Most production AI agents don't fail because the model is bad. They fail because the infrastructure around them is invisible.
You've probably seen this already.
The agent worked perfectly in your notebook. It passed evals. The demo went smoothly. Leadership approved the rollout. Then production happened.
Within two days, a tool call started returning malformed JSON and the agent silently continued with bad data. A prompt that worked on GPT-4o behaved differently on Claude. Latency exploded halfway through a multi-step workflow, and nobody could tell whether the problem was retrieval, the model, or an external API.
That's the real production gap in 2026.
