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Comment · 3 years ago
that's a good approach. haha
Comment · 3 years ago
google is the main source. also there are some github repositions and reddit links.
Comment · 3 years ago
Hey jruohonen, great point. it depends on what does "survive" mean.

Monetize-able GPTs? Not many for sure. What will happen IMO is established companies will build official GPTs to better serve existing customers.

GPTs for personal use? Many GPTs will be abandoned and not be used by anyone. That's okay for one-off use cases.

There will be a loooooong tail of GPTs that people would use from time to time. There will be a lot of diversity but the top GPTs will eventually be like the top apps in the app store IMO.

Comment · 6 years ago
If you're a front-end dev, you'd probably worked with PMs on building features that helps the product grow. This guide covers many of those features.

If you're a backend dev, you'd probably been asked to create database tables to save marketing or business data. AirTable allows many business people to create tables and gather info , and selling info without involving backend dev.

It will be interesting to see how the self-serve business tools (nocode) will affect the type of work devs will be asked to do in the future.

Comment · 6 years ago
Super impressive work since I first saw it on IndieHackers. Congrats!
Comment · 6 years ago
One of the things that bothered me for years was the lack of clarity around Product-Market Fit. So far all the explanations are a posteriori - you can only observe or measure them. E.g. "You've found PMF when you sell it faster than you can make it", or "You can measure PMF by asking your users if they'd be sad if the product is taken away from them".

Can't we systematically get to it step by step instead of observing a big black box?

Last week, one model crystallized in my mind: Product Market Fit consists of 5 "fits" under the surface, each of which can be measured separately, which I summarized in the Twitter thread.

Would like to hear your opinion on if this makes sense to you.

Comment · 6 years ago
Reading an article this in-depth and pure on blogger brings me back to 2004, the good ol' days
Comment · 6 years ago
how does it work? :-D
Comment · 6 years ago
Thanks a bunch!

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