If a tool returns a massive 50MB JSON file, you can't feed that to the LLM. How do you "summarize" or "filter" tool observations for the agent?

A user asks "What were the sales in 2023?" How do you prompt the LLM to separate the semantic search ("sales") from the metadata filter ("year == 2023")?

What is the fundamental difference between a "Chain" (hardcoded steps) and an "Agent" (model-decided steps)? When is a Chain actually better than an Agent?

AI agents often rely on external tools/APIs. How would you design a system that ensures robustness when these dependencies are unreliable or slow?