interesting to see how prevalent this is in AI generated code - is anyone doing a study?

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.

Open source has never been more alive for me. I have been publishing low key for years, and AI has expanded that capability more than 100 fold, in all directions. I had previously published packages in multiple languages but recently started to cut back to just one manually. But now with AI, I started to expand languages again. Instead of feeling constrained by toolchains I feel comfortable with, I feel freedom to publish more and more.

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.

This. Maintainability and refactorability are some of the major Go superpowers for me which enables getting into any code base and updating it. These are supported by features like static typing, fast compile times, etc.

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

I enjoy the Go ecosystem quite a bit and haven't found many issues with documentation. I love how open source modules are documented on pkg.go.dev, including those from major providers, like AWS, Google, etc. Every library has the same references. When examples are useful, such as with charting modules, I've found that the projects do provide them. On the occasion where the README.md code is out of date, it's been easy for me to check pkg.go.dev and update it myself.

A good example is io/ioutil. It's useful to migrate to eliminate the deprecation messages, but you don't need to do it right away.

I still get substantial value out of Coursera. I started with Andrew Ng's original Machine Learning course way back when, and recently completed classes that I thought were well worth my time on Claude Code, Crew AI, AutoGen, and MCP.

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.

AsciiDoc may have a naming issue. I'm speculating that it's not restricted to the ASCII character set but the immediate question that comes to mind is what is restricted to ASCII and if it can support Unicode or even ISO 8859.

What is your language?

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

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

Disclosure: I'm a contributor to the project.

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 ).

It would be great if that information was published.

I received a full tuition scholarship to BU.

Back in the day, I used SuperShuttle over taxis for airports, but when ridesharing arrived, it was just much more convenient. For early morning flights, there was no more getting up super early so you can be on a shuttle that picked up a few more people.

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.

Lyft also has a similar color as T-Mobile. Did T-Mobile make the same ask of Lyft?