Deploying AI in Production: Lessons Learned

AI is Easy. Production AI is Hard.

Building a wrapper around OpenAI's API takes a weekend. Building a resilient, autonomous AI system that scales to thousands of users takes serious engineering.

Handling Rate Limits and Latency

When building our AI Social Media Engine, we quickly hit rate limits from both the LLM providers and the social platforms themselves.

The Solution:

• Robust Queueing: We implemented background job processing (using tools like Hangfire and Redis).
• Circuit Breakers: If an API goes down or latency spikes, the system automatically backs off and retries later.
• Agentic Workflows: We broke down complex prompts into smaller, chained LLM calls. One agent drafts, another critiques, and a final agent formats.

This approach significantly reduced hallucinations and improved the overall reliability of the system.