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
In the fast-paced world of continuous integration and deployment (CI/CD), managing sensitive information like API keys, tokens, and credentials—collectively known as secrets—is not just a best practice; it's a critical foundation for security and efficiency. GitHub Actions provides a robust framework for automating workflows, but a common friction point for many development teams, particularly tho
The Challenge of Scalable Secrets Management in GitHub Actions For development teams scaling beyond a handful of repositories, managing environment-specific variables and secrets in GitHub Actions can quickly become a significant bottleneck. The manual duplication of configurations across multiple repos, especially when dealing with distinct environments like development, staging, and production
I got tired of the same three-step content publish loop: write draft → open CMS → paste, format, re-paste, fight the rich-text editor, click publish. Repeat for every environment — staging, then production. For one article, fine. For a team publishing 20+ pieces a month? That workflow is a quiet tax on everyone's time. So I wired up a pipeline that cuts the loop entirely. You commit a .md file to
Most teams I have worked with have one auth test in their suite. It looks like this: test('valid token verifies', () => { const token = signSync({ sub: 'user-1', aud: 'api://backend' }, secret); const result = verify(token, options); expect(result.valid).toBe(true); }); That test is fine. It is also a smoke test, not a regression suite. It catches the case where verification is completely b
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