# Use Function Calls Instead of Parsing LLM Output

DevFeed: [Use Function Calls Instead of Parsing LLM Output](<https://devfeed.tech/articles/don-t-parse-call-33476.md>)

Original publisher: [Read original article](<https://timkellogg.me/blog/2025/10/03/functions>)

Published: 2025-10-03T00:00:00Z

Content type: article

Language: en

Sources: [Tim Kellogg](<https://devfeed.tech/sources/tim-kellogg.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [API](<https://devfeed.tech/topics/api.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [api](<https://devfeed.tech/tags/api.md>), [functions](<https://devfeed.tech/tags/functions.md>), [llms](<https://devfeed.tech/tags/llms.md>), [openai](<https://devfeed.tech/tags/openai.md>), [parsing](<https://devfeed.tech/tags/parsing.md>)

## AI overview

The article argues that developers should use function-calling APIs instead of parsing formatted text from large language models. It presents functions as expressive enough to model failures, repeated calls, optional calls, and varied call sequences, and describes this approach as a foundation for agentic behavior.

## Source excerpt

Instead of writing crap tons of parsing code for LLMs you can just use functions. It's easy.