The biggest challenge in many projects is not a lack of technological capability. It is the uncertainty about whether the solution being built actually solves a problem that matters to the user or the business. 

Organizations can spend months working on requirements, analyses, mockups, and roadmaps before a user ever sees a working product. AI makes it possible to complete part of this work much faster. 

Startups have long used prototyping, user testing, and rapid experiments. Their goal is not to create a perfect product at the first stage. The goal is to gain knowledge as quickly as possible and at a controlled cost. 

The episode includes a statement that captures this philosophy well: 

“Ideas are cheap.” 

An idea does not have much value simply because it is innovative. Value appears when it can be tested against a real need and when users show that they want to use it. 

“We are not creating a huge list of requirements. We are creating something clickable, something that can be given to a user to validate the hypothesis.” 

This is an important change in how discovery is conducted. Instead of spending a long time discussing only what the solution should look like, teams can prepare a working version faster and test the audience’s response. 

If the hypothesis is not confirmed, the project can be stopped at an early stage. If the results are promising, only then does it make sense to commit greater resources to design and development. 

For the management board, this primarily means the ability to reduce the cost of poor investment decisions. 

In many organizations, new products, services, or internal tools begin with planning. Roadmaps, budgets, schedules, and documentation are created first. 

Only later does the key question appear: does the user actually need this? 

Vibe coding fits well with the mindset known from Lean Startup. Instead of immediately building a complete solution, an organization can start with an experiment that helps verify the most important assumptions. 

The podcast includes the example of a student who wanted to create an app for renting clothes. The idea seemed attractive, but it had not been validated with potential users in advance. Instead of starting development right away, the decision was made to first test interest in the service. It turned out to be practically nonexistent. 

As the expert sums it up: 

This is a good example showing that in innovation, the winner is not always the organization that builds the product the fastest. Often, the greater advantage belongs to the organization that learns faster and can stop a misguided idea before it consumes significant resources. 

The most expensive project is not necessarily the one with the highest development cost. It may be the one that consumed people’s time and budget for months, only to turn out after implementation to be a solution nobody needed.