Anticipate failure modes

For each severe conversation memory failure on the personal tutoring assistant, define stop condition, safe state, owner, and lasting prevention. Rollback only works if prior prompts, indexes, and models remain available. “Send to a human” needs queue capacity and context—not just a button name.

Run one tabletop on the personal tutoring assistant for conversation memory: inject a defect, verify detection, contain, recover, and keep the blameless trace.

After the tabletop, store the injected conversation memory defect for the personal tutoring assistant as a regression fixture. If the same failure later reaches users silently, your detection story was aspirational. Detection without a fixture tends to rot for conversation memory.

Also pin one numeric memory from this conversation memory chapter: If 40 memories are injected every turn but only 3 affect the hint, you spent tokens and risked contradictions—measure useful-memory rate, not memory count. That number is not decoration; it is a template for how claims about conversation memory on the personal tutoring assistant should look in design docs. Scoped specifically to conversation memory / personal tutoring assistant / failure-modes.

People confuse conversation memory with neighboring buzzwords when debugging the personal tutoring assistant. Before changing prompts, ask whether the broken stage was evidence gathering, the conversation memory judgment itself, validation, or the product action. Fixing the wrong stage creates folklore (“we tried conversation memory and it failed”) that blocks the next team on the personal tutoring assistant. Scoped specifically to conversation memory / personal tutoring assistant / failure-modes.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to conversation memory rather than generic AI advice.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to conversation memory rather than generic AI advice.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to conversation memory rather than generic AI advice.