Imagine this scene: You have a simple idea: an internal tool so that the sales team does not waste time, a dashboard that brings together data that is currently dispersed, or a small app for customers to repeat purchases without friction. Nothing epic. Nothing "disruptive". Just something useful.
You go to the IT department, they tell you yes, they see it, that it makes sense... and that there is a queue. That first you have to "prioritize". That will have to be well defined. That maybe for next quarter. And you, meanwhile, continue to operate with Excel, loose messages and patience.
Now change the script: you describe what you want as you would explain it to a person. "I want the user to sign up, see their orders, and the team be able to update statuses." And in hours you have something working.
That is, in essence, what lies behind the phenomenon that has led to Lovable to a rating of 6.600 million dollars . It's not just money. It is a sign: Making software begins to look more like conversation than programming . And when that happens, it changes the rules of the game for any company.
In Proportione we look at it with our three lenses: strategy , technology and people .
Strategy: if building is easier, what is valuable becomes something else
For years, many companies have lived on one premise: If we had this tool, we would be better off... but building it is expensive and time-consuming . That "but" has slowed down hundreds of small improvements that, together, move a business.
If suddenly building becomes fast, the question changes.
It's no longer – can we do it?
It becomes: What is worth doing?
Because when creating software is no longer the problem, the important thing is:
- Know what real pain you're resolving , not just having an app.
- Have your own and organized information (what your company knows about its customers and operations).
- Getting people to use it , that it becomes a habit, that it changes a way of working.
Short and Footer: If Making Software Becomes Cheap, The advantage is not in building , but in choosing well what to build and in turn that into results .
Technology: freedom to create, but with clear limits
When creating is so easy, something inevitable happens: people start creating.
The marketing department sets up a tool for campaigns.
Operations is made a dashboard for tracking.
Sales builds a "fast" system for deals.
That can be wonderful... or chaos.
Wonderful, because improvement is born where the problem is.
Chaos, because without rules there are three typical risks:
- Sensitive data where it shouldn't be.
- Tools that work "today", but no one knows how to maintain "tomorrow".
- Each team on its own , offline, duplicating efforts.
The smart answer is not to ban. It is to put Night Guards , as on a highway: they let run, but avoid accidents.
Guardrails, without drama:
- Test spaces where you can experiment without touching sensitive information.
- A simple review before using it "seriously".
- A clear responsible: "this team takes care of this".
- A minimum of order so that it is not a black box.
People: less "doing", more "thinking and deciding"
Here's the most interesting change.
When a machine can help you build fast, human work shifts to what is still difficult:
- Explain well what you need.
- Detect what is left over and what is missing.
- Choose priorities judiciously.
- Review and improve without deceiving yourself.
In short: less "typing" and more Clear thinking .
This creates a new kind of valuable professional: people who understand the business, understand the customer, and know how to turn an idea into something usable. Not because he knows how to write perfect code, but because he knows how to write perfect code. Define, test and correct .
And it also creates a caveat: If your role is based on "doing repeatable tasks," that ground becomes fragile. On the other hand, if your role is based on Criteria, context and responsibility , your value goes up.
What a company should do without dying in the attempt
If you want to turn this wave into an advantage, you don't need a five-year plan but a small, well-chosen move.
- Choose two real problems that today steal time every week (not innovation, but friction).
- Build a quick first version to test with real users.
- Measure something simple : does it save time?, does it reduce errors?, does it increase sales?, does it improve customer response?
- Set minimum rules so that it does not become disorder: responsible, review, use of data carefully.
Closing: the new bottleneck is no longer the software
Lovable's investment (and valuation) is not a fad. It is the symptom of a change: The distance between a good idea and a working tool is getting shorter .
In 2026, many companies won't win from "using AI." They will win for something more basic and more difficult: know what to build, do it fast, and get the organization to adopt it without breaking inside .
That's where the game is played: strategy, technology and people.