Trust in AI coding: why the go-live click is no longer enough
AI makes website development cheaper and faster. Good. For site owners, one uncomfortable question remains: what broke after launch without anyone noticing?
This article is based on a note from my LinkedIn feed. The point: AI coding is not going away. Trust now comes less from promises and more from independent checks. Original post on LinkedIn.
Trust was scarce before AI
How do I trust my agency? How do I trust my development team? These questions existed long before AI. They just sounded simpler before: “Please do not introduce bugs.” Of course, that was never a process.
In practice, changes already pass through many loops before deployment. Code review. Internal QA. Automated tests. UAT. And then the familiar moment still arrives: go live, open the browser, click through it once yourself.
Not because all the other steps are worthless. Because trust on the web is practical. In the end, it does not matter whether a ticket is closed. It matters whether the site works for real users.
And now AI enters the room
With AI, everything gets faster. Sometimes stranger, too. A feature that used to take half a sprint is suddenly there in the afternoon. Refactors get cheaper. Variants get tried, thrown away, and rebuilt.
You have probably seen the same posts I have: 1.7x more bugs, more logic errors, 7.6x more performance issues. Whether every number transfers perfectly is almost beside the point. The pattern matches what many teams are seeing.
Still, there is no realistic path back. Development costs are falling. Delivery times are shrinking. Customers expect more output. Agencies and product teams have to work with AI.
The question is: what else got touched?
I see this inside Mira, too. A change to Feature A suddenly pulls older areas along with it. Sometimes that is good. The UI becomes more consistent, components fit together better, and the product feels less assembled from loose parts.
But then comes the uncertainty: were those all the effects? Did it only touch the area I happened to see? Or did the change also affect a form, a checkout step, or a mobile view along the way?
For site owners, this is exactly the point. Higher speed, higher risk of mistakes, but still a need to stay in control. Not because you distrust the agency. More like a seat belt in a faster car.
The old loops do not disappear
Code reviews, automated tests, and UAT remain important. More important than before, really. They just have to keep up with a development world where more changes happen in less time.
The manual go-live click has become too small for that job. It comes late, depends on individuals, and usually checks only what someone happens to remember. AI coding expands exactly the area nobody thought about.
Website QA therefore needs more distance from the development process. Not only: “The build is green.” But: “Can a user still complete the most important journey?”
What I want to see as a site owner
If your website is maintained by an agency or an AI-assisted team, you do not need anti-AI rules. You need evidence that does not only come from the development process itself.
- Which user journeys are considered critical and checked after changes?
- Which older areas could be affected by a new change?
- Is there an independent browser check, not just a green build?
- Do I get traceable results instead of “should be fine”?
That is why I am building Mira
Welcome back to the series: AI is wild, so we are building our own QA and testing tool. That tool is Mira, my own SaaS for website QA.
Mira is meant to give site owners confidence at exactly this point. Not as a replacement for good developers or solid agency processes. Mira learns the website, checks important journeys, watches changes, and reports problems.
Trust in AI-assisted development does not come from slowing down again. It comes from a second look that is not stuck in the same tunnel.
Frequently asked questions
- Should agencies and development teams stop using AI coding?
- No. AI coding is now part of development. The better question is how teams check quality when changes are produced faster.
- Why are code reviews and automated tests no longer enough?
- They remain important, but they often check from the code's point of view. Site owners also need checks from the user's point of view: does the page load, does the journey work, and is anything important broken?
- How does Mira help teams trust AI-assisted website development?
- Mira checks critical website journeys in a separate QA loop and reports issues after changes. Fast development gets an independent second look.