Will JSON help with clearer prompting? A recruiter's perspective

Using JSON when creating prompts for AI models like ChatGPT is becoming popular, and for good reason. JSON (JavaScript Object Notation) is a lightweight, human-readable way to structure data using key-value pairs. Instead of writing a big block of text, you can divide your prompt into clear sections. For example, you might have keys for “background”, “task”, “requirements”, and “tone”.

One of the biggest advantages of using JSON in prompting is clarity. When you break your instructions into structured fields, the AI is less likely to miss important details. For recruiters, this can be a game-changer when drafting prompts to write job ads, candidate summaries, or interview questions. Instead of feeding in a messy text like “Write an advert for a senior developer role in a friendly but professional style with these bullet points”, you can specify in JSON exactly what you want in each section. This helps ensure the output hits the brief consistently.

Another benefit is consistency across teams. If your recruitment firm uses AI tools to draft communications, JSON templates can standardise inputs. Everyone in the team can fill out the same structured fields, which reduces variation in quality. It also makes it easier to automate the process, since many tools and systems work well with JSON.

JSON also shines when using more advanced AI features. Some AI providers offer structured API calls where you send your prompt as JSON and get back JSON-formatted results. This enables integration with your CRM or ATS systems. Imagine automatically drafting personalised outreach messages at scale, all while keeping control over the inputs.

However, there are some downsides to consider. Not everyone finds JSON intuitive, especially if they are less technical. Even though it is relatively simple, errors in formatting (like missing commas or braces) can cause the AI to reject the input or misinterpret it. For teams without technical support, there can be a learning curve.

Another limitation is that AI models do not always respect the structure perfectly. Even if you use JSON, the model might sometimes ignore your categories or blend them together if the instructions are not clear enough. This can frustrate users who expect machine-like precision.

In a recruitment context, the benefit of structured prompts is that they reduce the risk of critical details being lost, like required certifications or role responsibilities. They also help recruiters work faster by making sure inputs are ready for automation or integration. On the other hand, they can add a bit of overhead in training staff and setting up templates.

In short, using JSON for AI prompting offers recruiters a way to be clearer, more consistent, and more automation-ready. But it is not a silver bullet. It works best when paired with good prompt design and clear expectations about what AI can deliver. For firms willing to invest in some setup and training, it can improve quality and productivity significantly.