Custom GPTs vs API

Custom GPTs vs Using the API. What should you consider?

At some point, creating a custom GPT may be more hassle than you need but it doesn’t mean that GPT is not a good tool, we just have to re-work how we use it. I’ll outline why a custom GPT is a good way of harnessing the power of GPT, and then how you might think about the next step.

Building a Custom GPT

Pros

• Rapid prototyping: Getting a Proof of Concept up and running is quick, and exposes the power immediately
• Non-technical: Programming a GPT is done in natural language; anyone can do it!
• For Specific, narrow tasks: If your use case is well-defined and doesn’t require complex integrations, a custom GPT is a winner.

Cons

• Loosely Structured: Its very easy to get into edge cases that aren’t easy to predict
• Non-technical: When code interpreter is used, it can be very easy to miss what your GPT is doing
• Non-Deterministic: The same question in one chat can often produce different results in another.

Integrating with the API

Pros

• Control: You have full control over what the LLM has access to and how it responds.
• Complex integrations: If you need to combine the language model with other services or data sources, the API is the way to go.
• High customization: Fine-tuned control over your prompts, parameters, and post-processing.
• Cost efficiency: Not charged on a per seat basis, the API calls are charged per word in/out

Cons

• UI: No longer do you have the simple UI that staff will know - you need to build this.
• Technical expertise required: Integrating with the API requires programming.
• Development time: You’re gonna need much more time to build.
• Maintenance : Model performance changes over time and the setup will need adjusting to accommodate for this.

Best Practices

Regardless of which method you choose, keep these top of mind:

• Start Small: Begin with a well-defined use case and expand from there.
• Monitor Performance: Keep an eye on the quality, is it still doing what you want/need?
• Iterate and Refine: Using the monitoring above, adjust your implementation to improve.

TL;DR

As your eyes are opened to the power of GPT, it feels like you can throw more at it and get results. You can, but you might have to change how you throw it.