Building and using autonomous AI agents for complex multi-step tasks.
5 tips in this topic
Define your tools as JSON schemas, then let the model decide when to call them. Start simple: one tool for search, one for calculation. The model returns a function call instead of text, you execute it, feed results back. Loop until done.
ReAct combines Reasoning and Acting. The agent thinks out loud (Reason), takes an action (Act), observes the result, then repeats. Format: "Thought: I need to... Action: search(...) Observation: [results] Thought: Now I know..."
Prompt injection is when user input overrides your system instructions. Prevent it by: separating user input with clear delimiters, validating inputs, using the system message for instructions (not user message), and never trusting user input to be benign.
Layer defenses: ask the model to cite sources, implement fact-checking against known databases, flag low-confidence responses for human review, and set clear expectations with users that AI can make mistakes. Never fully automate high-stakes decisions.
Put the most important instructions at the start AND end of the system prompt (primacy and recency effects). Use clear formatting like numbered lists. Repeat critical constraints. Test with adversarial inputs to see if the model breaks character.