TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15530 · Feb 28
#typescript#agentic_ai#ai_agents#claude_code#cli#codex#coding_agents#cursor_agent#desktop_app#developer_tools#electron#git_worktree#llm#mcp#opencode#orchestration#parallel_agents#terminal#tui#vibe_coding#worktrees Superset is a turbocharged macOS terminal for running 10+ CLI coding agents like Claude Code, Cursor, and GitHub Copilot in parallel. It isolates tasks in separate Git worktrees to avoid interference, lets you monitor progress from one dashboard, review changes with a built-in diff viewer, and switch contexts quickly. You benefit by coding 10x faster, shipping more without context-switching delays or conflicts, saving time on development workflows. https://github.com/superset-sh/superset
Search: #runtime
@golang · Post #58 · 04/22/2018, 08:22 PM
Why are goroutines not lightweight threads? Kartik Khare shows us his meaning about goroutines, lightweight threads and their difference in GoLang. There are no code examples inside but good thoughts about parallelism, threads and useful links at the end of the article :) #development#runtime#language https://codeburst.io/why-goroutines-are-not-lightweight-threads-7c460c1f155f
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@golang · Post #64 · 06/21/2018, 04:17 PM
Hi there! Which ways do you use to avoid memory leaks for REST API? In the following article by Iman Tumorang describes an excellent example of memory leaks, his solution, and results. Must have to read for everyone 😉 #development#runtime#architecture https://hackernoon.com/avoiding-memory-leak-in-golang-api-1843ef45fca8
@githubtrending · Post #15382 · 01/01/2026, 12:30 PM
#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples