Telegram Reviews

1. Flawlessflower

   almost 3 years ago
   the best messanger sp far for me

   Very secure, straightforward,and i must say,more relevant nowadays, at least in my opinion.

   👍 Pros:    Intuitive|Easy user interface

Temporal Reviews

Telegram mentions (139)

• SignalApp UI Home Screen but with Flutter

  Anyway, copying and reproducing is a great way to learn. It also train the mind to decompose every applications in small pieces. The same could have been done for Briar, SimpleX or Telegram applications, all of them are open-source and available on Github, Gitlab or somewhere else. Some of them are supporting mobile, desktop and web platform, in short, they are great targets. To summarize, if you want to learn how... - Source: dev.to / 19 days ago

• Remote Slop with Claude Code

  In fact, as of today, Anthropic officially shipped this as Claude Code Channels — a plugin-based feature that lets you push messages from Telegram or Discord into a running Claude Code session on your machine. Your session processes the request with full filesystem, MCP, and git access, then replies through the same chat. It's built on MCP, which means it slots into the existing plugin ecosystem cleanly. I ran my... - Source: dev.to / 4 months ago

• Trading Bot in C# — Part 2— Notifications

  Nowadays, messaging apps are ubiquitous. It’s quite possible that at least one message from such a service just buzzed in your pocket a moment ago. So why not to send a message to a chat group where your friends or customers can act on your trading tips! We chose Telegram because we are the most familiar with that particular service. The concept is straightforward: create a Telegram bot and utilize it to send... - Source: dev.to / about 1 year ago

• Understanding the Market Dynamics of Fragment Telegram Username: An In-Depth Analysis

  Learn about Telegram’s growth and privacy features at Telegram. - Source: dev.to / about 1 year ago

• Enhancing User Experience in Fragment Telegram: A Comprehensive Analysis

  As digital identity and blockchain integration continue to evolve, Fragment Telegram sets an inspiring benchmark for other platforms looking to innovate while emphasizing ease of use and security. The discussion of these trends also intersects with broader topics in blockchain finance and development. For additional information on blockchain innovations, refer to Telegram’s official website and read about current... - Source: dev.to / about 1 year ago

Temporal mentions (15)

• Compiler as Custodian

  Two specific moves stand out in Duncan's account. The first is durable execution, via Temporal — Mercury replaced fragile cron-and-database state machines with workflow code whose failure semantics are platform-handled (replay, retry, timeout, cancellation). Mercury open-sourced its hs-temporal-sdk, which wraps Temporal's official Rust Core SDK via FFI and provides a Haskell-native API. The dovetail with Haskell's... - Source: dev.to / 14 days ago

• How we turned our workflow editor into a real SDK

  We picked Temporal as the first reference engine on purpose. Temporal has the strictest execution model we know of – a V8 sandbox, determinism constraints, replay-driven recovery. If our port contract holds up against that, easier engines – an in-memory test double, a BullMQ queue, or JSON-first platforms like Inngest or Restate – plug in through the same two interfaces. We're shipping Temporal first; the rest is... - Source: dev.to / about 1 month ago

• Three days debugging a missing trace

  The trick is to find whatever metadata channel the queue already gives you and use that and thankfully, almost every mature queue has one (probably because of this scenario). SQS has message attributes, Temporal has context propagators built into the SDK, and Hatchet (which we use to run our workflows) has a metadata field called additionalMetadata. - Source: dev.to / 3 months ago

• Best ChatGPT Alternatives in 2026: Evaluated on Automation, Persistence, and Data Ownership

  A typical production stack for teams using Claude or Gemini as the reasoning layer includes an LLM provider API, an orchestration layer (n8n, Temporal, or a custom Python service), application infrastructure (a server running the orchestration code), and a data layer (a database for storing results). Each boundary introduces a failure point. When the LLM provider changes its rate limits, as OpenAI did repeatedly... - Source: dev.to / 3 months ago

• 50 Lines of TypeScript to Automate Any Website with AI

  The core is a browserclaw agent loop wrapped in a Temporal workflow. The AI navigates to your provider's payment page, identifies form fields from the snapshot, fills in your payment details, and submits. Every successful payment generates a "biller skill" — a playbook that makes subsequent payments to the same provider faster and more reliable. - Source: dev.to / 4 months ago