# LLMs and Programming in the first days of 2024

DevFeed: [LLMs and Programming in the first days of 2024](<https://devfeed.tech/articles/llms-and-programming-in-the-first-days-of-2024-20631.md>)

Original publisher: [Read original article](<http://antirez.com/news/140>)

Published: 2024-01-02T10:56:14Z

Content type: opinion

Language: en

Sources: [Antirez](<https://devfeed.tech/sources/antirez.md>)

Topics: [LLMs](<https://devfeed.tech/topics/llms.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [ChatGPT](<https://devfeed.tech/topics/chatgpt.md>), [Python](<https://devfeed.tech/topics/python.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [chatgpt](<https://devfeed.tech/tags/chatgpt.md>), [llms](<https://devfeed.tech/tags/llms.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [programming](<https://devfeed.tech/tags/programming.md>), [python](<https://devfeed.tech/tags/python.md>)

## AI overview

A programmer reflects on using LLMs, including ChatGPT and locally running models, to accelerate coding and avoid low-value programming work. The article argues from personal experience that LLMs are most useful when users understand when to apply them, and may initially benefit already capable programmers more than those who are behind.

## Source excerpt

I'll start by saying that this article is not meant to be a retrospective on LLMs. It's clear that 2023 was a special year for artificial intelligence: to reiterate that seems rather pointless. Instead, this post aims to be a testimony from an individual programmer. Since the advent of ChatGPT, and later by using LLMs that operate locally, I have made extensive use of this new technology. The goal is to accelerate my ability to write code, but that's not the only purpose. There's also the intent to not waste mental energy on aspects of programming that are not worth the effort. Countless hours spent searching for documentation on peculiar, intellectually uninteresting aspects; the efforts to learn an overly complicated API, often without good reason; writing immediately usable programs that I would discard after a few hours. These are all things I do not want to do, especially now, with Google having become a sea of spam in which to hunt for a few useful things. Meanwhile, I am certainly not a novice in programming. I am capable of writing code without any aid, and indeed, I do so quite often. Over time, I have increasingly used LLMs to write high-level code, especially in Python, and much less so in C. What strikes me about my personal experience with LLMs is that I have learned precisely when to use them and when their use would only slow me down. I have also learned that LLMs are a bit like Wikipedia and all the video courses scattered on YouTube: they help those with the will, ability, and discipline, but they are of marginal benefit to those who have fallen behind. I fear that at least initially, they will only benefit those who already have an advantage. But let's take it step by step. # Omniscient or Parrots? One of the most concerning phenomena of this new wave of novelty and progress in machine learning is the limited ability of AI experts to accept their limited knowledge. Homo sapiens invented neural networks, and then, even more crucially, an algorithm t