More people are turning to AI to write code, and more of them are getting stuck on answers that miss the mark. A tutorial from the Juejin community delivers a plain read we agree with: the problem isn't the AI — it's that your prompts are too vague.
What this is
A beginner-oriented practical tutorial that delivers four ready-to-use prompt templates (a "prompt" being the structured format you fill in when asking AI for help), each handling one task: explaining code you can't read, generating simple functions, debugging errors, and optimizing existing code.
The core isn't tricks — it's structure. The article draws a sharp contrast, and we think it lands: just say "write me a price-calculation function," and the AI has no way to know your discount rules, currency unit, or error-handling expectations. Spell out the inputs, outputs, and rules, and the AI returns code you can actually verify. Every template hammers the same point — describe the problem clearly, then let the AI answer.
Industry view
Supporters argue that as Cursor (an AI coding editor) and GitHub Copilot (an AI code-completion tool) enter ordinary office workflows, "how to ask AI for what you need" is becoming as basic a literacy as "how to write an email." The templates in the tutorial, in essence, turn structured-expression training into a fill-in-the-blank exercise.
But we think the dissenting views are worth flagging. First, templates solve the "how to ask" problem — if a user hasn't even clarified what problem they're trying to solve, no template will rescue them. Second, over-templatization turns questioning mechanical, leaving users paralyzed when facing atypical problems. Third, the real skill these templates drill is structured thinking, which travels fine without AI — it's not an AI skill, it's a general-purpose expression skill.
Impact on regular people
For enterprise IT: ship the templates as internal training material to lower the barrier for non-programmers using AI coding tools — but note clearly that knowing the template isn't the same as judging whether the code is fit for use.
For individual professionals: even if you never write code, the ability to "describe a problem clearly" applies to everyone who uses AI — drafting reports, building slides, analyzing data — it's all the same underlying skill.
For the consumer market: the AI tool race may shift from "whose model is stronger" to "who can teach users how to use it." Prompt templates are the front line of that education war.