I think being in this bubble of working in and thinking about tech 24/7 can often make us miss the point - these apps are just meant to be tools to do a task.
I think being in this bubble of working in and thinking about tech 24/7 can often make us miss the point - these apps are just meant to be tools to do a task.
It's true that most users don't want to configure remote storage for each app. That's solvable though. There should be a way to store your remote storage preferences and just give each app permission to store there in one click.
I have some vague plans around building a job portal just for startups looking to hire ex-startup founders where the data is not owned by my platform and freely available for everyone to leverage as per user preferences.
I’ve been thinking a lot about the difference between a product and a project. I’m launching an open source project and we need to make it a bit of a product, but I’m hoping to maybe grow a following on patreon or open collective so we don’t have to focus on selling things directly.
Anyway this seems like a cool open source project that might not be trying to be a “product” for the masses.
Just imagine. You use Duolingo to learn a language and it shuts down. What do you do? What's the export format. Will the new product have the same levels / trees/ etc? Very unlikely. You'll have to start all over again. It's not about the raw data, it's about the data that your work has generated.
If you're doing machine learning, then there's the raw data, but there's also all the other data resulting from your hard work: training jobs, experiment tracking, parameters and artifacts and metrics, models.
The question becomes... First, how important is your product in the user's life? If it's important, they'll rely on it a lot and use it a lot to do things that are important for them, or for their organization.
Then, the service needs to provide export options and send you a shutdown notification. These are not always true but, assuming they are, you'll have to scramble to exfiltrate your data.
Then when you exfiltrate your data, it's an export. You'll have to find another product or service, and then somehow hope you can import that data to the new product, and then set up another workflow.
And here I'm talking about consumer products. For enterprise, there are many parameters including who the vendor is, procurement, team size. Meaning if you are Google/Amazon/Microsoft/etc, then a lot of people will treat you like a utility that will continue to be there, even with the track record of some of these of shutting down products and services (how many products has Google shut down over the years).
Look at this thread[0] I posted about our machine learning platform and the conversation that followed. The person objected that as long as it wasn't open source, they wouldn't use it. But digging a bit deeper, it turns out what they wanted wasn't really open source, but open source was one solution/implementation to their underlying problem. Trust you'll be there or control.
- [0]: https://old.reddit.com/r/MachineLearning/comments/kolobf/p_c...
It's true that the limited period of time between end of life and servers going offline may be a problem, but that tends to be a long period of time (3-6 months in general from the services I've used that have shutdown).
Valuable applications more often than not simplify complex things or do hard things behind the scenes. Their value is in the workflow/experience or the processing that takes place on the data, including APIs and integrations to unlock users' creativity.
>It's true that the limited period of time between end of life and servers going offline may be a problem, but that tends to be a long period of time (3-6 months in general from the services I've used that have shutdown).
Again, have you used these as an individual relying on them lightly, or heavily, or as a business/organization where your work relied on these? Have you used them as a user, or as the person who was involved in making the purchasing decision for the whole team/organization?
For business applications, the conversation may be different, but for the consumer ("average non-techie" as the original comment said) I believe what I said holds true.