Great article @heathermeeker
. I have a question for you: my company is currently working towards making our codebase open source and we've been really struggling with the argument of competition vs adoption with AGPL.
As a bit of context we're developing tools for other businesses to use when developing their own AI tools and products. We plan to offer our code as open source repositories largely because one of the things our tools are focused on is transparency and auditability and we believe that we have to practice what we preach.
We expect we will be able to build up a modest community of developers/data scientists contributing to the open source tools but our sales market is largely non-data companies who need to use our tools for productivity, audit and regulation of AI tools or products they may be developing with in-house data teams or external data partners.
We intend to host the whole pipeline with a SaaS-like model. For us, AGPL makes business sense. To us it says: "use our code, sell our code, but make sure you contribute back - we're only small and if you steal from us we'll go under" but I am very aware that there are big companies who say no to AGPL and also some community backlash over recent years. Do you have any thoughts or advice on how a small company balances the fear of competition from the big players with the desire to see widespread adoption?
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Great article @heathermeeker . I have a question for you: my company is currently working towards making our codebase open source and we've been really struggling with the argument of competition vs adoption with AGPL.
As a bit of context we're developing tools for other businesses to use when developing their own AI tools and products. We plan to offer our code as open source repositories largely because one of the things our tools are focused on is transparency and auditability and we believe that we have to practice what we preach.
We expect we will be able to build up a modest community of developers/data scientists contributing to the open source tools but our sales market is largely non-data companies who need to use our tools for productivity, audit and regulation of AI tools or products they may be developing with in-house data teams or external data partners.
We intend to host the whole pipeline with a SaaS-like model. For us, AGPL makes business sense. To us it says: "use our code, sell our code, but make sure you contribute back - we're only small and if you steal from us we'll go under" but I am very aware that there are big companies who say no to AGPL and also some community backlash over recent years. Do you have any thoughts or advice on how a small company balances the fear of competition from the big players with the desire to see widespread adoption?