So much energy in my life was spent making compromises between quality and speed, or pushing technical debt priorities. Constantly growing backlog, and guilt for the choices I had to do. What if we could fix the bug problem with AI? I mean, completely.
Image the program always follows the designed spec, and stays that way over time. And the only bugs left are human judgment issues, where you had some hypothesis and it was wrong.
You probably thinking, Leo, it is just not possible, stop dreaming, and talking about some theoretical stuff. Maybe it just hype farming. But trust me, it is not, and pretty much real, and it happening right when we talk.
If you think about an automobile or MRT, you wouldn’t expect some stupid bug that will kill a person there. It just works. So why can they do it and we can’t?
This was the question I asked myself while looking for the answer to this problem.
And the answer is essentially that they have a completely different view on quality and on the price of a mistake — human life. All the issues need to be found before they even reach development, and during development before they reach production.
And it’s totally possible. It’s just very slow, expensive, and requires a lot of processes.
All the techniques we invented in consumer engineering were about how to cut corners so that you can deliver faster. Everything is about speed and money. Which is fair, but it doesn’t have to be like that. There are also other options.
You must say: We are not NASA. We don’t need the same level of processes.
But why not?
If it’s because of slow, complex, pricey processes, it’s solvable with AI.
These days it can manage your requirements management system. It can do the hazard analysis. It can do 100% MC/DC testing for you.
Why cut corners? Just throw the tokens at this problem.
In my view, this is exactly the problem that deserves to be solved by throwing more tokens at it. It will make so many people happier, and it will make all our lives better.
The whole point with all of this AI evolution is that you can do an inhuman amount of work.
Just giving people Claude Code or Codex, etc., is still doing human work, just faster and multiplied by 10x, maybe, or something similar.
We can do so much more with this technology.
Back to the roots: no longer cutting corners, no longer picking whether I’m shipping the feature or fixing the bug, and then regretting it while fighting regressions I introduced or some security issues.
And it will actually solve another big issue.
We can’t scale autonomous AI software factories because we don’t trust their output.
But trust is something that should be earned.
No one trusts the engineer in a regulated software engineering company. No one trusts anyone. You have to earn the trust.
So if we build our workflows around trust and evidence, we can scale agentic workflows as well.
Let’s start thinking differently.
We are at the point of reshaping what software engineering is supposed to be, lets not screw it up.
This is exactly what I’m building at Proof. I’m on a mission to bring the engineering standards of regulated industries to everyday software - without the cost and process that made them impractical before. If any of this resonates with you, just reach out. I love talk about software quality, engineering craft, and what AI changes about it.
Interesting take on the topic. It was a good read.