Really valuable write-up, especially the part about testing what happens when the local model fails or the wrong token is used. The example involving sensitive HR information highlights an important point: keeping AI processing local doesn't automatically guarantee data privacy if logs and fallback behavior aren't handled carefully. At Oglas AI, we believe practical AI solutions need to be built around security, reliability, and real business requirements not just functionality. Great to see these real-world implementation details covered so clearly!
Really valuable write-up, especially the part about testing what happens when the local model fails or the wrong token is used. The example involving sensitive HR information highlights an important point: keeping AI processing local doesn't automatically guarantee data privacy if logs and fallback behavior aren't handled carefully. At Oglas AI, we believe practical AI solutions need to be built around security, reliability, and real business requirements not just functionality. Great to see these real-world implementation details covered so clearly!