How Engineers Use Iterative Meta Prompting
- Patrick Law
- Jul 24
- 2 min read
Ever feel like your ChatGPT prompts are close... but not quite there? You’re not alone. Most people stop when they get a bad result. At Singularity, that’s exactly where we start. Our team of engineers uses a technique called Iterative Meta Prompting—a feedback-driven loop that continuously improves the quality of both the prompt and the output. This isn’t just using AI—it’s engineering it.
Key Strengths or Features:
It’s a feedback loop, not a guessing game. Each prompt is reviewed, improved, and re-run in the same chat—no fresh threads, no retyping from scratch.
ChatGPT helps you improve the prompt. We don’t just rewrite blindly. We ask ChatGPT how to rewrite the prompt for clarity, structure, or precision.
You get better outputs and learn what doesn’t work. Even failed prompts teach us something. We track what made results worse and avoid those patterns in the next round.
You sharpen instructions over time. Each cycle adds clarity, reduces ambiguity, and pushes ChatGPT closer to the exact result we need—especially in engineering workflows where precision is non-negotiable.
Limitations or Risks:
Improving the prompt doesn’t always improve the output. Sometimes, even a “better” prompt leads to worse results. But that’s part of the process—we now know what not to do.
It takes a few rounds. This isn’t one-and-done. Engineers might go through 3–5 prompt cycles before landing the best output.
Requires patience and review. Engineers must actively evaluate results and feedback, not just automate the loop without judgment.
How It Fits Into Singularity’s Workflow:
At Singularity, this approach is embedded in our AI-assisted engineering processes. Whether we’re drafting calculation reports, generating technical summaries, or prototyping workflows, we use one continuous thread. No new chats. No “starting over.” We treat prompts like code: debug, refactor, re-run. That’s what makes our workflows faster, more accurate, and reusable.
Conclusion / Call to Action:
Iterative Meta Prompting isn’t just a trick—it’s a methodology. If you want sharper results, clearer outputs, and faster workflows, it starts by making your prompts smarter.
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