Build Products and Become Unstoppable

I am a product person who happened to learn web development because I wanted to build products and startups.

That was the original reason.

I did not learn to code because I wanted to become a “developer” in the traditional sense. I learned because I wanted to be able to take an idea in my head and turn it into something real. Something people could use. Something that could maybe become a business.

But something happened along the way.

I became good enough at web development that I started trading those skills for money. And honestly, it made sense. It took me years, long hours, and a lot of frustration to develop those skills. So when people were willing to pay good money for them, it became easy to keep doing that.

I worked for startups. I learned new technologies. I built things for other people. I kept improving. I also tried to have some sort of personal life in between all of it.

But I never really took the time to use the technical skills I had built to do the thing I originally wanted to do.

Now, with AI, everything changes.

It is now possible to build products much faster than before. You can think through an idea, generate code, debug problems, build interfaces, write backend logic, create database schemas, improve copy, and ship faster than ever.

For someone like me, someone who loves product thinking and product development, that is exciting.

It means I can revisit the original reason I learned web development in the first place.

I can build products for myself.

And if they help other people too, even better.

But I do not believe in blindly vibe coding products

I do not think vibe coding a product from 0 to 1 without understanding what is happening is sustainable.

At least not if you want to build something real.

AI is incredibly powerful, but you still need to know enough to steer it. You need to understand the basics. You need to know when the code looks wrong, when the architecture is fragile, when the database design will not scale, when the auth flow is risky, when the deployment setup is a mess, or when you are creating future problems for yourself.

The good news is that you no longer need to master every technology at an expert level before you can use it. That is the big shift.

This is the path to becoming unstoppable

If you want to build products in the AI era, you need enough technical knowledge to avoid getting blocked. Not because you want to become a DevOps engineer or infrastructure expert, but because you want to move from idea to prototype, prototype to production, and production to something users can trust. The goal is to build and ship without by yourself.

A few beliefs shape this path. Use open source whenever possible, especially in the early stages when simplicity, ownership, and low costs matter most. Build products you personally care about so you can be your own first user. And learn how the pieces fit together: databases, auth, deployment, infrastructure, and applications. AI is powerful when you understand enough to guide it. This journey is not about mastering every technology. It is about becoming capable, adaptable, and hard to stop.

The learning path

This is the path I believe product builders should learn.

1. Git

Before anything else, you need to understand Git.

It is the foundation of how modern software gets built, reviewed, deployed, and maintained.

If you want to build products , you need to be comfortable with version control. You need to know how to create branches, commit changes, review history, merge work, resolve conflicts, and revert mistakes.

You should learn commits, branches, merges, rebases, pull requests, resolving conflicts, GitHub workflows, commit hygiene, .gitignore, tags, releases, rollback strategies, and working with development, staging, and production branches.

2. Postgres

You need to save your data somewhere, and Postgres is the database I would learn first.

It is open source, powerful, reliable, and used everywhere. Most serious products need structured data: users, accounts, projects, subscriptions, settings, activity logs, permissions, content, transactions, and more.

If you understand Postgres, you can build real applications with confidence.

You should learn SQL, schema design, relationships, indexes, migrations, transactions, backups, restores, connection pooling, and basic performance debugging.

3. Auth with Better Auth

Once you have data, you need users.

Authentication is one of the first things most products need. People need to sign up, log in, reset passwords, connect with OAuth, access protected routes, and sometimes belong to teams or organizations.

Better Auth is interesting because it is open source and works well with modern TypeScript apps.

The goal is to understand login, sessions, OAuth, roles, permissions, organizations, protected routes, admin access, password reset, email verification, and multi-tenant auth patterns.

4. Docker

You need a way to run your app and its services consistently.

Docker helps you package your application, database, workers, Redis, and other services in a way that works locally and in production.

You should learn Dockerfiles, Docker Compose, volumes, networks, environment variables, local development environments, production containers, logs, and service restarts.

5. Linux

If you want to self-host or understand production environments, you need Linux basics.

You do not need to become a full-time sysadmin, but you should not be scared of a server.

You should understand SSH, users, permissions, firewalls, processes, logs, systemd, disk usage, environment variables, package installation, and basic networking.

