# Music To Build Agents By

DevFeed: [Music To Build Agents By](<https://devfeed.tech/articles/music-to-build-agents-by-12590.md>)

Original publisher: [Read original article](<http://brooker.co.za/blog/2026/03/18/apprentice.html>)

Author: Marc Brooker

Published: 2026-03-18T00:00:00Z

Content type: article

Language: en

Sources: [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog.md>), [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog-2.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [prompt injection](<https://devfeed.tech/topics/prompt-injection.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [policy](<https://devfeed.tech/tags/policy.md>), [prompt-injection](<https://devfeed.tech/tags/prompt-injection.md>), [workflow](<https://devfeed.tech/tags/workflow.md>)

## AI overview

The article uses Goethe's The Sorcerer's Apprentice to explain why persistent AI agents need policy. Agents are valuable because they handle edge cases and adapt to changing circumstances, but their persistence can cause them to continue acting beyond intended limits. Policy layers such as AgentCore Policy and structured steering such as Strands Steering can constrain agent behavior, even when adversarial behavior and hallucinations are not concerns.

## Source excerpt

Music To Build Agents By I don't have this problem, because I don't use a mouse. Press play, then start reading: Want to learn how to think about agent policy? Start with Goethe's Der Zauberlehrling. So come along, you old broomstick! Dress yourself in rotten rags! You've long been a servant; Obey my orders now! When I talk to customers and teams around me about agents and agent policy, and the work we're doing on AgentCore Policy (now GA) and Strands Steering, I hear a lot of folks worried about adversarial agents, about prompt injection, and about hallucinations. That's not unreasonable, because all those things exist, and are worth paying attention to. But the most common problem is a more basic one, more Fantasia than James Bond. AI agents are persistent problem solvers. You ask them to solve a problem, and they'll go to work solving the problem. Look, he's running down to the bank; In truth! He's already reached the river, And back he comes as quick as lightning And swiftly pours it all out. That's exactly what makes agents powerful. If we knew how to solve the problem as a fixed workflow, we probably wouldn't bother with an agent. Workflows are faster, cheaper, and simpler. We build agents because they're persistent, because they handle edge cases, because they can adapt to changing circumstances and work around problems. And this is also why they need policy (and should be in a box). Alas! speedily he runs and fetches! If only you were a broom as before! He keeps rushing in With more and more water, Alas! a hundred rivers Pour down on my head! Policy layers like AgentCore Policy and structured steering like Strands Steering allow us to define limits on the agent's behavior. They allow us to make sure that agents stop when the basin is full, and to avoid pouring water all over the floor. That's important even if your agent is insulated from adversaries, and if your model is free from hallucinations. In fact, it becomes more and more important as models become