Is debugging an AI system fundamentally different than debugging a traditional software system?

Mark Russinovich explains that debugging generative AI requires a different mindset than debugging traditional software.

Overview

• LLM-based systems are probabilistic, so the same input can produce different outputs across runs.
• Agentic systems compound this effect because later steps build on earlier decisions, so small variations can cascade.
• Because behavior can evolve run to run, debugging focuses less on finding a single deterministic “bug” and more on:
  • Adding guardrails to constrain behavior
  • Improving observation/observability to understand what the system did and why
• With the right guardrails and observation in place, non-determinism can be treated as a strength rather than purely a problem.