Before I start, let me start: without a doubt, children should be children and enjoy their childhood.

However, many makers here already have families, and the role of founders also affects how their children perceive them (they probably see their parents as role models).

The last 2 or 3 years, I have been trying to learn more foreign languages besides English.
My go-to app is (not surprisingly) Duolingo.

I have also experience with Memrise, but it didn't feel like a good fit.

I find these apps to help learn vocabulary or for keeping up with a language I've previously learned in other ways (for example, from a language school or online lessons), but not necessarily for learning at a conversational level.

A few years ago, AI at work meant smarter autocomplete or a chatbot on your website.

Now, I m seeing something different.

Companies are experimenting with AI agents as teammates - not just tools. They schedule meetings, file reports, analyze data, and even handle parts of customer support.

I'm 4 years into entrepreneurship, and Impostor Syndrome has become a part of daily life.

That's the bad news. The good news is that I've kind of become numb to it.

Recently I've worked with a group of non-corders trying to "vibe code" their apps with AI.
While knowing code is clearly not a must these days, it helps to get technical.
People who were familiar with basic software engineering concepts were 10x more likely to success and get better results.
So, with the hope of providing value to the non-coders people, I've created a quick roadmap for the basic terms and concepts you should be familiar with.

• Requirements: Building apps with AI is all about being able to clearly guide AI and express your app features and requirements.
  You need to be able to express those ideas and explain them as you d explain to a human developer. Think like a Technical Product Manager.

• Frontend: The face of your app.
  It's what your users see and interact with. It could be a website, a mobile app, or a desktop app. Most popular frontend libraries and frameworks are React, Next.js.

• UIs: They are the buttons, the forms, the modals, the tooltips, etc. In React, the UI is built with components. For design & styling, Tailwind CSS is the most popular library.
  For animations, Framer Motion is the most popular library.

• Packages & npm: Apps are not built from scratch.
  They are built on top of existing libraries and frameworks, like lego blocks.

  The most popular package manager is npm. For example, "react-hook-form" is a famous package that helps you build forms.

• Backend: The backend is the part of your app that runs on the server.

  It's where you store your data, your business logic.

  e.g: If you want to send an email, or process payments - this is where you'll do it.

  Vibe tip: Use minimal backends with serverless functions.

• Database: The database is where you store your data.

  It's where you store your users, your projects, your tasks, etc. Think of it as a big spreadsheet.

  I recommend using a database that is integrated with your frontend.

  For example: Fine, or Supabase.

• API: Real-life apps almost always need to integrate with other apps.

  For example: if you want to send email, or get weather data, or integrate with AI - it's all done through APIs.

• Hosting & Deployment: For your app to be accessible to the public, you need to host it.

  The code is usually hosted on GitHub, and deployed to platforms like Fine, Vercel, Netlify.

Finally, being comfortable with code is helpful - even if not a must.

AI often makes minor mistakes (like importing a wrong package), and if you re not afraid of reviewing code - you will get better results faster.

Each of us leaves a digital footprint on the internet. The only difference is how much data and information we share publicly about ourselves.

For example, my local friend doesn't use his photo or name on his profiles so that no one will associate him too much with his income or political ideology.

LinkedIn officially shared the job titles that started appearing more often, and with the rise of AI, the market is restructuring.

The actual top 10 roles that have seen the biggest rise in listings (in the U.S.) are:

1. AI engineers Engineers developing and implementing AI models that perform complex tasks

2. AI consultants and strategists - Helping organisations plan and implement AI technologies to improve operations

3. New home sales specialists Which sounds like a rebranding or real estate agent

4. Data annotators Labelling and reviewing data for AI projects

5. AI/ML researchers Designing new AI models and systems

6. Healthcare reimbursement specialists Ensuring healthcare providers are getting correct and timely payments

7. Strategic advisors and independent consultants Which seems like a pretty broad-ranging segment

8. Advertising sales specialists You re reading a marketing blog, I assume you know this one

9. Founders Not sure this can be listed as a job title in itself, but LinkedIn s keen to highlight how people are shifting to their own businesses

10. Sales executives

Just wanted to say a quick thank you to everyone who checked out Cue today.

I launched this morning not expecting much. It's a tool I built over the holidays that turned from a side project into the main project I'm working on. Seeing it hit #3 (so far) is honestly surreal.