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This is another site that needs the "invite code" for new users to register? I know the arguments of controlling the influx of new people and having a trust-cha

This is another site that needs the "invite code" for new users to register? I know the arguments of controlling the influx of new people and having a trust-chain so that comments are decent etc... but it just feels so elitist. I just find hypocrisy in the contrast of: - hey, we're a cool new site, we'd like your attention - but you can't be part of the party, you're not one of the cool kids

Jugurtha 6y ago
>This is another site that needs the "invite code" for new users to register? I know the arguments of controlling the influx of new people and having a trust-chain so that comments are decent etc... but it just feels so elitist. Well, we're guilty of that, too. It's not about elitism, we let thirty of our colleague's students use our ML platform[0] for their final year projects, and send invites to people who go to our Slack workspace. There are some things to fix before we can onboard everyone, that's all. I don't say they're doing it for the same reasons, but it's not necessarily elitism. It can be limited resources, etc. >but you can't be part of the party, you're not one of the cool kids You're one of the cool kids. Where do I send the invite link? - [0]: https://iko.ai https://iko.ai
- code_scrapping 6y ago
  Like I said - I understand that there's probably a good reason why you're limiting user numbers, but it's a bad mechanism for doing so. Good luck, I'll take a pass on the invite, and wait for the site to become open, if that happens. As you're not limiting viewing of articles, I'm not losing much, and the biggest downside is that you'll miss-out on the early adopters and hype-surfers, but mostly it's just bad PR.
  - Jugurtha 6y ago
    I think you may have missed the part that explains we're not the original link. I'm not OP. I was explaining why we're doing it on https://iko.ai https://iko.ai to manage compute resources, as it is a machine learning platform. Early users help make the product acceptable for a wider audience. Building product in a void and launching is not the way to go in my opinion. The fact you take a pass means you don't need it that badly. Generally speaking, early users do need the product badly and are willing to accept certain imperfections, and have extremely helpful feedback to improve the product so it eventually becomes appealing to a wider audience. The pattern also helps limiti g the number of disappointed people. When it is a low stakes 'job to be done', you can open for everyone. When it's a bit more demanding, you need to get a few things right. Again, I'm not OP and the product I'm talking about is something else.
    - code_scrapping 6y ago
      Thanks for clarifying, you're right - I missed the fact that you're not talking about the same product. Thank you for the offer, but you're right - it would be lost on me. > early users do need the product badly and are willing to accept certain imperfections Agree on the second, but the first parts is a wild exaggeration. You get to discover that for yourself.
      - Jugurtha 6y ago
        >You get to discover that for yourself. We spent seven years delivering ML products to enterprise, and are building something based on what we discovered. However, this is not a photo sharing application where the use case is very narrow and one developer is enough to pin-point the need and execute on it. This is a meta-product that enables people to build products. There is some complexity in that the ML landscape is varied and it is precisely why many are trying to do that. We can discover part of this and we did, but we want to uncover more by having users try it out. A concrete example: during the first months of the pandemic, our colleague had thirty students with machine learning final year projects. These were in a hot COVID spot. We had total lockdown, and these students did not have the possibility to go to university to access computers. They also did not have means to buy a costly workstation just for the project. We onboarded them on the platform as "early users" so they could train machine learning models, deploy them, and build applications that used them, and as a result, were able to graduate on time. Now, I don't know what you think of that approach, but preventing 30 students from losing an academic year is not a bad thing. Did the platform suck in some ways? Absolutely. They graduated on time, though. 30 * one academic year = 30 years saved because that product, even in its primitive form, existed. We can either develop in a void and wait until the product is complete and perfect to show to the world and allow everyone to use it, but I don't think anybody who actually shipped useful products in their life ever does that. Whenever someone asks how they could focus more when building their product, even a personal project, I tell them to get the right kind of users. Early users help uncover the unknown, and help focus on some of the knowns. For example, you have a long backlog. Without users, prioritizing can be done but is tricky. With users: after the 20th user complains about a bug/UX, you know what your next issue/ticket is going to be. The result is faster development on what matters, and the consequence is instead of shipping the product to the wider audience in a year, it'll be in 6 months. Having early users helps tear down things we might have ignored and accelerates bringing this value to more users.

