Optimising AI Applications for Cost and Performance

Optimising AI Applications for Cost and Performance
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Introduction to Cost Optimization and Token Management

In the previous lessons, we focused on building AI applications professionally and adding guardrails to make them safer.

Now we are going to look at another challenge that becomes important as an AI application grows:

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As applications move into production, the next challenge is understanding what is happening after they are deployed.

In the next lesson, we will explore Logging, Monitoring and Versioning AI Apps, and look at how developers track application behavior, diagnose problems, and manage changes over time.

Citations :

Skillioma (October 28, 2026) Optimising AI Applications for Cost and Performance. Retrieved from https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/.
"Optimising AI Applications for Cost and Performance." Skillioma - October 28, 2026, https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/
"Optimising AI Applications for Cost and Performance." Skillioma - Accessed October 28, 2026. https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/
Skillioma October 28, 2026 Optimising AI Applications for Cost and Performance., viewed October 28, 2026,<https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/>
Skillioma - Optimising AI Applications for Cost and Performance. [Internet]. [Accessed October 28, 2026]. Available from: https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/
"Optimising AI Applications for Cost and Performance." Skillioma [Online]. Available: https://repo.skillioma.com/optimising-ai-applications-for-cost-and-performance/. [Accessed: October 28, 2026]

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