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

Write a prompt that gives the AI model precise context, role, task, and expected format.

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

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

RAG (Retrieval-Augmented Generation) fetches real docs for the model before answering. Know the difference.

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

Convert a meeting transcript (60+ min) into decisions and action items in 2 minutes.

Turn a 200-page PDF into a Q&A conversation with exact-quote answers.

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

Any question on recent events/prices/releases: check model training date — ignoring = confident wrong answer.

Set "system instructions" once in your account = every chat starts from your context automatically.

Give the model 2-3 complete input-output examples before your ask, instead of explaining the rule verbally.

Ask the model to "think out loud" step by step before the final answer, especially for logic and math problems.