How do you implement "Long-Term Memory" for an agent so it remembers a user's preference from a conversation that happened three weeks ago?

You can't use a standard debugger on an LLM's "thought process." How do you build observability into an agentic loop to find where a logic error occurred?

If your user queries are short "slang" phrases but your documents are formal legal texts, how do you ensure the embedding model can bridge that semantic gap?

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