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I didn’t start my developer journey by building engineering software.
I started with trading bots.
At first, I was fascinated by the idea that software could take a strategy, process data, make decisions, and execute actions automatically.
So I started building.
Trading bots.
Custom indicators.
Automated alerts.
Telegram integrations.
Trade journals and analytics tools.
That was where I began learning how to turn an idea into a working system.
Then something changed.
I started building products beyond trading.
I worked on tools like:
→ Kleroge — a real estate marketplace
→ Faishonix — an AI-powered fashion technology product
→ Revenue audit tools for fintech companies
→ Various AI-powered internal tools and automation systems
And eventually, I found myself building something completely different.
A heat exchanger software.
ROSIF-HEX.
What started from my final-year chemical engineering research became a standalone engineering application for simulating and optimizing shell-and-tube heat exchangers.
Python.
Thermodynamics.
Heat transfer.
Fluid mechanics.
Optimization.
Numerical methods.
Software engineering.
This was a different level of problem.
I wasn't just building a UI around an idea.
I was translating engineering principles, mathematical models, and optimization logic into software that engineers can actually use.
That journey has taught me something important:
Being a developer isn't just about knowing how to code.
It's about being able to look at a problem in any domain and figure out how software can solve it.
I take ideas from:
Problem → Concept → System → Product.
Trading bots were where I started.
Engineering software is where the journey has taken me so far.
And I'm still building.
The next chapter should be interesting.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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An AI engineer should make the path from input to output inspectable. In Tenderseal, I shaped an AI-assisted workflow where users READ source material, ASK focused questions, and DRAFT a response while keeping the underlying material close to the work. I build with approvals around consequential actions, read-back after integrations, and a clear boundary between model output and human judgment. If your AI feature needs a dependable workflow, message me.
Great Design :)