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 On the occasion where the README.md code is out of date, it's been easy for me to check pkg.go.dev and update it myself.
Also, most of this can be automated with `go install golang.org/x/tools/gopls/internal/analysis/modernize/cmd/modernize@latest && modernize -fix ./...`
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.
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 ).
First, thanks for this. It's a lot of work to support OSS and I appreciate the effort of you and the team.
Second, is there any way for new users to determine the maturity of each of the (many) generators available? I haven't seen it in the documentation or the github repo, but maybe I missed it?
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.
Of note, I've found this to be very important with AI generated code, where it's easy to grok and refactor AI code.