Tag: agent systems

This is a useful operational map: the model produces outputs, the inference service runs and meters it, the harness assembles context and tools, and the complete agent system turns those pieces into behavior. The distinction matters most during diagnosis. Missing context, unavailable tools, malformed tool calls, slow inference, and weak reasoning can look like one vague "AI problem" while belonging to different owners and requiring different fixes.

The boundaries are not laws of nature. Products bundle layers, vendors reuse terms, and even experienced teams disagree about how much orchestration is required before a tool becomes an agent or a harness. So this vocabulary should be treated as a troubleshooting interface, not a universal ontology. If naming a layer helps route a defect, compare two systems fairly, or avoid replacing a model when the real problem is context assembly, it has earned its keep. If it only creates a taxonomy argument, it has become another abstraction to maintain.