I’m part of a product team that relies on AI for tasks like generating metadata, creating thumbnails, translations, and labeling. We’re constantly experimenting with different providers—OpenAI, Anthropic, Google, etc.—to find the best fit for specific tasks.
The challenge? Every time we need to switch a model, add a new provider, or tweak something, it feels like starting from scratch. Updating APIs, reworking code, and dealing with billing—it’s a lot of overhead. This slows us down and makes rapid iteration harder, especially since our engineering team has to handle all the integrations manually.
If you’ve faced this, how do you manage it? Are there tools, frameworks, or approaches that make integrating and switching providers/models less painful? Would love to hear what’s worked for you.
Thanks for any advice!
0 comments
—
Ask HN: How Do You Handle Switching Between AI Providers/Models Efficiently? · HackerTrans
I’m part of a product team that relies on AI for tasks like generating metadata, creating thumbnails, translations, and labeling. We’re constantly experimenting with different providers—OpenAI, Anthropic, Google, etc.—to find the best fit for specific tasks.
The challenge? Every time we need to switch a model, add a new provider, or tweak something, it feels like starting from scratch. Updating APIs, reworking code, and dealing with billing—it’s a lot of overhead. This slows us down and makes rapid iteration harder, especially since our engineering team has to handle all the integrations manually.
If you’ve faced this, how do you manage it? Are there tools, frameworks, or approaches that make integrating and switching providers/models less painful? Would love to hear what’s worked for you.
Thanks for any advice!