The Wall Street Journal ran a piece yesterday on JustPaid, a 9-person Mountain View startup. They used OpenClaw and Claude Code to stand up seven AI agents that write code, review it, and run QA around the clock. In one month: 10 major features shipped. Each one would have taken a human engineer a month or more. This story is getting passed around as proof that the autonomous engineering team is h
Introduction Picture two doctors updating the same patient record at the same time - one in São Paulo, the other in London. Both are offline. When connectivity returns, whose changes prevail? This is not a hypothetical. It is the everyday reality of distributed systems: multiple nodes, no shared clock, no guaranteed network. The conventional answer has long been locking - one node waits while an
Introduction Some code works. Some code lasts. The difference rarely comes down to typing speed, syntax mastery, or how many nights you're willing to push through. It comes down to how you think about a problem before you write a single line. Big-O notation is a mathematical framework that describes how an algorithm performs as its input grows. In plain terms, it answers one question:
I went into a bunch of OpenClaw discussions expecting the usual advice about subagents: better prompts, cleaner folders, maybe some heroic config. What I found was more interesting. The OpenClaw setups that actually seem to hold up are not just "one agent with more prompts." They are separate services with separate trust zones. The pattern that keeps showing up looks like this: a librarian agent a
E aí, gurizada! De uns tempos pra cá, eu percebi um burburinho enorme em torno de uma ferramenta que tem chamado a atenção, e não é por menos: o OpenClaw. Eu, que vivo mergulhado nesse universo de IA e automação, gravei um vídeo recentemente, que está lá no meu canal, assista no YouTube, justamente pra desmistificar essa parada. E hoje, vim aqui no Dev.to pra gente conversar um pouco mais sobre o
If you use ChatGPT, Claude, Grok, Copilot, or Gemini daily, it feels like you're talking to a person. It remembers what you said three messages ago. It references the project details you shared yesterday. It feels like the model has a persistent brain that is learning about you. But it’s a lie. From an architectural standpoint, an LLM is the most "forgetful" piece of software you will ever use. Ev
Most symbolic systems rely on multiple primitives. Addition, multiplication, exponentials, logarithms — each plays a different role in structuring expressions. But what happens if you force everything through a single operator? This idea becomes concrete with the EML operator: eml(x, y) = exp(x) − ln(y) In theory, this operator can express all elementary functions. But theory doesn’t tell us what