This gives you confidence when something breaks.

6. Self-hosting with Coolify

Self-hosting is powerful because it gives you independence.

With a VPS and a tool like Coolify, you can deploy multiple apps, databases, workers, and services without creating a new paid platform account every time you have an idea.

Coolify makes self-hosting much more approachable.

You should learn how to deploy apps, host databases, manage services, configure SSL, manage environment variables, create staging environments, connect domains, set up Git-based deployments, and monitor server resources.

7. Backups and restores

This is not optional.

If you are storing data, you need to know how to back it up and restore it.

You should learn Postgres backups, database restores, volume backups, off-site backups, automated schedules, restore testing, backup retention, and disaster recovery basics.

If you want to build real products, you need to protect the data.

8. CI/CD

Once you can deploy manually, you should learn how to automate it.

CI/CD gives you a repeatable way to ship updates without relying on manual steps every time.

You should learn GitHub Actions, automated tests, automated deployments, build checks, migrations during deploy, environment-specific workflows, rollback basics, preview deployments, and secrets management.

This is how you start making your workflow feel professional.

9. AWS and S3

Most products eventually need file storage.

Images, PDFs, avatars, invoices, exports, generated files, documents, backups, and user uploads all need to live somewhere.

S3 is one of the most important cloud concepts to understand. Even if you use an S3-compatible service, the knowledge transfers.

You should learn buckets, file uploads, signed URLs, IAM basics, permissions, backups, lifecycle rules, private versus public files, CORS for uploads, CDN integration, and basic CloudWatch concepts.

10. Cloudflare

Once your app is online, you need to understand how traffic reaches it and how to protect it.

Cloudflare is useful for DNS, SSL, proxying, WAF rules, rate limiting, caching, bot protection, redirects, subdomains, and protecting private areas with Cloudflare Access.

This helps you understand the layer between your users and your server.

Your product is not just your code. It is also the path users take to reach it.

11. Background jobs and queues

Not everything should happen inside a user request.

Real products need to send emails, process files, call AI APIs, import data, handle webhooks, generate PDFs, retry failed tasks, and run scheduled jobs.

That is where background jobs and queues come in.

You should learn Redis, BullMQ, Inngest, Trigger.dev, scheduled jobs, webhooks, emails, AI tasks, file processing, retries, failures, dead-letter queues, and job dashboards.

This is especially important for AI products because many AI tasks are slow, asynchronous, and unreliable by nature.

12. Observability

Once your product is running, you need to know what is happening.

You need to know when something breaks, why it broke, who was affected, and whether it is still happening.

Observability gives you visibility into production.

You should learn error tracking, logs, metrics, traces, uptime monitoring, alerts, health checks, performance monitoring, request tracing, and database query monitoring.

This is what allows you to debug real products instead of guessing.

13. Security basics

You need to understand security basics because every product has risk.

You do not need to become a security expert before launching, but you do need good defaults.

You should learn secrets management, HTTPS, SSH keys, firewalls, least privilege, SQL injection, XSS, CSRF, CORS, rate limiting, secure file uploads, dependency scanning, admin route protection, and audit logs.

Security is not one feature you add at the end.

It is a way of building.

14. AWS fundamentals

You do not need to learn all of AWS first.

AWS is huge, and starting there can be overwhelming. But once you understand the fundamentals of apps, databases, Docker, Linux, storage, networking, and deployment, AWS becomes easier to understand.

You should learn IAM, S3, CloudWatch, Lambda, ECS or Fargate, RDS, Route 53, VPC basics, security groups, and billing alerts.

This gives you enough knowledge to understand the bigger cloud primitives when your products need them.

15. Next.js

Next.js is the product layer where all of this comes together.

For me, this is already familiar territory. But throughout the journey, Next.js remains the place where the product gets built.

You use it for UI, routing, server actions, API routes, full-stack app structure, deployment patterns, caching, middleware, forms, data fetching, and performance optimization.

Next.js is where the product becomes real.

The outcome

The outcome of this journey is not to become an expert in every technology. AI gives us leverage, but leverage is only useful if you know where to apply it. This learning path is about building the foundation, becoming the kind of person who can build products from zero to production, and becoming harder to stop.