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Three agent-engineering interview questions, and the modern way to scale to thousands of agents

Agents & MCP◆ Advanced@danialhasan.mcpsaved JUL 13

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Yes. The core insight, favoring generic agent personas with behavior composed from layered, individually evaluable skills over rigid role personas, is a sound and safe architectural best practice that matches the current direction of skill-based tooling. This is general agent-engineering guidance rather than a change to any one project, and it is most useful when designing multi-agent systems.

✦ Walkthrough+10 xp / step

Key takeaways on building and scaling agent systems:
Evaluate agents deliberately. For a few agents, use environment-based evals and reinforcement-learning tooling (the video names Prime Intellect). For thousands of agents, build a dedicated agent system whose job is to evaluate the other agents.
Design for scale from the start. Plan how the components tie together to serve millions of users, then use coding agents (the video names Codex and Claude Code) to build the system step by step and evaluate each stage.
Scale agent management with composable skills, not rigid personas. The older pattern gave each agent a fixed persona such as reviewer, auditor, or implementer. The modern pattern keeps personas generic (explorer, reviewer, worker) and packages the actual work into skills that layer on top of each other to compose behavior. This makes both the individual skills and the agents easier to evaluate, and lets the system scale to thousands of agents.

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I am designing a multi-agent setup. Help me apply the composable-skills pattern: keep each agent's persona generic (explorer, reviewer, worker) and package the actual work into small, individually testable skills that layer together to compose each agent's behavior. Propose how to structure the skills, how to evaluate each skill in isolation, and how this approach would let the system scale from a few agents to many without rewriting personas.

Three agent-engineering interview questions, and the modern way to scale to thousands of agents

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