𝟳 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗧𝗵𝗮𝘁 𝗕𝗿𝗲𝗮𝗸 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀
Your AI agent works in testing. It is fast and accurate. Then you deploy it to production. Suddenly, users report timeouts and errors.
Building resilient AI agents requires more than good code. You must prepare for the messy reality of production.
Here are 7 mistakes that break AI agents and how to fix them.
- Ignoring External API Failures Developers often assume API calls will always work. They do not. Network requests fail due to timeouts or rate limits.
- Wrap all calls in try-catch blocks.
- Set specific timeout values for every request.
- Add retry logic with exponential backoff.
- Use circuit breakers for failing services.
- Treating Failures as Binary Many developers think a system either works or it fails. In reality, parts of a system fail while others stay online.
- Design multi-tier fallback strategies.
- Define what reduced functionality looks like.
- Keep serving requests using available components.
- Poor Logging and Visibility If you have minimal logs, you are blind during an outage. You cannot fix what you cannot see.
- Log at different levels like INFO and ERROR.
- Use request IDs to trace user paths.
- Track response time percentiles (p50, p95, p99).
- Set up alerts for error rate spikes.
- Testing Only Happy Paths If you only test successful runs, your agent cannot recover from stress.
- Use chaos engineering to break dependencies.
- Simulate network latency and timeouts.
- Test with malformed data formats.
- Run load tests beyond your expected capacity.
- Losing Agent State If an agent crashes without saving its progress, it loses all context.
- Checkpoint state at key milestones.
- Use idempotent operations to prevent duplicate actions.
- Store enough context to resume workflows.
- Hardcoding Configurations Putting timeouts and API endpoints directly in your code makes updates slow.
- Move configurations to environment variables.
- Use feature flags for new behaviors.
- Make thresholds adjustable without redeploying code.
- Generic Error Handling Using the same fix for every error is a mistake. A validation error needs a different response than a network timeout.
- Separate retriable errors from permanent errors.
- Retry transient issues like rate limits.
- Do not retry permanent issues like authentication failures.
Resiliensi adalah tentang menulis kode yang mengantisipasi realitas. Mulailah dengan mengaudit agen-agen Anda saat ini terhadap tujuh jebakan ini.