Production Failed at 11:47 PM Agentic AI — How We Saved a $60,000 Deployment

Описание: At 11:47 PM, the system went down.

By 9:00 AM, we had to demo it to a major enterprise customer.

$60,000 was on the line.

This is a real production war story from an agentic AI deployment — what failed, why it failed, and the exact fixes that saved the contract.

Download Production Patterns and Checklist:
https://community.nachiketh.in

📅 Next Agentic AI Bootcamp cohort:
https://bootcamp.nachiketh.in

In this video, you’ll learn:
• Why the system worked perfectly in dev but collapsed in production
• How API rate limits silently caused cascading failures
• Why retries alone are NOT enough
• How circuit breakers prevent total system collapse
• How fallback strategies saved the live demo
• The production patterns that matter more than prompts

This wasn’t a prompt issue.
This wasn’t an LLM issue.
This was a production architecture failure.

And it happens all the time.

💡 Key takeaway:
POCs test if things work.
Production systems test how they fail.

If you’re building agentic systems for real users, you need:
• Retry with exponential backoff
• Circuit breakers
• Graceful degradation
• Caching
• Failure-mode testing

This is what separates demos from real production systems.

🎓 In the Agentic AI Enterprise Bootcamp, we teach:
• How to design agents that survive production
• Real failure modes you won’t see in tutorials
• Testing, deployment, monitoring, and recovery patterns
• War stories from real systems under load

Next cohort starts Feb 15
👉 Link in description
https://bootcamp.nachiketh.in

If this video helped, check out:
• Testing Strategies for Agentic Systems
• Deploying Agents: AWS vs Azure vs GCP
• Production Interview Questions (Senior Level)

Subscribe for real production lessons — not toy demos.