The pipeline that produces fluent nonsense
A pipeline caches tokenized text to avoid re-tokenizing a large corpus. Stage one tokenizes with a tokenizer loaded from a local path and writes integer arrays to Parquet. Stage two loads those arrays and runs them through a model.
After someone upgraded the model checkpoint to a newer release from the same family, outputs became fluent, grammatical, and semantically unrelated to the input. No error is raised. Sequence lengths are unchanged. Token id ranges look normal.
Perplexity computed on the cached ids against the new model is roughly 900.
Diagnose this from the evidence given. Then tell me why nothing in the system raised an error, and what invariant the pipeline should have been asserting all along.
Choose how you want to be interrogated
The same case under two modes is two different exercises. If you are unsure, RCA drill is the one that trains root-cause analysis most directly.
RCA drill
A symptom, and nothing else. Find the cause and prove it.
Trains: Hypothesis generation, ranking by prior, and naming the test that discriminates.
Red team
You propose. It attacks. It is trying to make you wrong.
Trains: Defending a position under pressure, and noticing when you should concede.
Socratic
Questions only. It will never tell you the answer.
Trains: Deriving from first principles instead of retrieving from memory.
Design review
Present an architecture. Justify every trade-off you made.
Trains: Stating what you optimised and what you gave up, on purpose.
Viva
Rapid escalating questions. Ends in a graded verdict.
Trains: Answering under time pressure without hedging.
Integration
Problems that span several domains at once. The hardest mode.
Trains: Reasoning across boundaries, where the cause is in a different system to the symptom.
Before you start: you begin locked. The Mentor will give you nothing — not a nudge, not a category — until you state a specific position and the mechanism you think produces it. Four genuine attempts unlock the resolution. There is no shortcut.