Building Secure AI Applications

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Introduction to Building Secure AI Applications

In the previous lesson, we added guardrails around an AI application.

We checked incoming requests, protected access to tools and data, moderated unsafe content, and validated the model’s output

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How efficiently are we using the AI model?

Every model request consumes tokens, takes time, and has a cost.

In the next lesson, we will look at optimising AI applications for cost and performance.

We will measure token usage, reduce unnecessary prompt content, control response length, choose appropriate models, and learn how to balance cost, latency, and quality in a production AI application.

Citations :

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Skillioma (October 28, 2026) Building Secure AI Applications. Retrieved from https://repo.skillioma.com/building-secure-ai-applications/.

"Building Secure AI Applications." Skillioma - October 28, 2026, https://repo.skillioma.com/building-secure-ai-applications/

"Building Secure AI Applications." Skillioma - Accessed October 28, 2026. https://repo.skillioma.com/building-secure-ai-applications/

Skillioma October 28, 2026 Building Secure AI Applications., viewed October 28, 2026,<https://repo.skillioma.com/building-secure-ai-applications/>

Skillioma - Building Secure AI Applications. [Internet]. [Accessed October 28, 2026]. Available from: https://repo.skillioma.com/building-secure-ai-applications/

"Building Secure AI Applications." Skillioma [Online]. Available: https://repo.skillioma.com/building-secure-ai-applications/. [Accessed: October 28, 2026]