Originally published on tamiz.pro.
The Production Reality Check
Every AI agent demo looks magical until it hits production. The moment you try to ship one, reality sets in: hallucinations, context drift, unpredictable failures, and zero reproducibility. Engineers spend weeks firefighting edge cases that never surfaced in notebooks.
The core problem isn't the LLM — it's the agent architecture. Agents chain together non-deterministic decisions, and each step multiplies failure modes exponentially. A planner that misinterprets a goal, a tool that returns slightly wrong data, a memory system that forgets critical context — any of these can derail the entire workflow.
Why Agents Collapse Under Real Constraints
