Notes from the workshop

Telegram offers developers a fast path to distribution, but durable products depend on disciplined infrastructure. This guide covers the practical patterns that matter most when building bots, Mini Apps, and backend services that need to stay responsive, observable, and safe under real-world load.

Telegram bots are often used for announcements and automation, but they can also power a fast, private support-escalation workflow. This article covers practical Bot API patterns for turning inbound messages into structured, low-friction help requests without overwhelming your team or leaking user data.

Telegram bots that connect to AI models can be powerful, but they also create a new attack surface: untrusted chat content can manipulate prompts, trigger unsafe tool calls, or leak private data. This article outlines practical defenses Telegram developers can implement to keep AI features useful without exposing users or internal systems.

Telegram-style systems are dominated by hot-path work: fanout, encryption, storage lookups, and cross-region replication. This tutorial shows how to improve throughput and tail latency by tightening the delivery path, reducing synchronous dependencies, and measuring the right bottlenecks.

A Hacker News discussion highlighted an interactive site that shows Los Angeles growing building by building from 1880 through 2026. For developers and Telegram builders, the project is a reminder of how data visualization can turn long-running urban change into a fast, explorable interface.

As Telegram communities adopt multiple AI bots for support, search, onboarding, and automation, moderation gets harder in ways that basic spam filters do not cover. This guide shows Telegram developers how to design moderation flows, permission models, and audit signals for a safer multi-bot experience.

Telegram developers do best when the opportunity is concrete: a bot, mini app, moderation tool, or automation workflow that solves an actual user problem. This guide shows how to scope the work, choose the right architecture, and turn a small Telegram integration into a durable product opportunity.

Telegram bots are often judged on features, but security is where developer opportunities really open up. This comparison looks at the main security tradeoffs in Telegram bot design and shows where developers can build better tools, better defaults, and better defenses.

Phil Schiller’s departure from App Store leadership was reportedly influenced by reservations about new CEO John Ternus’ push for more recurring revenue from the App Store. The report matters for developers and Telegram ecosystem watchers because it points to possible shifts in how Apple may monetize its platform.

Telegram is more than a chat app: it is a platform with clear entry points for bots, mini apps, authentication, notifications, and community automation. This tutorial walks through the infrastructure choices that matter when you build something real on Telegram, with an eye toward reliability, scaling, and product opportunity.

Telegram’s Bot API keeps moving toward richer, more stateful interactions, and the latest development is another sign that bots are becoming first-class app surfaces rather than simple command handlers. For developers, the practical question is no longer whether to adopt these changes, but how quickly to redesign bot flows around them.

A recent wave of Telegram-themed OAuth phishing has changed the threat model for bot developers: attackers are no longer trying only to steal bot tokens, but to hijack admin sessions, impersonate support flows, and pivot through connected web apps. This explainer breaks down what changed, why it matters, and the concrete controls Telegram developers should implement now.