How We Built a High-Performance Telegram Engine and Scaled to 1,100+ Users Organically
Source: Dev.to
The Problem: The “Latency Tax”
Most existing Telegram tools are built on top of inefficient request handlers. While they work for the majority of cases, power users often experience delays that can break a business model. We wanted to eliminate this “latency tax” by optimizing how we interact with the MTProto protocol.
Our Approach: Performance Over Fluff
We are a small team based in Dnipro, Ukraine. Instead of spending months on a fancy UI, we focused 100 % on the core engine—building a tool we would actually want to use.
Key Technical Focuses
- Concurrency – Managing thousands of requests without hitting local CPU bottlenecks.
- Rate‑Limit Navigation – Finding the sweet spot between maximum speed and Telegram’s API constraints.
- Reliability – Ensuring the engine stays stable during peak market volatility.
Scaling to 1,100+ Users with $0 Marketing
We didn’t have a marketing budget, so we chose a “developer‑to‑developer” path: sharing technical milestones, discussing bottlenecks openly, and inviting people to try the engine. The result was over 1,100 active users joining our community purely through word‑of‑mouth and technical discussions on developer forums.
Building in Public
We believe in transparency. Our team—myself @fuckobj and deputy lead @Who_realerr—continually iterates based on community feedback.
If you are a developer working within the Telegram ecosystem, we’d love to hear your thoughts on optimization and feature ideas for a high‑speed automation engine.