Building Lowwin with Codex: Lessons from a Telegram Mini App

Biruk — Wed, 21 Oct 2026 10:15:53 +0000

I'm an independent developer from Ethiopia, and one of the projects I've been building is Lowwin, a mobile-first Telegram Mini App for auctions.

This project has been a practical way for me to explore how AI-assisted development can support real product building. I already have experience with Mini App development, so my workflow is not just “ask AI to make an app.” Instead, I combine my own product and engineering knowledge with ChatGPT Pro and Codex to move from idea to implementation, then testing and iteration.

In this post, I want to share how I’ve been using Codex while building Lowwin, what has been useful, and what I’ve learned from the process.

Note: Lowwin is still an active development project. The screenshots and examples here are development previews.

What is Lowwin?

Lowwin is a Telegram Mini App auction platform designed with a mobile-first experience.

The goal is to create a smooth interface where users can:

Browse auction items
View auction details
Place bids
Navigate a simple mobile-friendly experience inside Telegram

Some of the current UI areas include:

A homepage with featured auction items
Auction listing screens
Item detail pages
User-focused navigation for bids, alerts, favorites, deposit, and profile

My workflow: ChatGPT Pro + Codex + my own development knowledge

The most useful workflow for me has been a combination of:

Thinking through the feature or problem
Using ChatGPT Pro to improve and structure prompts
Using Codex to implement, refine, and test
Reviewing the output as a developer
Repeating until the result is good

This is important because AI works best when the developer gives it:

Clear context
Clear goals
Expected behavior
Constraints
A way to verify the output

I don’t treat Codex like a magic button. I treat it like a very powerful development assistant.

What Codex helped me with

Codex helped me across the Lowwin project from start to end in different ways.

That includes:

Translating feature ideas into implementation steps
Generating and refining interface code
Improving structure and consistency
Helping with testing-related thinking
Speeding up repetitive development work
Making it easier to move from concept to working UI

A big part of my process was using ChatGPT Pro to prepare better prompts, then using those prompts to guide Codex more effectively.

That made a big difference.

Instead of writing vague requests, I could be more specific about:

What screen I wanted
How the behavior should work
What should be improved
What needed to be tested
What constraints to preserve

Example: building a real product, not just a demo

One thing I value in AI-assisted development is that it should help build real software, not just attractive demos.

While working on Lowwin, I’ve been focused on building something that feels like a real product:

Mobile-friendly
Clear navigation
Consistent layout
Usable screens
A product flow that makes sense inside a Telegram Mini App

That means checking more than just “does the code run?”

It also means asking:

Does this screen make sense for users?
Is navigation clear?
Does the interface feel consistent?
Does the feature behave the way I intended?
Can I build on top of this later?

Codex helps a lot, but I still need to make the product decisions.

Screenshot preview

Lowwin homepage

This screen presents the main brand, featured products, and core navigation.

Auction detail screen

This view shows the product, auction information, and bidding entry point.

Auction listing screen

This screen helps users browse available auctions and quickly take action.

What I learned

1. AI is most useful when you already understand what you're building

Because I already have experience with Mini App development, I can guide the process better.

That makes AI more effective.

2. Good prompting matters

A better prompt gives better output. For me, ChatGPT Pro has been useful for shaping prompts before sending them into Codex.

3. Codex speeds up development, but review is still necessary

Codex can accelerate implementation, but I still review structure, logic, UX, and output quality.

4. Building is iterative

The real value is not a one-shot response. It’s the cycle of:
idea → prompt → implementation → review → test → improve

Why this matters to me

As a developer from Ethiopia, I’m especially interested in showing that AI tools like Codex can help builders create real products, not just experiments.

I want to share more practical examples from my own work, especially for:

Ethiopian developers
Independent builders
People building Telegram Mini Apps
Developers learning how to use AI tools productively

For me, the exciting part is not just using AI — it’s using AI to build things that are actually useful.

Final thoughts

Lowwin has been a good example of how I like to work with AI.

I bring the direction, product understanding, and development experience.

ChatGPT Pro helps me think more clearly and improve prompts.

Codex helps me build faster, refine ideas, and move toward working software.

That combination has been powerful for me, and I’m excited to keep sharing what I learn.

If you're also building with Codex, I’d love to hear how you use it in your workflow.

AI disclosure: I used AI tools to help refine my workflow, organize ideas, and support the writing and development process described in this article.

DEV Community: Biruk