The Simplest-Approach Principle for Solution Design

Prefer the Simplest Approach That Solves the Problem

Anthropic's *Building Effective AI Agents* guidance carries a lesson that applies even to non-developers designing a solution around Claude: prefer the simplest approach that solves the problem. Many tasks are handled well by a single well-structured prompt or a short chain of prompts -- an elaborate multi-step "system" is often unnecessary.

Why Simplicity Wins

Added complexity adds failure points. Each extra step, handoff, or piece of tooling in a solution is another place where something can go wrong, another thing to maintain, and another thing to explain to stakeholders. If a single prompt or Project already solves the problem reliably, a more elaborate design is a cost without a corresponding benefit.

Applying the Principle

Before designing an elaborate solution, an associate should ask: does a well-structured prompt, or a short sequence of prompts, already solve this? Escalate to a more complex structure only when the simple version demonstrably falls short -- not by default.

Common exam traps

• Over-engineering a solution when a simple prompt or Project would do -- the exam frames this explicitly as adding complexity (and failure points) without added benefit.
• Assuming "more sophisticated" (multi-step, multi-tool) is automatically "better" -- the correct default is the simplest structure that solves the problem, escalating only when needed.