How many billion dollar companies were built on dynamically typed languages? Do you think that companies/bosses/investors care about the compiler warnings or whether you can deliver/iterate faster than the competition?
nobody likes plumbing, but we all know it’s necessary.
Is it, really? Are we all working on mission critical software? We are living in a world where people are launching usable applications with nothing but the prompt to an LLM, ffs, and you are there trying to convince yourself that pleasing the Hindley-Milner gods is fundamental requirement in order to deliver anything?
Good engineering is about understanding design constraints and knowing where to choose in a myriad of trade-offs. It’s frankly weird to think that such an absolute, reductionist view like yours got so much support here.
I care about types not just because I like having stronger confidence in my own software, but because, as a user, bugs are really annoying, and yes, I’m confident that stronger type systems could have caught bugs I’ve seen in the wild as a user.
I don’t really want to be talking past each other. The point I am refuting is that even if type-safety can help reduce the amount of bugs shipped, this is not the only metric that matters to measure the value of the software being developed.
bugs are really annoying
And being late or never delivering out of fear of shipping buggy code is even worse.
Some years ago, I worked on a crypto project that was financed via an ICO. This meant that whatever money the company was going to get was already in their hands, and their only job was to make sure they could prove they’ve done a best effort to deliver what was promised to investors.
Because of these incentives, the engineers were more concerned about covering their asses regarding bugs than to actually get the software out in the hands of users. The implementation was in python, and to the team it was easier to justify spending time on getting 100% mypy coverage than to get things in hands of users to see the value of what we promised to deliver.
In the end, by the time the team managed to deliver, the code was super well-tested, there were 0 mypy warnings and absolutely zero interest from other people in adopting our tool because other competitors have launched a whole year before them.
How many billion dollar companies were built on dynamically typed languages? Do you think that companies/bosses/investors care about the compiler warnings or whether you can deliver/iterate faster than the competition?
Is it, really? Are we all working on mission critical software? We are living in a world where people are launching usable applications with nothing but the prompt to an LLM, ffs, and you are there trying to convince yourself that pleasing the Hindley-Milner gods is fundamental requirement in order to deliver anything?
Good engineering is about understanding design constraints and knowing where to choose in a myriad of trade-offs. It’s frankly weird to think that such an absolute, reductionist view like yours got so much support here.
I care about types not just because I like having stronger confidence in my own software, but because, as a user, bugs are really annoying, and yes, I’m confident that stronger type systems could have caught bugs I’ve seen in the wild as a user.
I don’t really want to be talking past each other. The point I am refuting is that even if type-safety can help reduce the amount of bugs shipped, this is not the only metric that matters to measure the value of the software being developed.
And being late or never delivering out of fear of shipping buggy code is even worse.
Some years ago, I worked on a crypto project that was financed via an ICO. This meant that whatever money the company was going to get was already in their hands, and their only job was to make sure they could prove they’ve done a best effort to deliver what was promised to investors.
Because of these incentives, the engineers were more concerned about covering their asses regarding bugs than to actually get the software out in the hands of users. The implementation was in python, and to the team it was easier to justify spending time on getting 100% mypy coverage than to get things in hands of users to see the value of what we promised to deliver.
In the end, by the time the team managed to deliver, the code was super well-tested, there were 0 mypy warnings and absolutely zero interest from other people in adopting our tool because other competitors have launched a whole year before them.