2026-05-06

Simon Willison — 2026-05-06#

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The highlight of today is Simon’s candid reflection on how highly reliable coding tools like Claude Code are blurring the line between professional “agentic engineering” and hands-off “vibe coding”. He raises important questions about accountability, the loss of traditional software evaluation metrics, and how the bottlenecks of the entire software development lifecycle are radically shifting.

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Vibe coding and agentic engineering are getting closer than I’d like Simon expands on a recent podcast conversation to discuss how he is increasingly treating AI agents like Claude Code as semi-black boxes, trusting them to write unreviewed production code. He notes that because AI can generate comprehensive tests and beautiful readmes in minutes, traditional signals of software quality are losing their value, making actual usage the most important metric. Furthermore, he observes that as coding speeds up exponentially, upstream bottlenecks like cautious, extensive design processes are being fundamentally challenged. Despite these shifts, he isn’t worried about the future of software engineering careers, emphasizing that these tools are simply amplifiers for a discipline that remains fiercely difficult.

2026-05-15

Simon Willison — 2026-05-15#

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Simon’s latest AI-assisted project is a lightweight QR code generator built entirely with the help of Claude. It perfectly highlights his ongoing exploration of “vibe-coding” to quickly spin up practical, small-scoped utilities for everyday tasks.

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[QR code generator] · Source Simon used Claude to write a custom tool for instantly generating QR codes. The utility gracefully handles standard text and URL inputs, and also features a dedicated mode for generating QR codes that connect mobile devices to WiFi networks. It serves as another practical demonstration of using generative AI to rapidly build, iterate, and ship helpful little tools.

2026-06-22

Simon Willison — 2026-06-22#

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Simon’s success in porting a PyTorch machine learning model to a browser-based WebGPU application entirely through “vibe coding” highlights a fascinating shift in developer workflows. It demonstrates how autonomous agents like Claude Code can now bridge significant gaps in domain knowledge, allowing developers to orchestrate the deployment of complex client-side AI tools while actively writing code for entirely different primary projects.

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Porting the Moebius 0.2B image inpainting model to run in the browser with Claude Code · Source Simon successfully ported the Moebius 0.2B lightweight image inpainting framework to run locally in the browser, relying purely on “vibe coding” with Claude Code. While waiting for Codex Desktop to complete mid-sized refactors for a new Datasette table UI, he instructed Claude in a terminal window to convert the original PyTorch model to ONNX, publish the 1.24GB converted weights to Hugging Face, and build a user interface hosted on GitHub Pages. To prevent the application from downloading the massive 1.3GB model on every single page load, he pointed a Claude subagent at a Whisper Web demo to successfully implement browser caching via the CacheStorage API. The core takeaway is the impressive capability of Opus 4.8 to act as a full-stack ML engineer—handling format conversion, model deployment, and front-end development—proving that heavy client-side AI is feasible today if users tolerate the initial download. After completing the project without writing a single line of code himself, Simon used Claude.ai to study his newly generated repository and gain a deeper technical understanding of how ONNX files bundle computation graphs and model weights together.