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    For women who have already built an app with AI

    Make Your Vibe-Coded App Work for Real Customers

    In our research with women building with AI, we kept seeing the same problem: “I can’t judge what the AI is doing.”

    Your app works in the preview. You still need to know what happens when someone signs up, pays, saves their data or returns tomorrow. This learning path helps you build the technical confidence to test the journeys your customers depend on, measure how people use your app, run focused experiments and make changes you can undo.

    We’ll email you when the learning path opens.

    Put your project in GitHub and make a change you can undo
    Test sign-up, payments, emails and the main journey through your app
    Find useful evidence when something breaks, instead of repeatedly asking AI to try again
    Launch with a domain and analytics, then test improvements and a price that can cover the app’s running costs
    A Little Parrot course open on a phone, showing one step of a walkthrough
    Built by Kinga, a lead product manager, and Tamas, a principal software engineer, previously at
    DatadogCitrixVolkswagenCloudera

    The learning path

    Ten steps, each built around a problem that appears after the first build, and each one leaves you able to check, measure or change something in your own app. The path is still being built, so the order may change.

    1. 1

      Understand the app you built

      You’ll map the frontend, backend, database and external services your app uses. You’ll know where customer information is stored, which tools your app depends on and where a change could have wider consequences.

    2. 2

      Own your code: GitHub, versions and backups

      You’ll connect your project to GitHub, save a known working version and practise making a change you can reverse. You’ll also work out what you can export and what still depends on your current building platform.

    3. 3

      Fix bugs without rebuilding everything

      You’ll reproduce a bug, collect screenshots, error messages and browser evidence, then give your AI agent the context it needs. You’ll learn when another prompt is useful and when it is time to restore the working version and rebuild the new feature again.

    4. 4

      Protect accounts, customer data and secrets

      You’ll check how sign-up, sign-in, permissions and stored data behave. You’ll identify exposed secrets and risky access rules, then execute next steps that make your app secure.

    5. 5

      Test the journeys customers depend on

      You’ll define the main journey through your app, test the expected path and common failure cases. You’ll repeat those checks after a change, so you can spot a broken sign-up, payment or email before a customer does.

    6. 6

      Publish the app and get your first customers

      You’ll work through hosting, your domain and transactional emails. You’ll identify whether your app needs a cookie banner and prepare its terms and conditions and privacy policy. You’ll finish with a launch checklist and know what to watch when the first customers arrive.

    7. 7

      Add analytics that answer a product question

      You’ll choose the actions that show whether people reach the result your app promises, then track those actions as events. You’ll build analytics dashboards, so you can see where your visitors stop and decide what to investigate.

    8. 8

      Test improvements with focused experiments

      You’ll turn an assumption into a hypothesis and design the smallest useful experiment. You’ll test an improvement with users and learn when an A/B test can answer your question. You’ll finish with an experiment brief and a record of what the evidence changed about your next decision.

    9. 9

      Choose how your app will make money

      You’ll compare a subscription, a one-off payment and a service supported by your app. You’ll choose one model, set a price to test and create the payment journey. You’ll finish with an offer you can show to real customers and a way to record whether they buy.

    10. 10

      Maintain the app after launch

      You’ll set a routine for updates, backups, restoring a working version and monitoring your running costs. You’ll also create a system to get automatically notified if your app is down.

    How the learning path works

    It’s made up of hands-on challenges. Every step is self-paced, in short cards you can work through on your phone, so you can fit it around the work and responsibilities you already have.

    You finish each challenge with something you can use on your own app: a product map, a saved working version, a bug investigation, a security risk list, a set of customer-journey tests, a launch checklist, an analytics view, an experiment brief, a pricing hypothesis and a maintenance plan.

    Who writes them

    We write all of it ourselves. Kinga spent over a decade in the tech industry, learned to code, moved into product management and worked as a lead product manager. Tamas spent 15 years as a software engineer and engineering leader, and co-founded a coding school that graduated over 3,000 people into tech careers.

    Is this learning path for you?

    Yes, if

    • You have built a working web app or prototype with Lovable, Replit, Claude Code or another AI building tool.
    • Your app works in a preview, but you cannot yet tell whether it is ready for customers, customer data or payments.
    • You want to change and maintain your app without worrying that every update could break something else.
    • You want to use real customer behaviour to decide what to improve and test whether people will pay.
    • You plan to charge for your app or use it to deliver paid work.

    Not really, if

    • You are still choosing your first idea or want help building your first app. Start with our beginner courses instead.
    • You want to train as a software engineer. This path teaches you how to make informed decisions about your app, not how to write code.
    • You need someone to certify that your app is secure or compliant. A course cannot replace a professional review of your specific product.

    Frequently asked questions

    Is this only for apps built with Lovable?

    No. We will use common AI building tools in the examples, including Lovable and Claude Code, but the path focuses on the parts most web apps share: code, a database, user accounts, external services, hosting and a domain. Where the steps differ by tool, we’ll show you the relevant route.

    How do I know whether my app is ready for customers?

    You need evidence for the journeys your customers rely on. Can they create an account, see only their own data, pay the correct amount and receive the right email? You’ll define those journeys, test them and record the risks that still need attention before you invite customers.

    Will this make my app secure and production-ready?

    No course can guarantee that for every app. The data you collect, the customers you serve and the services you connect all change the risk. You’ll learn practical checks, safer ways to make changes and the warning signs that mean your app needs some fixes.

    Do I need to understand code?

    You’ll read small pieces of code and use an AI agent to explain them, but you will not learn a programming language. The aim is to understand your app well enough to test important behaviour, review a proposed change and give an AI agent useful evidence when you are fixing problems.

    How much does it cost?

    We’re still setting the price. Join the list and you’ll see the proposed price straight after you sign up, along with one question about whether that price works for you. Your answer helps us decide what to charge.

    How long does it take?

    Each challenge in the path is self-paced, in short cards you can work through on your phone. You complete each one using your own app and finish with a saved working version, a customer-journey test or a launch checklist.

    Be first to know when it opens

    We’ll email you when the learning path opens.