Hi everyone,
In this article I’ll share a practical trick to make your use of Claude, ChatGPT and other LLM tools more efficient while still getting strong responses.
Plan with strong model, execute with a lighter one
To reduce the cost of working with contracts, consider using a stronger model to plan and a lighter model to execute. This applies to agentic workflows more broadly as well.
The amount you can save will depend on the specific use case and models involved, but lighter models can cost 2-5X less (sometimes even 10X+) per token than more powerful but expensive ones.
For example, you could prompt: “can you help me plan out this workflow and decide which model I should use to balance performance with cost and efficiency? Here’s some context:…”
If the task is reasonably straightforward, a lighter model can often get the job done without issue and at a lower cost. The more powerful model can still help plan the workflow, break it into tasks, and orchestrate it as needed.
For example, let’s say you’re trying to:
Find 10 agreements that meet certain criteria
Identify several clauses or data points within those agreements
Research additional information related to the results
A stronger model might be useful for determining the overall approach: how to identify the right agreements, what information should be extracted, which research sources to use, etc.
However, once that plan is established, most of the execution steps may be straightforward for a lighter model.
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In contrast, imagine you’re trying to understand whether an assignment clause is enforceable under unfamiliar governing law. In that example, using a stronger model may make more sense.
The core idea: use the stronger, more expensive model where it adds the most value.
Hope this is helpful. If there’s other content that you’d find useful, feel free to drop a comment or send me a note.
Thanks,
Leonid