Why models state falsehoods fluently, and the failure modes every AI engineer must anticipate.
Skip to solutionKEEP THE
easyAI Engineering
What are hallucinations and what causes them?
303 views
01
Understand the problem
hallucinationgroundingreliability
02
Attempt it yourself
Sketch your approach before reading the solution — that's what interviews test.
Nudge consolestandby
Stuck? Beam a request up — the console returns a conceptual nudge that guides your logic without spoiling the implementation.
03
Study the solution
A hallucination is fluent output that is factually wrong or fabricated — invented citations, APIs that do not exist, confident wrong answers. They happen because the model optimizes plausibility (next-token likelihood), not truth: when the training data or provided context lacks the answer, the most statistically plaus
Solution ready — 2 min read
Classified // press E to declassify
04
Read the code
The abstain-or-cite pattern
const system = [
"Answer ONLY from the provided context.",
"Cite the doc id for every claim, like [doc-3].",
"If the context does not contain the answer, reply exactly:",
'"I could not find this in the provided documents."',
].join("\n");
// downstream: reject answers whose citations do not resolve
const ok = extractCitations(reply).every((id) => contextIds.has(id));05
Join the discussion
Discussion (0)
Sign in to join the discussion.
No responses yet. Be the first to share what you think.
Transmission complete // awaiting log
KEEP THE
STREAK ALIVE.
Dossier 9 of 80 decoded in the AI Engineering track. One more won't hurt.