AI agents are good at doing one thing at a time. Give Claude a focused task and it performs. But real work isn’t one task. It’s a tree of tasks with dependencies, parallelism, and context that needs to flow between them. The multi-agent frameworks are multiplying. They’re all solving the wrong problem. What’s out there LangGraph models coordination as a state machine. You define nodes and edges in
Rust is an appealing language for building user interfaces for a variety of reasons, especially the promise of delivering both performance and safety. However, finding a good architecture is challenging. Architectures that work well in other languages generally don’t adapt well to Rust, mostly because they rely on shared mutable state and that is not idiomatic Rust, to put it mildly. It is sometim
In 2023, we launched an AI-powered Chief of Staff for engineering leaders—an assistant that unified information across team tools and tracked critical project developments. Within a year, we attracted 10,000 users, outperforming even deep-pocketed incumbents such as Salesforce and Slack AI. Here is an early demo: By May 2024, we realized something interesting: while our AI assistant was gaining tr
Lately I’ve gotten heavily back into making stuff, and it’s mostly because of LLMs. I thought that I liked programming, but it turned out that what I like was making things, and programming was just one way to do that. Since LLMs have become good at programming, I’ve been using them to make stuff nonstop, and it’s very exciting that we’re at the beginning of yet another entirely unexplored frontie
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Cord: Coordinating Trees of AI Agents
Xilem: an architecture for UI in Rust
Building AI Products—Part I: Back-end Architecture
How I write software with LLMs - Stavros' Stuff