Jugurtha 6y ago

>This is another site that needs the "invite code" for new users to register? I know the arguments of controlling the influx of new people and having a trust-chain so that comments are decent etc... but it just feels so elitist. Well, we're guilty of that, too. It's not about elitism, we let thirty of our colleague's students use our ML platform[0] for their final year projects, and send invites to people who go to our Slack workspace. There are some things to fix before we can onboard everyone, that's all. I don't say they're doing it for the same reasons, but it's not necessarily elitism. It can be limited resources, etc. >but you can't be part of the party, you're not one of the cool kids You're one of the cool kids. Where do I send the invite link? - [0]: https://iko.ai https://iko.ai

code_scrapping 6y ago
Like I said - I understand that there's probably a good reason why you're limiting user numbers, but it's a bad mechanism for doing so. Good luck, I'll take a pass on the invite, and wait for the site to become open, if that happens. As you're not limiting viewing of articles, I'm not losing much, and the biggest downside is that you'll miss-out on the early adopters and hype-surfers, but mostly it's just bad PR.
- Jugurtha 6y ago
  I think you may have missed the part that explains we're not the original link. I'm not OP. I was explaining why we're doing it on https://iko.ai https://iko.ai to manage compute resources, as it is a machine learning platform. Early users help make the product acceptable for a wider audience. Building product in a void and launching is not the way to go in my opinion. The fact you take a pass means you don't need it that badly. Generally speaking, early users do need the product badly and are willing to accept certain imperfections, and have extremely helpful feedback to improve the product so it eventually becomes appealing to a wider audience. The pattern also helps limiti g the number of disappointed people. When it is a low stakes 'job to be done', you can open for everyone. When it's a bit more demanding, you need to get a few things right. Again, I'm not OP and the product I'm talking about is something else.
  - code_scrapping 6y ago
    Thanks for clarifying, you're right - I missed the fact that you're not talking about the same product. Thank you for the offer, but you're right - it would be lost on me. > early users do need the product badly and are willing to accept certain imperfections Agree on the second, but the first parts is a wild exaggeration. You get to discover that for yourself.
    - Jugurtha 6y ago
      >You get to discover that for yourself. We spent seven years delivering ML products to enterprise, and are building something based on what we discovered. However, this is not a photo sharing application where the use case is very narrow and one developer is enough to pin-point the need and execute on it. This is a meta-product that enables people to build products. There is some complexity in that the ML landscape is varied and it is precisely why many are trying to do that. We can discover part of this and we did, but we want to uncover more by having users try it out. A concrete example: during the first months of the pandemic, our colleague had thirty students with machine learning final year projects. These were in a hot COVID spot. We had total lockdown, and these students did not have the possibility to go to university to access computers. They also did not have means to buy a costly workstation just for the project. We onboarded them on the platform as "early users" so they could train machine learning models, deploy them, and build applications that used them, and as a result, were able to graduate on time. Now, I don't know what you think of that approach, but preventing 30 students from losing an academic year is not a bad thing. Did the platform suck in some ways? Absolutely. They graduated on time, though. 30 * one academic year = 30 years saved because that product, even in its primitive form, existed. We can either develop in a void and wait until the product is complete and perfect to show to the world and allow everyone to use it, but I don't think anybody who actually shipped useful products in their life ever does that. Whenever someone asks how they could focus more when building their product, even a personal project, I tell them to get the right kind of users. Early users help uncover the unknown, and help focus on some of the knowns. For example, you have a long backlog. Without users, prioritizing can be done but is tricky. With users: after the 20th user complains about a bug/UX, you know what your next issue/ticket is going to be. The result is faster development on what matters, and the consequence is instead of shipping the product to the wider audience in a year, it'll be in 6 months. Having early users helps tear down things we might have ignored and accelerates bringing this value to more users.