Complex questions need smaller questions first. AI reasons better when problems are split into parts.
Same complex question. One asks for sub-questions first.
AI: It depends on your situation. Buying builds equity but requires a down payment and commitment. Renting offers flexibility but you don't build ownership. Generally, if you plan to stay 5+ years and can afford it, buying might make sense. If you value flexibility or aren't sure about the area, renting could be better...
Generic advice. Doesn't account for your specific situation.
AI: To answer this well, we need to figure out:
1. How long do you plan to stay in this area?
2. What's your current savings and down payment ability?
3. What are property taxes and maintenance costs in your area?
4. How do local rent prices compare to mortgage payments?
5. Do you have stable income to handle ownership costs?
Want me to walk through each one?
Now you see what factors actually matter for your decision.
AI reasons better when questions are broken into smaller parts. Complex questions have hidden assumptions and missing information. Breaking them down reveals what you actually need to know.
When AI identifies sub-questions first, it's forced to think about what information matters before jumping to conclusions. You get advice tailored to your situation instead of generic guidance.
For complex questions, ask AI to identify the smaller questions first. Answer those, then combine them for a better final answer.