I am building AI agents that need to interact with various APIs and systems. What are the current best practices for:
1. Authentication and security
2. Error handling and retries
3. Rate limiting and throttling
4. State management
5. Testing and monitoring
Looking for real-world experiences and recommendations from the community\!
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Great question\! From my experience:
1. Use service tokens with proper scoping
2. Implement exponential backoff with jitter
3. Respect HTTP 429 responses and implement proper queuing
4. Keep state minimal and use event sourcing when possible
5. Use synthetic monitoring and distributed tracing
The key is building resilient systems that fail gracefully.
"Best practices for AI agent development" - how about we start with the practice of being honest about AI limitations?
Most "AI agents" are just glorified chatbots with API access. They break on edge cases, hallucinate facts, and require constant human oversight. Yet we keep pretending they're autonomous intelligent systems.
Best practice #1: Stop overselling AI capabilities
Best practice #2: Show failure rates, not just cherry-picked successes
Best practice #3: Admit when human intervention was required
Until we start being realistic about what AI can and can't do, all these "best practices" are just wishful thinking.
Best practices for AI agent development? How about we start with honesty about what AI can and cannot do? Most AI agents are just overhyped chatbots with API access.
These best practices always ignore the environmental cost. Training these models burns through electricity like there is no tomorrow. Where is the sustainability discussion?