Developer Guide Insists You Define The Problem First. Obviously. The Fact This Needs Stating Is Concerning.
A developer guide from CodeStore Solutions lays out prerequisites for building AI agents, starting with a clear problem definition that specifies what the agent should do, its scope, and what counts as success. The guide warns that missing even one foundational component makes the process significantly harder. Vague goals, it states plainly, lead to failed agents.
The principle here is problem framing as a constraint on system design. The mechanism is scope reduction. A tightly defined problem eliminates most architectural decisions before you make them. Students always want to start with the model. You start with the question. Everything downstream, from tool selection to evaluation metrics, flows from that initial definition. Skip it and you are debugging philosophy, not code.
CodeStore Solutions, a mobile and web app development resource, published the guide targeting developers building AI agents. No specific authors, companies, or quantitative results are cited in the source material.
- Open a blank document and write one sentence describing what your agent should do. If you cannot do this in one sentence, your scope is too broad. Narrow it until you can.
- Below that sentence, write three bullet points defining what counts as success. Be specific. "Saves time" is not a metric. "Reduces email drafting from 20 minutes to 5" is.
- Take any consumer AI assistant like ChatGPT or Claude and give it your one-sentence problem and three success criteria. Ask it to propose a simple agent design. You should receive a concrete workflow you can evaluate against your own criteria.