2026 in LLMs (so far)
Simon Willison reflects on how AI coding agents became reliable daily tools, urging creators to be much more ambitious with what they build.
For a long time, AI coding helpers were fun to play with but made too many careless mistakes to trust for heavy lifting. As underlying models quietly improve, automated tools have crossed a critical line from clumsy experiments into genuinely reliable assistants. When your tools actually work without constant babysitting, everything changes about how you create software.
Developer Simon Willison suggests the best response to these breakthroughs is to "be more ambitious" with your projects. Instead of holding back because you lack a traditional computer science background, modern coding agents make it practical to spin up multiple ideas, test prototypes rapidly, and tackle software challenges that used to require entire engineering teams.
If you are just getting started, this shift is great news. You do not need to memorize every syntax rule before you start making things. By pairing up with modern AI tools and testing their limits through hands-on experiments, you can turn your ideas into working software faster than ever before.
Originally reported by Simon Willison
Read the originalMore news
Kākāpō Party
See how combining Claude with Claude Code can turn a fun idea into a live interactive web animation and automate recording it to video.
Source: Simon Willison
Pixel Canary is now available in stealth for free on AI Gateway
Vercel has released Pixel Canary, a new experimental AI model tuned for frontend coding and Next.js development that is currently free to test.
Source: Vercel / v0 News
Inside Chats: How Lovable's Agents Work Together
Lovable revealed the tech behind its multi-agent Chats feature, showing how it safely separates brainstorming from live app building.
Source: Lovable Blog
Weekly vibe-coding tips — coming soon
We're getting this ready. Leave your email and we'll let you know the moment it launches. No fluff, unsubscribe whenever.