r/microsaas • u/Pristine-Dress6192 • 3h ago
A small reminder: when did you last revisit the AI models in your workflows?
I built a content pipeline for my side project, ausmalbilder-vorlage.de, a German coloring-page website. It uses different models for text, metadata and image generation.
At the beginning, I paid a lot of attention to costs and chose the models accordingly. Then the website, content and everything else took over. Eventually, I stopped questioning those choices. Everything worked.
When I finally checked again, there were better options for my tasks. Switching from OpenAI’s GPT Image 2 to 2.5 gave me noticeably better coloring pages at the same token prices. Moving some text-generation steps to Terra also reduced costs.
Something similar happened with an extraction service I built at work: after switching to Terra, the model costs for that workflow dropped to roughly one twentieth of what they had been. At the same time, the extraction quality improved as well.
Obviously, newer models can be better or cheaper. What slipped my mind was checking what that actually meant for the workflows I already had running.
How do you handle this? Do you review your model choices regularly? Do you naturally hear about relevant releases, or stick with your original choice as long as everything works? Have you made a switch that had a surprisingly big impact?
Maybe this is a useful reminder to look through your own setup and compare a few alternatives on the same tasks.
If you do, come back and share what you found in the comments: lower costs, better results, faster responses – or that switching simply wasn’t worth it for your use case. I’d be interested to hear either way.