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I've been working on Amaru, and it's time to share where the architecture is heading. When I started this project, the initial focus was engineering execution in the age of AI agents. But as the ideas evolved, so did the scope. I realized that the underlying challenge goes beyond software engineering: how do we coordinate people, AI agents, tools, and specialized execution environments within a coherent production system? That's what Amaru is becoming: a distributed, AI-native production platform. I've just published Part 2, where I share the architecture that has emerged from this process. Some of the key architectural principles: 🔹 Intelligence is not control. Amaru Brain provides context, reasoning, and decision support, while the platform enforces execution rules, permissions, and boundaries. 🔹 Orchestration is independent of execution. Workflows and state machines coordinate production without being tied to a particular agent, machine, or environment. 🔹 Execution is distributed. Containers, Linux and Windows machines, remote workers, and specialized environments can participate in the same production process. 🔹 The ecosystem is open. Rather than reinventing every tool, Amaru aims to integrate existing providers, services, and specialized capabilities. 🔹 Deployment should be flexible. Cloud, self-hosted, and hybrid environments should share the same underlying platform concepts. One of the most important ideas behind this architecture is simple: An AI agent should not need to own the entire production process. Intelligence, orchestration, infrastructure, and execution are different responsibilities. Treating them separately makes it possible to build systems that are more scalable, observable, recoverable, and governable. This architecture is still a direction, not a finished implementation. There is plenty of engineering ahead, and I expect real-world constraints to challenge some of these decisions. That's part of the journey. 📖 Read Part 2: From Vision to Architecture — Designing a Distributed AI-Native Production Platform https://medium.com/@rluders/amaru-part-2-from-vision-to-architecture-designing-a-distributed-ai-native-production-platform-04ba1886d438… The goal isn't to build another AI assistant. It's to build the infrastructure that allows people, agents, and tools to work together at scale. Also ⭐ the project on Github: https://github.com/rluders/amaru/