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๐Ÿ”
AI EngineeringC#

X2 Problem Solve

by teklabsdigital

Diagnoses unknown runtime product misbehavior using structured observation, hypothesis testing, and minimal instrumentation to find root cause efficiently.

12 stars1 forksAdded 2026/07/16
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README

X2 Problem Solve

Diagnosis, priced in human turns. Every "try this and tell me what you see" is a round trip the human pays for, and the metric counts it. The kernel prevents classes of defects; it does not diagnose novel ones, so when one appears, spend the fewest observation turns that honestly find the cause.

The pipeline

  1. Observe. Get the observation and visual evidence first (screenshot, recording, exact repro). Find the last working state in git; the diff between working and broken is the search space.
  2. Hypothesize. Form two to four falsifiable hypotheses, each with the data signature it predicts. Write the expected values down before instrumenting; a hypothesis without a predicted signature is a guess.
  3. Validate with one pass. Design ONE instrumentation deployment that discriminates between all hypotheses simultaneously: five to ten log points, state transitions only, a filterable prefix, no per-render logging. Deploy instrumentation only, no other changes. One round trip. If the data says "working correctly" and the human says otherwise, the hypotheses are wrong, not the human's eyes; return to step 2.
  4. Confirm. State the root cause in one sentence tied to measured data. If it does not fit in one sentence, it is not understood yet.
  5. Fix. A failing regression test first where the defect is testable; then the fix through the normal implement loop; then remove every log point added in step 3. If the root cause is a specification defect, that is green-but-wrong: the fix goes in the decision file, never patched into source.

Anti-patterns

  • No code changes before a confirmed cause. No layered speculative fixes; if you stack three changes, you learn nothing. No trying the opposite of a failed fix without new data.

Human-turn contract

  • No gate. The observation round trips are the turns; log each one to the ledger like any other, and design the instrumentation so there is usually exactly one.

What this skill must NOT produce

  • No fixes without a measured root cause, no instrumentation left behind, no commits without direction.