MonoX: a foundation for AI agents, a clearer path to delivery
An open-source foundation connecting repository structure, agent context, and deployment contracts. What to try today, and what still needs checking.
Read the articleTurn AI-generated code into a project you can test, deploy, and maintain. Explore tools and hands-on lessons, with MonoX as an open-source foundation to build on.
Try it first. Understand along the way. Take it to your next project.
// context.md
goal: "make the next step easier"
constraints: ["clear", "testable", "human"]Define the problem before asking for a solution.
// one useful change at a time
const change = await build(context);
await test(change);Make small changes you can actually verify.
// the human stays in the loop
if (review(change).approved) {
share(whatWeLearned);
}Check the outcome. Share what got you there.
From experiment to code: guides, decisions, and open examples.
An open-source foundation connecting repository structure, agent context, and deployment contracts. What to try today, and what still needs checking.
Read the articleA project post template connecting the problem, decisions, demonstration, and a question for the community.
A simple way to map friction before deciding another tool is the answer.
Five steps connecting context, a small change, verification, and a clear report.
You don’t need to know everything to belong. Just bring the urge to learn, experiment, and share what works. And what doesn’t.
Why Devex existsTests, secrets, deployment, and operations. Plan them with your agent as part of the work.
The context, the decisions, and the mistakes matter as much as the finished result.
Less noise, more thoughtful conversation. In Hebrew and English, at every experience level.
An open question, a small discovery, a work in progress. There’s a place for it here.