Production AI agents face classic software engineering reliability issues

Arpit Bhayani

Arpit Bhayani

May 30, 2026 • 1 min read


Everyone talks about agent intelligence. Then agents reach production - or face even the slightest bit of load - and suddenly the hard problems are:

  • memory management
  • concurrency
  • backpressure
  • retries
  • timeouts
  • failure handling
  • observability

Agentic loops are long-running, non-deterministic, and inherently error-prone, which makes reliability difficult. The more complex the agents, the more interesting the failure modes.

Turns out, agents are often more of a classic software engineering problem than an AI problem. Good engineering practices are not going anywhere.

Arpit Bhayani

Principal Engineer II at Razorpay - building Agent Studio, Ex-staff engg at GCP Memorystore & Dataproc, Creator of DiceDB, ex-Amazon Fast Data, ex-Director of Engg. SRE and Data Engineering at Unacademy. I spark engineering curiosity through my no-fluff engineering videos on YouTube and my courses