The common mistake
Many AI applications start as demos: a text box, a model, and a promise that is too large. It charms quickly and fails quietly.
An LLM becomes more useful when it enters as a component in a larger system. It receives context, operates under contract, emits signals, and has clear limits.
Contract before prompt
Before writing the perfect prompt, it is worth asking:
- What input does the component accept?
- What output is considered valid?
- What happens when the answer is partial?
- How will cost, latency, and quality be observed?
Larger system
user -> intent -> context -> model -> validation -> action
The model does not need to carry the whole architecture on its back. When it fails, the system should still know what to do.