I’ve been experimenting with both prompt engineering techniques (like layered prompting and chain-of-thought) and function calling in the latest GPT-4 Turbo setup. I’m curious how the community is approaching this balance.
Some of my observations:
- Function calling is super clean for structured tasks (like pulling JSON or calling APIs), but…
- Layered prompts seem to perform better when nuance or reasoning is needed — especially with summarization or content workflows.
Are you leaning more into one approach than the other?
Anyone here combining both strategies in production or testing?
Would love to hear how you’re using prompt strategies with GPT-4 or GPT-4 Turbo (especially in real-world use cases).