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Source channel @githubtrending · Post #15230 · Oct 16

#other This collection of leaked GPT prompts offers a wide range of tools and ideas for interacting with AI models. It includes prompts for tasks like writing, coding, humor, and education, which can help users understand how GPT models work and improve their interactions with AI. By using these prompts, users can create more effective and personalized AI experiences, benefiting from the diverse contributions and insights shared by the community. This resource is valuable for both developers and users looking to enhance their AI interactions. https://github.com/linexjlin/GPTs

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Go

@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

Go

@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

GitHub Trends

@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