Build evaluation harnesses that measure output quality, faithfulness, hallucination rate, latency, and cost across model versions and prompt changes — governing whether AI features ship or roll back.
Implement prompt engineering at the system level, including guardrails, output filtering, and red-teaming to ensure safe and reliable AI behaviour.
Integrate workflow automation platforms (e.g. n8n, Make, Power Automate) to extend AI capabilities into business operations.
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