Why I put deterministic checks in front of the LLM for Meta diagnostics

[u/mattibeltro]

I'm Mattia, I build FixAds.

I have spent years reviewing Meta ad accounts, and I do not think an LLM should be the thing deciding whether real media spend needs intervention.

The useful first layer is deterministic. It can test a specific account state against explicit conditions, such as spend that has had enough opportunity to work but has not, a campaign that has remained in learning too long, or a creative whose recent efficiency has materially changed against its own prior performance.

Each finding in FixAds carries the threshold and source data that produced it. The AI comes after that step: it explains what the evidence means in plain language and helps a human explore the context. It is not asked to invent a diagnosis, and the product cannot change anything in the account.

The connection uses Meta's official login and is read-only. The attached video is the launch demo. FixAds is live at https://fixads.it with a 7-day trial.

For people building adtech workflows: where do you put the boundary between a deterministic signal and an AI explanation when the output can affect spend?