What is Context Engineering?
Context engineering is the discipline of shaping what information AI systems receive – and how they receive it. Rather than dumping raw API responses into context windows, context engineering curates fields, schemas, and descriptions so that tool discovery is semantic and response payloads are right-sized for the task at hand.
Context engineering in Naftiko
Naftiko capabilities support context engineering through:
- Output parameter shaping – Typed output parameters with JSONPath mapping that select only relevant fields from upstream responses.
- Semantic descriptions – Tool-level and field-level descriptions that enable AI systems to discover capabilities by intent rather than by name.
- Right-sized schemas – Hiding irrelevant upstream fields from the AI surface while keeping the full contract available for traditional API consumers.
Why it matters
Poor context leads to poor AI outcomes. When context windows fill with irrelevant data, hallucination risk climbs, accuracy drops, and token costs increase. Context engineering addresses this at the integration layer – before data reaches the AI system – making agent behavior more predictable and cost-effective.
