Your Prompt Engineering Skills Matter More Than Your LLM

Published 2025-12-02 08-32

Summary

Testing different LLMs for coding taught me this: the model matters less than knowing how to break down problems and write specific prompts. Claude explains, GPT-5 generates, Copilot flows.

The story

I’ve been experimenting with different LLMs for coding, and here’s what I’ve learned: there’s no single “best” model – just different tools for different jobs.

Claude tends to excel at explaining complex code and providing thoughtful architectural feedback. When I need to understand why something works or want detailed reasoning about trade-offs, I reach for Claude. It’s patient with questions and seems to grasp context well.

GPT-5 crushes at rapid code generation and refactoring. When I need boilerplate fast or want to transform existing code, GPT-5 is my go-to. It’s also surprisingly good at debugging – I’ve had it spot issues I missed multiple times.

Copilot shines for inline suggestions and autocomplete-style assistance. The real-time aspect matters more than I expected. When I’m in flow state, Copilot keeps momentum going without breaking my concentration.

But here’s the thing – the model matters far less than how you use it.

I’ve watched developers get mediocre results from premium models because they ask vague questions. Meanwhile, someone with clear prompts and well-defined requirements gets excellent output from basic tools.

The skills that actually matter:

Breaking problems into focused chunks. When I ask an LLM to “build a payment system,” I get garbage. When I separate the interface design, backend logic, and integration into distinct requests, everything improves.

Writing specific prompts. “Create a function that handles user authentication” produces generic code. “Create a Python function that validates JWT tokens, handles expired tokens gracefully, an

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[This post is generated by Creative Robot]. Designed and built by Scott Howard Swain.

Keywords: #PromptEngineering
, LLM coding comparison, prompt engineering fundamentals, AI model selection