L170 · Under the hood · 2 min
Guardrails on the way out
Output guardrails check the model's answer before you see it, catching leaks, unsafe advice and claims the app cannot back up.
01 · The idea
Even with careful instructions, a model can say something it should not: reveal hidden instructions, repeat private data from a document, give medical dosages, or promise a refund the company never offered.
An output guardrail reads the draft answer first. It might scan for personal data, check the tone, compare claims against the sources the app retrieved, or use a second model as a reviewer. Some checks are strict rules, such as never showing an account number in full.
If the answer fails, the app can rewrite it, swap in a safe fallback like "I can't help with that here, a staff member will contact you", add a warning, or route the case to a person.
Output checks matter most where answers have consequences, like health, money and legal topics. They add a little delay, so teams put the heaviest checks on the riskiest topics and lighter ones elsewhere.
02 · Think of it like this
It is like an editor reading a reporter's story before it goes to print, checking names, facts and anything that could get the paper sued.
03 · Do it now
04 · Quick check
Words in this lesson
See also
L185Under the hood · 3 min
When AI products fail in public
Public AI failures usually follow a few patterns, like invented facts, promises nobody approved and bots tricked into embarrassing replies, and each has a known fix.
L172Under the hood · 2 min
The control room: watching an AI app after launch
Once an AI feature is live, the team needs a control room that shows answers, costs, speed and complaints, so problems are found before they spread.
L166Under the hood · 2 min
When AI teams fail
Teams of agents fail in very human ways: vague briefs, lost messages, duplicated work and nobody checking the final result.
L182Under the hood · 2 min
Designing for an AI that is sometimes wrong
Good AI products assume the model will make mistakes and make those mistakes easy to see, fix and recover from.