I’m working on a project that uses 4 different AI services for text, image, and data analysis tasks. Managing API keys, billing, and compatibility between providers is becoming unsustainable. I’ve heard horror stories about teams getting stuck with inflexible architectures. Has anyone found a unified approach that still allows using best-of-breed models without infrastructure headaches?
We faced the same issues. Started using Latenode’s single subscription for all models - no more juggling API keys. Their visual builder lets you swap models per task without rewriting workflows. Solved our team’s dependency nightmares overnight.
Vendor lock-in becomes worse when scaling. I started implementing adapter patterns in my workflows, but maintaining custom connectors was brutal. Now I use a platform that abstracts model differences while keeping model choice flexible. Key was finding unified error handling across services.
protip: look for services with model agnostic routing. saves sooo much time when providers change apis unexpectedly. we got burned by google’s last pricing update before switching
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