andendau

Agreed. I think with the pace of change happening more frequently it might require more disciplined focus on training, constraining systems, and number of products.

Seems like a narrow view of developer tools. Isn't this the bread and butter of GitLab/Microsoft and others? I work in a dull industry and the perception isn't we need new tools to understand our abstractions. The main challenges I run into are that we need more staff to run and maintain new ways to work with our APIs. How do we keep track and find our APIs? Who owns the database? Am I allowed to connect to this database? My main job is to figure out how to make an on-rails experience so that when a developer leaves after two years new ones aren't relearning the flavor of the month pattern or tech someone wanted to try. It's a broad enough problem I'm sure it can be productized if you keep it general enough.

There's some level of friction in working with databases. Not insurmountable but painful.

I loved the ML based emphasis. I'm a big fan of f# unfortunately as the article details .net has a shadow of the libraries that Java has. Clojure and Scala have much broader access to popular libraries. I've found most developers are ok with the hum drum c based languages thus c#, java, golang are good enough for most people with no interest to jump the chasm to an ML inspired language.

Any plans on open sourcing this or making the code available?

Do you support on-premises kubernetes?

yes good product management is key even though your customers may not have a choice

Great book highly recommended

Nice job! I had a good experience as part of the applied machine learning data science coursera specialization. The cloudant support was great to have.

It's a great testing resource. Way more concrete than 'well just test all the different strings'

Never Split the Difference is really good highly recommended and based in science.