Get Camino build log · 4 of 10
The truth pipeline
For an app that tells people what the law requires of them, being right can’t be a value on a poster. It has to be a system that refuses to ship the alternative.
- 01
Source at scale
15 hours of expert webinar transcripts, mined by parallel agents. The catalog grows to 60 obligations.
Fast and broad — but not yet trustworthy.
- 02
Ground in primary sources
28 uncited obligations re-verified against the law itself: the BOE, the tax agency, the DGT.
Caught: a penalty the courts had struck down. A form that no longer exists.
- 03
Gate the build
No page may state a number its cited source doesn't carry. The lint fails the deploy.
First run: caught a violation before any user saw it.
My app tells people what the Spanish government requires of them. “Mostly right” isn’t a quality bar here — a wrong fact is someone missing a residency deadline.
So the most important system in Get Camino isn’t a feature. It’s the process that decides what’s true.
Step 1 — Source at scale. Claude mined 15 hours of expert webinar transcripts with parallel agents, growing the catalog to 60 obligations. Fast, broad — and not yet trustworthy.
Step 2 — Ground everything. 28 of those obligations arrived without primary citations. Every single one got re-verified against the actual source: the BOE, the tax agency, the DGT. Not blogs quoting blogs. The law itself.
That pass caught two things no prompt would have: a penalty that a court had struck down (still cited all over the expat internet), and a form that had been abolished. The web remembers rules that no longer exist. An AI trained on the web remembers them too.
Step 3 — Make truth a build gate. The honesty rule — no page may state a number its cited source doesn’t carry — stopped being a value and became a lint that fails the deploy. On its first run it caught a violation before any user ever saw it.
Here’s the lesson I’d offer every leader shipping LLM products: hallucination is not a prompt-engineering problem. It’s a systems-design problem. You don’t ask the model to be honest. You build a pipeline where dishonesty can’t ship.
AI collapsed the cost of drafting 60 obligations. It did nothing to collapse the cost of one of them being wrong.