Separate prompt parts with XML tags (instructions, examples, document) so the model handles each precisely.

Don't default to the biggest model. Choose by: task depth, cost, privacy, speed.

Show the model 2-5 examples of the desired output style so it mirrors the pattern with high precision.

Ask the model to decompose the problem and show its reasoning before answering, raising accuracy on complex tasks.

The model does not know what happened after its training cutoff. Know each model's cutoff.

Use an LLM to draft an email in 30 seconds, then edit by hand for personal tone.

When an LLM helps you with content you publish or send, disclose it clearly.

For critical information, ask two different models (Claude and GPT, say) the same question independently, and compare before relying on either.