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When to Let Users Customize AI Models (And When to Keep It Simple)
AI tools are more powerful than ever, but with that power comes complexity. One big decision for product builders is whether users should be able to choose their AI model or if the system should handle it for them.
I recently added support for selecting LLM providers in my VAPI integration. Some users found it valuable, but it also raised an important question—when does customization improve the experience, and when does it just add confusion?
Here are three key factors to consider.
1. Customization is helpful when users have different needs
Not all AI models are the same. Some prioritize speed, others cost, and some excel at specific tasks like reasoning or summarization. If your users have different needs, letting them choose their model can improve their experience.
For example, in my case:
- Some users wanted OpenAI for top-tier performance.
- Others needed Claude for handling long-context tasks.
- Some preferred open-source models to reduce costs.
Since different users had different priorities, model selection made sense.
2. Customization can add complexity when most users do not need it
Too many choices can overwhelm users. Most people just want an AI that works—they do not want to research different models, compare costs, or tweak settings.
If customization is not solving a clear problem, it can make setup harder, require extra documentation, and lead to support issues when users select the wrong model.
3. A good middle ground is smart defaults
The best approach is often a mix of both—offer customization for those who need it but set a strong default so most users do not have to think about it.
In my case, I chose a default model that works well for most use cases. Users who need more control can change it, but they do not have to. This keeps things simple while still giving flexibility to power users.
Conclusion
Letting users pick their AI model can be useful, but only when it solves a real problem. If customization adds complexity without clear benefits, it is better to keep things simple.
If you are building AI-powered features, think about your users. Would giving them control help them get better results, or would it just slow them down? The best products strike a balance between flexibility and ease of use.
And that’s it! What do you think? I’d love to hear your thoughts—feel free to share them. For more insights like this, subscribe to my newsletter.
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