TLA+ is also (one of the) method that we at Intent Lab used to build mission critical infra software like Agent FS. Key is to make it verifiable and scalable - going through millions of states and also ensure the TLA+ to Rust/C conversion doesn’t weaken the end to end correctness. intentlab.ai/blog/turn-your-…

Good afternoon from Vienna People of Pi ☀️ Some slightly different Sunday meditations today in which @mitsuhiko talks about some shared frustrations with agentic software engineering. Remember that you're not alone in finding it harder than it looks!

This is the way! Give it a try! Q2 but still strong!

I can’t stress enough how little an idea matters compared to the agency of the people executing the idea. I have had the privilege of knowing and sometimes even working with some of the most successful people (by various metrics). The difference between mediocre and excellent work and outcomes is predominantly one of agency. In practice this means: they dont wait for things to happen to them they go out and make things happen for them. They don’t wait for someone else to do something, for someone to teach them, for someone to give them the path, etc. They just go out and find a way to do it. I think the single biggest superpower these people have is the realization/belief that the world around them is completely mutable. Most everything that happens is because a person made it happen. I used to tell people to look around the room you’re sitting in. Look at everything. Every noun. It almost all exists because a person willed it into existence. Nothing is stopping you from doing the same. I see people online all the time dismissing someone else’s success because “I had that idea first” or whatever. I mean… yeah? If so then the difference is… you. So a bit of a self own whenever I hear that. Number one tip: act with agency.

我今天针对一个AI模型做深入分析， Qwen 3.8 27B xhigh 的速度比 GPT 5.6 sol Max 快5倍不止，而且 Qwen 3.8 27B分析的结论非常严密 包括今天和英伟达的芯片架构师聊过，他的一个观点 “30B的稠密模型就能解决个人编码的需求，以后不需要高显存带宽的更贵机器，因为AI模型本身会进化” 这句话就像我今晚做的试验一样， Qwen 3.8 27B 的足够能力，让我觉得，其实GPT再强大，它后台的服务器集群再牛逼，也许分到每个用户身上，就是30B的算力资源

Control the ideas, not the code: blog post here antirez.com/news/169

📊 Sometimes the smallest evals reveal the biggest insights. See what 50,000 runs of a 5-line task taught the @code team about model efficiency, tool use, and AI behavior. 📖 Read the full post: aka.ms/vscode/blog/evals

Practical guide for debugging AI agents in @code with OpenTelemetry. Shows how to go from "agent feels slow" to seeing exact token counts, model latency, and finish reasons per turn. The @aspiredotdev dashboard runs locally in Docker, no accounts needed. opentelemetry.io/blog/2026/g…