Why Validation Matters for Non-Developers
As a technical writer using AI to generate code snippets, you don’t need to be a developer to ensure accuracy. The validation step is where you catch errors before they reach your documentation. By integrating simple, automatable checks into your workflow, you can verify AI-generated code with confidence—without writing a single script yourself.
Use Language-Specific Linters and Formatters
Start with tools that work out of the box. For JavaScript, configure ESLint with a basic rule set—many online linters are available for instant checks. For compiled languages like Java, run a simple javac command on a stripped-down class to test compilation. Document any errors you find, then return to your AI prompt (as covered in Chapter 5 of my e-book) and ask: “Fix the syntax error in line X.” This iterative feedback loop sharpens your AI’s output over time.
Sandbox and API Conformance Checks
Paste each snippet into a relevant online sandbox (e.g., JSFiddle for JavaScript, Replit for Python). Next, combine your snippet and your OpenAPI spec in a single prompt to verify API conformance. This tells you whether the generated code matches your actual API endpoints, parameters, and response shapes—critical for accurate documentation.
Critical Safety Rule
Never use production keys or real data in these tests. Always rely on the platform’s test credentials and sandbox environments. One mistake with a live API key can corrupt data or incur charges.
Actionable Checklist for Automated Checks
Integrate these steps into your daily workflow. Each action takes under two minutes:
- ☐ Run a language-specific linter/formatter locally or via a simple script (e.g., ESLint for JS).
- ☐ For compiled languages (e.g., Java), use a
javaccommand on a stripped-down class file. - ☐ Paste each snippet into an online sandbox and execute it.
- ☐ Prompt the AI with your OpenAPI spec: “Validate this snippet against my API spec.”
- ☐ Note any errors and return to your AI prompt with a correction request (e.g., “Fix the syntax error in line X.”).
Example: Spotting a Mismatch
Suppose your AI generates a JavaScript snippet with an endpoint path /api/v1/users, but your OpenAPI spec defines /api/v2/users. A linter won’t catch this—only a conformance prompt will. By combining the code with your spec in a single question, you force the AI to cross-reference the two. If it flags a mismatch, you have a concrete error to fix.
These validation techniques let you test AI-generated code like a developer—without writing any code yourself. Each step is simple, repeatable, and designed for non-developers who need accurate technical documentation.
For a comprehensive guide with detailed workflows, templates, and additional strategies, see my e-book: AI for Freelance Technical Writers (API/SaaS): How to Automate Code Snippet Generation and Documentation Updates.