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Source channel @githubtrending · Post #15250 · Oct 26

#python#agent#agentic_ai#llm#mlops#reinforcement_learning Agent Lightning is a tool that helps improve AI agents using reinforcement learning. It allows you to train your agents without making big changes to their code, which is very convenient. You can use it with many different frameworks like LangChain or OpenAI Agent SDK. It also supports various training methods, including reinforcement learning and automatic prompt optimization. This means you can make your agents better at their tasks without a lot of extra work. https://github.com/microsoft/agent-lightning

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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