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  • React
  • Angular
  • Vue
  • Svelte
  • NextJS
  • Redux
  • Apollo
  • Storybook
  • D3
  • Testing Library
  • JavaScript
  • TypeScript
  • Node.js
  • Deno
  • Rust
  • Python
  • GraphQL

How To Build An AI Therapist Mobile App With Bolt, UX Pilot and Expo

Did you know that THE most common use case for ChatGPT —and LLMs in general—in 2025 is for therapy and companionship? (Yes, they have them linked as one category). I’m not making this stuff up or picking it from a random dude on X / Twitter . It’s from Harvard Business Review .
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Synthetic Data Generation with Prompt Engineering

In our previous article, we talked about the role of synthetic data in QA testing, and looked at two QA methodologies: Equivalence Class Partitioning and Boundary Value Analysis. Today, we’re going to talk about how you can use LLMs to generate test data for your applications. If you haven’t read it yet, I recommend taking a look at our articles on prompt engineering for traditional and reasoning models, as we’re going to be using prompts to generate test data. As we’ve discussed before, there are many reasons to use synthetic data in your testing - one of the largest being the cost and scalability, but it may also be required as an alternative to production data in the event that it contains personally identifiable information (illegal to use in most of the world).
Thumbnail Image of Tutorial Synthetic Data Generation with Prompt Engineering