How to tell a real AI-native firm from one that added the words
Almost every software firm now describes itself as AI-native, which has made the term close to meaningless as a buying signal. This page does not name competitors and does not claim we are better than them. It sets out the questions that distinguish a firm that genuinely reorganised its practice from one that bought editor licences and updated its website, so you can ask them of anyone, including us.
Facts about another AI-native agency last checked 2026-08-21
- Using AI to write code is now the industry norm, not a differentiator.
- The real question is what replaced code review as the primary control.
- Ask what runs automatically on every change, and what happens when it fails.
- A firm that cannot show you a check failing does not have a working suite.
- Ask these of us too. The questions are only useful if they are applied evenly.
Where another AI-native agency is the right answer
Written first, and deliberately. If we could not fill this section honestly, the page would not be worth publishing.
What another AI-native agency is good at
- Many firms describing themselves this way have genuinely strong engineering practice
- Established firms adopting AI bring process maturity a newer firm has not built yet
- A larger firm can offer specialisms and scale that a small team cannot
- Some have measured their own delivery before and after, which is more than most
Choose them over us when
- They can answer the seven questions below better than we can
- They have a track record in your specific domain and we do not
- They are large enough to run a programme that would be too large for a small team
- Their references are confirmed and, being new, we have none to offer
Side by side
Every cell about another AI-native agency is labelled with where it came from. Nothing here is inferred, and a blank is left blank.
| Reveneau | Another AI-native agency | |
|---|---|---|
| AI writes the implementation | AI writes the implementation, on every engagement | Very likely, and increasingly universalTheir claim |
| What must pass before a merge | An eval suite written from the specification, blocking the merge | Ask. This is the question that separates firmsNot established |
| Can they show a check failing | Yes, on request | Ask them to demonstrate itNot established |
| Method published in public | Yes, in the guides on this site | VariesNot established |
| Track record | None. Reveneau is new | Often years of itTheir claim |
A term that everyone claims stops giving any information. "AI-native" is most of the way there, so here is a way to test it that does not depend on anyone's marketing.
Why the claim stopped meaning anything
Using a model to write code is now ordinary. Industry surveys put the share of developers using or planning to use AI tools in the mid-eighties percent. A firm advertising that it uses AI is describing its industry.
So the differentiator cannot be that AI writes the code. It has to be what the firm changed in response, and specifically what replaced human code review as the control that catches mistakes, given that generated code arrives faster than anyone can read it.
The seven questions
1. What runs automatically on every change, and does it block a merge? A report nobody reads is not a control. If the answer is "our engineers review everything", ask how many lines a reviewer sees per day and whether that number changed when generation started.
2. Can you show me a check failing? Ask them to break a protected behaviour deliberately and show the build turning red. Suites full of assertions that mock away the real path, or compare a value to itself, pass forever and prove nothing. This is the single most revealing question on the list and it takes five minutes.
3. Where do your checks come from? Derived from the specification is a good answer. Derived from the code is a weaker one, because those checks encode whatever the code already does, including its bugs, and they break on every refactor.
4. What happened the last time something reached a customer that should not have? You are listening for a change to the pipeline, not just to the code. A team that fixes the bug meets it again; a team that adds the check that would have caught it keeps improving.
5. Who writes the specification, and how precise is it? When a machine implements what you wrote, vague sentences become confident wrong code within minutes. Firms that have genuinely reorganised talk about specification a lot, because it became the expensive part.
6. What do I get at handover? Code alone is the wrong answer. The specification, the checks, and the reasoning are what make it maintainable. This is covered in can your team maintain AI-written software.
7. What security checks run, and on which paths? Veracode's spring 2026 testing found roughly 55 percent of AI code generations were secure with no security guidance, unchanged for two years while syntax correctness rose past 95 percent. A firm releasing generated code without automated security checks that block a merge has not read its own industry's evidence. The detail is in is AI-generated code secure.
Apply these to us
These questions are only worth anything if they are asked evenly, so ask them of us. Where our answer is weaker, it is weaker: Reveneau is new and has no track record, so question four is answered from method rather than from a decade of incidents, and a firm with ten years of postmortems can answer it better.
We published this page knowing it helps you question us closely. That is the point. A buyer who cannot tell the difference between suppliers eventually picks on price, and that is a worse market for everyone doing this properly.
Where we fit
Reveneau suits this when
- You want the verification method stated publicly and in detail before you buy
- The build has a correctness standard that justifies an eval suite
- You would rather judge a supplier on method than on a client list
Common questions
What does AI-native actually mean?
Is using AI to write code a differentiator in 2026?
What is the single best question to ask an AI development firm?
Should automated checks come from the specification or the code?
How do I judge an AI-native firm with no track record?
Why would Reveneau publish questions that could be used against it?
How is Reveneau different from another firm that also calls itself AI-native?
What happens when a check fails at an AI-native firm?
Sources
Marked independent where the source has nothing to gain or lose from the answer. Anything from the other party is their own account and is labelled as such.