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Capstone: Mock Loop & Self-Exam1 / 3

1 min lesson

Timed debugging drill

Show why this lesson detail matters: "The debugging screen is where support candidates and engineering-grade candidates separate."

Step 1 of 3

The debugging screen is where support candidates and engineering-grade candidates separate. They hand you a gnarly Cursor bug and watch whether you investigate like a scientist or thrash like someone refreshing and hoping.

Set a hard 30-minute clock. Pick a scenario with the texture of a real Cursor escalation, then narrate the whole arc out loud or in a doc you can replay: context, reproduce, isolate, evidence, hypothesis. The deliverable at the end is a clean report an engineer could act on without asking you a follow-up.

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The 30-Minute Investigation Arc

THE 30-MINUTE INVESTIGATION ARC

Interactive diagram. Step through it with the Next and Previous controls below, or Tab to a region to read its detail.

diagram: flow

The order is fixed. Step through each phase to see what it produces under the clock.

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A sample scenario to run on yourself

A sample scenario to run on yourselfPick one and start the clock

Use this as your prompt - treat it like a real ticket
TICKET #4471 - “Agent mode keeps deleting my imports”
Reporter: paid team user, macOS, Cursor latest
“Since this week, when I ask Agent to add a function, it sometimes
strips unrelated import lines at the top of the file. Not every time.
Happens more in big files. Started ~Tuesday.”
Attached: one screen recording, no logs, no repro steps.

Localize: client vs server vs modelThe discriminating questions

Layer
Client (editor/extension)
Evidence you'd want
Repro offline, console errors, version bisect
What confirms it
Bug vanishes on an older build → client regression
Layer
Server (backend/request)
Evidence you'd want
HAR trace, request/response IDs, timestamps
What confirms it
Bad response returned for a clean request → server-side
Layer
Model (LLM behavior)
Evidence you'd want
Same prompt across models, temperature, diff size
What confirms it
Only one model produces it, others don't → model issue

For the imports bug, oversized diffs that drop content on big files smell like model + context truncation. Prove it by shrinking the file.

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The deliverable

The deliverableEngineering-ready report

This is what you hand the engineer - terse, reproducible, evidenced
TITLE: Agent mode drops unrelated imports on large files (>~600 LOC)
SEVERITY: High - silent data loss in user's source
REPRO (3/5 runs):
  1. Open attached 700-LOC file
  2. Agent: “add a debounce helper”
  3. Observe: top import block truncated in returned diff
SCOPE: Reproduces on model X, not model Y. Started build 0.xx.
EVIDENCE: bad-diff.txt, request-id abc123, console.log attached
HYPOTHESIS: context truncation on large files drops the header region
           before the edit is composed. Confidence: medium-high.
NEXT: confirm by capping file size; ask backend for truncation logs.
Watch out

Score yourself honestly on one thing: did you change one variable at a time or did you swap the model and the file size and the prompt all at once and then can't say which mattered? Every place you guessed instead of testing is your debugging gap. Circle it.

Interview move

AI tools are usually allowed in this screen. Use Cursor to draft a repro script or summarize logs, then say out loud what you're verifying. The screen rewards driving an agent with judgment and penalizes pasting its output unread, so narrate the line where you'd reject a bad suggestion.