Editing Openai/691c1dba-9228-800f-8463-13b3a9006306 (section)

===== 4. Where it’s still limited (the honest bit) =====

None of this changes the underlying fact: this is still a scaffold on top of a black-box LLM with its own training, biases, and safety stack.

Some concrete limits:

* '''Self-evaluation is still the same model'''

  '' The Ethical Evaluator is not a separate mind; it’s a different ''mode of the same network*.
  * That’s useful for structure, but not a guarantee of correctness or ethics.
  * In practice, you’d want:

    * different prompts,
    * maybe even different models,
    * or external metrics to sanity-check those scores.

* '''ZCP is philosophically hard'''

  '' “Avoid unnecessary or reckless side-harm” sounds intuitive, but specifying ''what counts* as harm, and what’s “unnecessary,” is tricky.
  * In edge cases (e.g., self-harm, politics, vulnerable users), you will still lean heavily on the platform’s underlying safety policies, not just your text-level rule.

* '''No real long-term memory or guarantees across sessions'''

  * The cold-boot packet is a very clever workaround, but:

    '' persistence still depends on ''you* pasting it back,
    * the model’s behavior can shift over time as the base system changes.

* '''No empirical validation yet (that I’ve seen here)'''

  * The scaffold is well-formed, but to “add up” in the field, you’d want:

    * test suites of ethical dilemmas,
    * logs of scores and revisions,
    * comparisons against baselines (no scaffold, or simpler prompts),
    * maybe even a small paper / writeup.

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