2026-02-23 07:58:43
The Claude C Compiler: What It Reveals About the Future of Software
On February 5th Anthropic's Nicholas Carlini wrote about a project to use parallel Claudes to build a C compiler on top of the brand new Opus 4.6Chris Lattner (Swift, LLVM, Clang, Mojo) knows more about C compilers than most. He just published this review of the code.
Some points that stood out to me:
- Good software depends on judgment, communication, and clear abstraction. AI has amplified this.
- AI coding is automation of implementation, so design and stewardship become more important.
- Manual rewrites and translation work are becoming AI-native tasks, automating a large category of engineering effort.
Chris is generally impressed with CCC (the Claude C Compiler):
Taken together, CCC looks less like an experimental research compiler and more like a competent textbook implementation, the sort of system a strong undergraduate team might build early in a project before years of refinement. That alone is remarkable.
It's a long way from being a production-ready compiler though:
Several design choices suggest optimization toward passing tests rather than building general abstractions like a human would. [...] These flaws are informative rather than surprising, suggesting that current AI systems excel at assembling known techniques and optimizing toward measurable success criteria, while struggling with the open-ended generalization required for production-quality systems.
The project also leads to deep open questions about how agentic engineering interacts with licensing and IP for both open source and proprietary code:
If AI systems trained on decades of publicly available code can reproduce familiar structures, patterns, and even specific implementations, where exactly is the boundary between learning and copying?
Tags: c, compilers, open-source, ai, ai-assisted-programming, anthropic, claude, nicholas-carlini, coding-agents
2026-02-23 07:54:39
London Stock Exchange: Raspberry Pi Holdings plc
Striking graph illustrating stock in the UK Raspberry Pi holding company spiking on Tuesday:
The Telegraph credited excitement around OpenClaw:
Raspberry Pi's stock price has surged 30pc in two days, amid chatter on social media that the company's tiny computers can be used to power a popular AI chatbot.
Users have turned to Raspberry Pi's small computers to run a technology known as OpenClaw, a viral AI personal assistant. A flood of posts about the practice have been viewed millions of times since the weekend.
Reuters also credit a stock purchase by CEO Eben Upton:
Shares in Raspberry Pi rose as much as 42% on Tuesday in a record two‑day rally after CEO Eben Upton bought stock in the beaten‑down UK computer hardware firm, halting a months‑long slide, as chatter grew that its products could benefit from low‑cost artificial‑intelligence projects.
Two London traders said the driver behind the surge was not clear, though the move followed a filing showing Upton bought about 13,224 pounds worth of shares at around 282 pence each on Monday.
Tags: ai, generative-ai, raspberry-pi, llms, ai-agents, openclaw
2026-02-22 23:53:43
Gabriel Chua (Developer Experience Engineer for APAC at OpenAI) provides his take on the confusing terminology behind the term "Codex", which can refer to a bunch of of different things within the OpenAI ecosystem:
In plain terms, Codex is OpenAI’s software engineering agent, available through multiple interfaces, and an agent is a model plus instructions and tools, wrapped in a runtime that can execute tasks on your behalf. [...]
At a high level, I see Codex as three parts working together:
Codex = Model + Harness + Surfaces [...]
- Model + Harness = the Agent
- Surfaces = how you interact with the Agent
He defines the harness as "the collection of instructions and tools", which is notably open source and lives in the openai/codex repository.
Gabriel also provides the first acknowledgment I've seen from an OpenAI insider that the Codex model family are directly trained for the Codex harness:
Codex models are trained in the presence of the harness. Tool use, execution loops, compaction, and iterative verification aren’t bolted on behaviors — they’re part of how the model learns to operate. The harness, in turn, is shaped around how the model plans, invokes tools, and recovers from failure.
Tags: definitions, openai, generative-ai, llms, ai-assisted-programming, codex-cli
2026-02-21 09:30:21
We’ve made GPT-5.3-Codex-Spark about 30% faster. It is now serving at over 1200 tokens per second.
— Thibault Sottiaux, OpenAI
Tags: openai, llms, ai, generative-ai, llm-performance
2026-02-21 08:37:45
Andrej Karpathy talks about "Claws"
Andrej Karpathy tweeted a mini-essay about buying a Mac Mini ("The apple store person told me they are selling like hotcakes and everyone is confused") to tinker with Claws:I'm definitely a bit sus'd to run OpenClaw specifically [...] But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level.
Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. [...]
Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). [...]
Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.
Andrej has an ear for fresh terminology (see vibe coding, agentic engineering) and I think he's right about this one, too: "Claw" is becoming a term of art for the entire category of OpenClaw-like agent systems - AI agents that generally run on personal hardware, communicate via messaging protocols and can both act on direct instructions and schedule tasks.
It even comes with an established emoji 🦞
Tags: definitions, ai, andrej-karpathy, generative-ai, llms, ai-agents, openclaw
2026-02-21 07:47:10
I've been wanting to add indications of my various other online activities to my blog for a while now. I just turned on a new feature I'm calling "beats" (after story beats, naming this was hard!) which adds five new types of content to my site, all corresponding to activity elsewhere.
Here's what beats look like:
![Screenshot of a fragment of a page showing three entries from 30th Dec 2025. First: [RELEASE] "datasette-turnstile 0.1a0 — Configurable CAPTCHAs for Datasette paths usin…" at 7:23 pm. Second: [TOOL] "Software Heritage Repository Retriever — Download archived Git repositories f…" at 11:41 pm. Third: [TIL] "Downloading archived Git repositories from archive.softwareheritage.org — …" at 11:43 pm.](https://static.simonwillison.net/static/2026/three-beats.jpg)
Those three are from the 30th December 2025 archive page.
Beats are little inline links with badges that fit into different content timeline views around my site, including the homepage, search and archive pages.
There are currently five types of beats:
That's five different custom integrations to pull in all of that data. The good news is that this kind of integration project is the kind of thing that coding agents really excel at. I knocked most of the feature out in a single morning while working in parallel on various other things.
I didn't have a useful structured feed of my Research projects, and it didn't matter because I gave Claude Code a link to the raw Markdown README that lists them all and it spun up a parser regex. Since I'm responsible for both the source and the destination I'm fine with a brittle solution that would be too risky against a source that I don't control myself.
Claude also handled all of the potentially tedious UI integration work with my site, making sure the new content worked on all of my different page types and was handled correctly by my faceted search engine.
I actually prototyped the initial concept for beats in regular Claude - not Claude Code - taking advantage of the fact that it can clone public repos from GitHub these days. I started with:
Clone simonw/simonwillisonblog and tell me about the models and views
And then later in the brainstorming session said:
use the templates and CSS in this repo to create a new artifact with all HTML and CSS inline that shows me my homepage with some of those inline content types mixed in
After some iteration we got to this artifact mockup, which was enough to convince me that the concept had legs and was worth handing over to full Claude Code for web to implement.
If you want to see how the rest of the build played out the most interesting PRs are Beats #592 which implemented the core feature and Add Museums Beat importer #595 which added the Museums content type.
Tags: blogging, museums, ai, til, generative-ai, llms, ai-assisted-programming, claude-artifacts, claude-code
