GitHub Copilot Reviews

1. Stan

   · Founder at SaaSHub · over 2 years ago
   Indispensable

   It definitely increases my productivity.

   🏁 Competitors: Tabnine

Google Cloud Speech API Reviews

GitHub Copilot mentions (388)

• Test smarter with Snagly: 30 open-source QA skills for AI coding agents

  Snagly is a free, MIT-licensed set of 30 skills for AI coding agents — GitHub Copilot, Claude Code, Cursor, Codex and 70+ others — that turn "an AI that can drive a browser" into "an AI that tests like a QA professional." A skill, if you haven't met them yet, is a reusable instruction set that teaches the agent a specific working method — when to use it, what rigor it requires, what evidence to capture, and what... - Source: dev.to / 3 days ago

• I almost credited llms.txt for a Google AI Mode win. Then I read what Google actually says.

  Where llms.txt genuinely gets read is a different layer: coding and agent tooling — Cursor, Claude Code, GitHub Copilot, Windsurf — pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's Agents SDK. That's real, and it's growing fast. - Source: dev.to / about 1 month ago

• GitHub Copilot for Engineers: Getting Better Results

  You need an active GitHub Copilot subscription. Plans are available at individual, business, and enterprise tiers at github.com/features/copilot. Once active, all tools use your GitHub account credentials. - Source: dev.to / 2 months ago

• Agentic: Which App/Harness Is Best for Angular Development?

  For over a decade PhpStorm (starting in my WordPress era) and later WebStorm have been my main IDEs for web development. So when GitHub Copilot launched, it was a natural choice to try it out in WebStorm. It was one of the first AI coding tools I used, and it had a big impact on how I thought about AI-assisted coding. - Source: dev.to / 2 months ago

• Your Design System Needs An MCP Server

  Before we get into it, there are some things about AI usage worth addressing. I've had my fair share of scepticism in the past, but recent model releases have made it increasingly difficult to argue that AI isn't a viable tool for the majority of workstreams, including building user interfaces. Most large language models are trained on public data scraped from the internet, which means your internal design system... - Source: dev.to / 2 months ago

Google Cloud Speech API mentions (45)

• Automating Meeting Follow-Ups: From Transcript to Task List

  If you want to roll your own solution, you can use APIs like Google Cloud Speech-to-Text or AssemblyAI:. - Source: dev.to / 6 months ago

• What the Best Coding Copilots Can Do for You in 2025

  *- Speech Pipelines * Copilots can generate ready-to-use code for speech-to-text and text-to-speech using APIs like OpenAI Whisper, Azure AI Speech, and Google Cloud Speech-to-Text. For example, a developer can ask for a transcription setup in Python and get working code within seconds — useful for customer support, meeting notes, or language learning apps. - Source: dev.to / 11 months ago

• GCP Fundamentals: Cloud Speech-to-Text API

  Google Cloud Speech-to-Text API is a powerful tool for transforming audio into actionable insights. Its accuracy, scalability, and customization options make it a valuable asset for a wide range of applications. By understanding its features, capabilities, and best practices, you can unlock the full potential of speech recognition and build intelligent applications that understand and respond to the world around... - Source: dev.to / about 1 year ago

• The Technology Behind YouTube’s Auto-Captioning System

  Google, YouTube’s parent company, has invested heavily in speech recognition research. Their Cloud Speech-to-Text API is one of the most advanced in the world, and its technology forms the backbone of YouTube’s captioning system. The API uses neural networks to process audio, identify phonemes (the smallest units of sound), and assemble them into words and sentences. - Source: dev.to / over 1 year ago

• Cloud Solutions vs. On-Premise Speech Recognition Systems

  Cloud-based speech recognition solutions, such as Google Cloud Speech-to-Text and Microsoft Azure Speech, have gained popularity due to their accessibility, power, and scalability. Developers gain access to ready-to-use APIs with high-quality speech recognition models. However, behind this convenience are several important technical aspects that need to be considered when choosing a cloud solution. - Source: dev.to / over 1 year ago