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Self-Rewriting Meta-Prompt Loop NEW

Problem

Static system prompts become stale or overly brittle as an agent encounters new tasks and edge-cases. Manually editing them is slow and error-prone.

Solution

Let the agent rewrite its own system prompt after each interaction:

  1. Reflect on the latest dialogue or episode.
  2. Draft improvements to the instructions (add heuristics, refine tool advice, retire bad rules).
  3. Validate the draft (internal sanity-check or external gate).
  4. Replace the old system prompt with the revised version; persist in version control.
  5. Use the new prompt on the next episode, closing the self-improvement loop.
# pseudo-code
dialogue = run_episode()
delta = LLM("Reflect on dialogue and propose prompt edits", dialogue)
if passes_guardrails(delta):
    system_prompt += delta
    save(system_prompt)

Trade-offs

Pros: rapid adaptation; no human in the loop for minor tweaks. Cons: risk of drift or jailbreak—needs a strong guardrail step.

References