Thank you for writing this. I actually disagree with a lot of the "PRDs are dead" commentary we're seeing online; the thinking is precisely along the lines of your post (just ship it, don't think about it!).
Love this breakdown, Leah - especially the reminder that velocity without validation is just noise. AI might speed up the 'how,' but it still can’t replace the 'why' behind great product decisions.
I understand the article and agree with it. And it can be summed up when you say "Building a tech and software product that is commercially viable will always be hard".
but I have two questions:
1 - If we use AI along the process of development (at least MVP development) wouldn't we be gaining time in the process for validation with the users and iterate it along?
2 - What do you mean by complex systems? An Ecommerce can be one of those examples?
A complex system integration could be in mind something that requires "offline" knowledge or data that is not easily accessible by any AI agent or the data is for whatever reason not processable by it.
Security measures in big enterprises are also oftentimes going completely against what AI needs (complete access), there's a million things that an AI can't solve regardless of it's capabilities simply by not having access (or lacking offline context).
We absolute will gain time and you *should* use AI, but it doesn't absolve you from mastering the other disciplines, the reality is that your bottleneck will always be somewhere.
Absolutely agree, Leah. I was part of a startup that launched a product prematurely. We thought we could make improvements on the fly but instead, customer trust took a hit. It's critical to ensure readiness before shipping.
Thank you for writing this. I actually disagree with a lot of the "PRDs are dead" commentary we're seeing online; the thinking is precisely along the lines of your post (just ship it, don't think about it!).
I wrote this post with Ravi, which looks at things in the other extreme: seeing specs as the source code: https://blog.ravi-mehta.com/p/specs-are-the-new-source-code
Would love your thoughts :)
I've said it today somewhere on a different LinkedIn Post.
Prototyping is not the same as building a solution. Prototyping got sped up a LOT, building received a little boost as well.
Whether you draw a prototype, write it out or vibe code it, is all the same in the end, it's to convey meaning about what you envision.
Love this breakdown, Leah - especially the reminder that velocity without validation is just noise. AI might speed up the 'how,' but it still can’t replace the 'why' behind great product decisions.
I understand the article and agree with it. And it can be summed up when you say "Building a tech and software product that is commercially viable will always be hard".
but I have two questions:
1 - If we use AI along the process of development (at least MVP development) wouldn't we be gaining time in the process for validation with the users and iterate it along?
2 - What do you mean by complex systems? An Ecommerce can be one of those examples?
A complex system integration could be in mind something that requires "offline" knowledge or data that is not easily accessible by any AI agent or the data is for whatever reason not processable by it.
Security measures in big enterprises are also oftentimes going completely against what AI needs (complete access), there's a million things that an AI can't solve regardless of it's capabilities simply by not having access (or lacking offline context).
We absolute will gain time and you *should* use AI, but it doesn't absolve you from mastering the other disciplines, the reality is that your bottleneck will always be somewhere.
agree!
Whoa, proprietary data's just a myth now? That's wild!
Absolutely agree, Leah. I was part of a startup that launched a product prematurely. We thought we could make improvements on the fly but instead, customer trust took a hit. It's critical to ensure readiness before shipping.
Totally get you, Jiri! It's all about shifting folks' habits, right?