I would agree if the only way to achieve (digital product) success were to implement as many versions of software as possible. That's not true.
The whole Lean Startup was about figuring out how to validate ideas without actually developing them. And it is as relevant as ever, even with AI (maybe, especially with AI).
In fact, it's enough to look at the appalling rate of product success. We commonly agree that 90% of startups fail. The majority of that cohort have built things that shouldn't have been built at all in the first place. That's utter waste.
If only, instead of focusing on building more, they stopped and reevaluated whether they were building the right thing in the first place. Yet, most startups are completely immersed in the "development as a bottleneck" principle. And I tell that part from our own experience of 20+ years of helping such companies to build their early-stage products. The biggest challenge? Convince them to build less, validate, learn, and only then go back to further development.
When it comes to existing products, it gets even more complex. The quote from Leah Tharin explicitly mentions waiting weeks/months of wait till they were able to get statistically significant data. What follows is that within that part of experimentation, they were blocked.
Another angle to take a look at it is the fundamental difference in innovation between Edison/Dyson and Tesla.
The first duo was known for "I have not failed. I found 10,000 ways that don't work." They were flailing around with ideas till something eventually clicked.
Tesla, in contrast, would be at the Einstein's end of the spectrum with "If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and 5 minutes thinking about [or in Tesla's case, making] solutions."
While most of the product companies would be somewhere in between, I'd argue that development is a bottleneck only if we are very close to Edison/Dyson's approach.
I heard that before. No, Lean Startup is not about working around the cost of software development.
It is about designing good experiments, validating, and learning, so that when we're down to development, we build something that's way more likely to succeed.
The fact that we were advised to build non-technical experiments is but a small part. And with the current AI capabilities, we actually have a new power tool for prototyping that falls neatly into the whole puzzle.
Distinction without a difference. Your SWE costs blow up because development velocity is low and labor is a fixed cost. You reduce costs by increasing velocity, which in this case is achieved by aiming your development better.
Move faster and move better (to move faster) are the same thing. You reduce costs by going faster, and with lean you go faster by avoiding time wasters.
The whole Lean Startup was about figuring out how to validate ideas without actually developing them. And it is as relevant as ever, even with AI (maybe, especially with AI).
In fact, it's enough to look at the appalling rate of product success. We commonly agree that 90% of startups fail. The majority of that cohort have built things that shouldn't have been built at all in the first place. That's utter waste.
If only, instead of focusing on building more, they stopped and reevaluated whether they were building the right thing in the first place. Yet, most startups are completely immersed in the "development as a bottleneck" principle. And I tell that part from our own experience of 20+ years of helping such companies to build their early-stage products. The biggest challenge? Convince them to build less, validate, learn, and only then go back to further development.
When it comes to existing products, it gets even more complex. The quote from Leah Tharin explicitly mentions waiting weeks/months of wait till they were able to get statistically significant data. What follows is that within that part of experimentation, they were blocked.
Another angle to take a look at it is the fundamental difference in innovation between Edison/Dyson and Tesla.
The first duo was known for "I have not failed. I found 10,000 ways that don't work." They were flailing around with ideas till something eventually clicked.
Tesla, in contrast, would be at the Einstein's end of the spectrum with "If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and 5 minutes thinking about [or in Tesla's case, making] solutions."
While most of the product companies would be somewhere in between, I'd argue that development is a bottleneck only if we are very close to Edison/Dyson's approach.