---
title: "Simon Willison Analyzes Impact of AI Coding Agents on Personal Output via Code Frequency Chart"
source: "Simon Willison 博客（Atom）"
source_tier: "t2"
url: "https://simonwillison.net/2026/Jul/13/datasette-code-frequency/#atom-everything"
permalink: "https://feed.astralor.com/items/itm_2a1ce7713b71c0d93eb32f18"
published: "2026-07-13T21:45:27.000Z"
score: 76
channel: "ai"
tags: ["AI Coding Agents","Datasette","GitHub","Opus 4.5","Simon Willison","code frequency chart"]
---

# Simon Willison Analyzes Impact of AI Coding Agents on Personal Output via Code Frequency Chart

## AI commentary

> This blog post is a must-read for developers, as it quantitatively validates the real productivity gains from AI coding agents rather than just talking about trends. For teams and individuals evaluating whether to adopt AI-assisted tools, this is an intuitive reference case.

## At a glance

In his blog, Simon Willison shares an experiment where he uses a GitHub code frequency chart to visually illustrate how coding agents (such as Opus 4.5-class models) alter his development productivity. The post highlights the significant impact of AI-assisted programming tools on personal workflows and output patterns, sparking reflection on the future of human-AI collaboration.

## Key points

- Simon Willison uses a GitHub code frequency chart to compare commit patterns before and after introducing AI coding agents.
- Advanced coding agents like Opus 4.5-class models significantly boost personal code output.
- The experiment reveals that AI tools can alter developer work rhythms and creative approaches.
- The analysis sparks discussion on the long-term implications of AI-assisted programming.

## Full text

Out of curiosity I decided to see if I could find a useful illustration of the impact of coding agents and Opus 4.5 class models on my own output. The …

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