I’ve been using GitHub Copilot more and more in my daily work with AI, and I’m starting to feel that choosing the right model is becoming a skill in itself.
For example, I tend to use different models depending on the task:
More advanced models (like Opus-level reasoning) for planning, architecture, and breaking down complex problems
Faster / lighter models (like Sonnet, Codex-style models) for execution, coding, and iteration
This approach seems to significantly improve both speed and output quality. I also notice that when prompts are structured well, tasks can be completed surprisingly fast, sometimes much faster than expected.
What I’m curious about:
How do you choose which AI model to use for a given task?
Do you deliberately split work between “thinking” models and “execution” models?
Have you found specific prompts, workflows, or tricks that consistently speed things up?
Are there patterns you follow to get better or faster results?
Curious to hear how others are approaching this.