For businesses building software with AI
The AI bill you can see.The rework you can’t.
Every feature that comes back half finished costs you twice: your team’s time, and another round of AI spend. DevFactory checks the work before anyone calls it done.
Every piece of work, what has been checked, and what is waiting on a person.
The short version
What’s DevFactory?
What goes wrong when AI writes most of your software, and what DevFactory does about it.
You have two ways to know how the work is going.
The invoice
Exact, and completely silent on whether the work is any good.
Your team telling you
Says a great deal. There is no way for you to check it.
Spend went up. Speed went up. The way you check the result stayed where it was.
Rework is the expensive part, and it never appears as a line item.
Called done, comes back
A feature ships. Two weeks later the bug report arrives and the same work happens again. You already paid for it once.
A long session down the wrong road
An agent can build for hours on a decision it got wrong in the first ten minutes. Those hours cost the same as the useful ones.
The fix that breaks its neighbour
Nobody checked the thing next to it. Now there are two problems instead of one, and a team a week behind.
None of it shows up on your AI invoice. It shows up in your timeline.
Nine checks, every time, before anything is called done.
Nine questions, asked on every piece of work, whether a person wrote it or an agent did.
Does it have tests?
Tests written
Do the tests pass?
Tested
Has someone reviewed the code?
Code reviewed
Is this feature built the same way as the rest of the project?
Architecture validated
Does it show a clear error when it breaks?
Error handling done
Is the data protected?
Security reviewed
Does it look right on screen?
Screenshot verified
Can we catch it if it breaks again?
QA test cases created
Is it written down for the next person?
Internal docs updated
One failed check stops the work. Eight out of nine is not a pass.
Questions you could not answer last month.
Nobody builds this report for you at month end. The record writes itself while the work happens, because the record is how the work moves. One screen, and you do not need to read any code.
- Is this piece of work actually finished?
- What was checked before it went live?
- Who approved it, and when?
- What is stuck right now, and on what?
The AI does the work. It never signs off on the work.
An agent saying a feature is finished is making a claim. It can be wrong about that, and it sounds exactly as confident either way.
Would you rather have an agent’s word that the work is done, or the evidence, captured before it reaches your customers?
So who is accountable? The same person as before. The difference is that now they can see what they are signing.
Your agent
“Perfect! Everything works now.”
Your agent
“You’re absolutely right, that one was on me. Fixed.”
You
“Show the person’s name, not the ID.”
Forward this part to your engineering lead
Worktree isolation, per-project gate profiles, database-level enforcement, the append-only evidence ledger, and why promotion only ever ships the exact commit that was verified.
DevFactory is in private beta.
We run it on our own builds before we run it on anyone else’s. If you are paying for AI tools and cannot tell what you are getting back, tell us what that looks like from where you sit.
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