[Open Source] SwarmGo: Build Scalable AI Agents with Go (MIT License)
https://www.reddit.com/r/programming/comments/1g9qa77/open_source_swarmgo_build_scalable_ai_agents_with/
<!-- SC_OFF -->I’m excited to announce that I’ve just open-sourced SwarmGo, a Go framework that makes it easy to build, coordinate, and manage multiple AI agents. Inspired by OpenAI’s Swarm framework, SwarmGo is designed to help developers quickly implement AI-driven workflows with customizable functions and agent handoffs. Key Features: • Agent Handoffs: Agents can pass control based on context, making it perfect for scenarios where multiple capabilities need coordination. • Custom Functions: Define specific functions or tools that agents can use to perform tasks. • Lightweight and Scalable: Designed to handle independent agent interactions without complexity or bloat. • MIT Licensed: Free to use, modify, and contribute to! If you’re working with Go and AI or exploring AI-driven workflows, I’d love for you to check it out and let me know what you think! 🎉 👉 https://github.com/prathyushnallamothu/swarmgo I’d be happy to answer any questions, get feedback, or hear ideas for future improvements. I built this package to contribute back to the Go and AI communities, and I’m excited to see how it can be used in real-world applications. Looking forward to your thoughts and feedback! golang #ai #opensource #machinelearning #OpenAI <!-- SC_ON --> submitted by /u/EasyPattern4601 (https://www.reddit.com/user/EasyPattern4601)
[link] (https://github.com/prathyushnallamothu/swarmgo) [comments] (https://www.reddit.com/r/programming/comments/1g9qa77/open_source_swarmgo_build_scalable_ai_agents_with/)
https://www.reddit.com/r/programming/comments/1g9qa77/open_source_swarmgo_build_scalable_ai_agents_with/
<!-- SC_OFF -->I’m excited to announce that I’ve just open-sourced SwarmGo, a Go framework that makes it easy to build, coordinate, and manage multiple AI agents. Inspired by OpenAI’s Swarm framework, SwarmGo is designed to help developers quickly implement AI-driven workflows with customizable functions and agent handoffs. Key Features: • Agent Handoffs: Agents can pass control based on context, making it perfect for scenarios where multiple capabilities need coordination. • Custom Functions: Define specific functions or tools that agents can use to perform tasks. • Lightweight and Scalable: Designed to handle independent agent interactions without complexity or bloat. • MIT Licensed: Free to use, modify, and contribute to! If you’re working with Go and AI or exploring AI-driven workflows, I’d love for you to check it out and let me know what you think! 🎉 👉 https://github.com/prathyushnallamothu/swarmgo I’d be happy to answer any questions, get feedback, or hear ideas for future improvements. I built this package to contribute back to the Go and AI communities, and I’m excited to see how it can be used in real-world applications. Looking forward to your thoughts and feedback! golang #ai #opensource #machinelearning #OpenAI <!-- SC_ON --> submitted by /u/EasyPattern4601 (https://www.reddit.com/user/EasyPattern4601)
[link] (https://github.com/prathyushnallamothu/swarmgo) [comments] (https://www.reddit.com/r/programming/comments/1g9qa77/open_source_swarmgo_build_scalable_ai_agents_with/)
Building AI Agents to Play the Famous Game: Leisure Suit Larry (EPISODE 2)
https://www.reddit.com/r/programming/comments/1n5ambd/building_ai_agents_to_play_the_famous_game/
<!-- SC_OFF -->This episode gets into the technical side of things. Check out part 1 for the demo (links below) Watch as cutting-edge AI agents tackle the legendary Sierra adventure game Leisure Suit Larry! This comprehensive series explores how modern LLMs handle complex reasoning, humor, and puzzle-solving in classic gaming environments. 🤖 What You'll Learn
LLM-based agents vs true AGI-based Agents
Ben Gortzel, Rich Sutton, John Carmack
Project processing loop
Detailed prompt overview Series Videos
Part 1: Overview/Demo https://www.youtube.com/watch?v=e42I2bP0F6g
Part 2: Internals https://youtu.be/oxa1z_zKQ0Q ⏰ Timestamps
0:26 AI Agents Fundamentals & Capabilities
2:45 Ben Gortzel - AI insights
4:16 Rich Sutton - AGI-Based Agents and the OaK Framework
5:38 John Carkmack Experiential AI and Keen Technologies
6:31 Our project's processing loop
8:39 The Static Prompt (Drives a Dynamic Context)
11:37 Interative, Dynamic (and LLM Augmented) Prompt
12:08 Wrapping up/What's next 🔧 Technical Stack
AGI Engine: Adventure Game Interpreter
Backend: CrafterCMS + Spring AI Framework
AI Models: Grok + Grok Vision (xAI)
Protocols: Model Context Protocol (MCP) 📚 Related AI Research
Rich Sutton: OaK Architecture & SuperIntelligence - https://www.youtube.com/watch?v=gEbbGyNkR2U
John Carmack: Keen Technologies Research - https://www.youtube.com/watch?v=iz9lUMSQBfY
Rich Sutton: https://www.youtube.com/watch?v=zZuh8YUBeDY 📚 Similar Projects
The Chaos of AI Agents https://www.youtube.com/watch?v=2YYjPs8t8MI #AIAgents #LLM #MachineLearning #ArtificialIntelligence #AgenticAI #OpenAI #GoogleAI #AnthropicClaude #GrokAI #xAI #SpringAI #ModelContextProtocol #MCP #AIResearch #GameAI #LLMEvaluation #MultiModalAI #AIBenchmarks #RetroGaming #SierraGames #LeisureSuitLarry #AITesting #MLEngineering #AIArchitecture #LangChain #AIAgentFrameworks <!-- SC_ON --> submitted by /u/Russ-Danner (https://www.reddit.com/user/Russ-Danner)
[link] (https://www.youtube.com/watch?v=oxa1z_zKQ0Q) [comments] (https://www.reddit.com/r/programming/comments/1n5ambd/building_ai_agents_to_play_the_famous_game/)
https://www.reddit.com/r/programming/comments/1n5ambd/building_ai_agents_to_play_the_famous_game/
<!-- SC_OFF -->This episode gets into the technical side of things. Check out part 1 for the demo (links below) Watch as cutting-edge AI agents tackle the legendary Sierra adventure game Leisure Suit Larry! This comprehensive series explores how modern LLMs handle complex reasoning, humor, and puzzle-solving in classic gaming environments. 🤖 What You'll Learn
LLM-based agents vs true AGI-based Agents
Ben Gortzel, Rich Sutton, John Carmack
Project processing loop
Detailed prompt overview Series Videos
Part 1: Overview/Demo https://www.youtube.com/watch?v=e42I2bP0F6g
Part 2: Internals https://youtu.be/oxa1z_zKQ0Q ⏰ Timestamps
0:26 AI Agents Fundamentals & Capabilities
2:45 Ben Gortzel - AI insights
4:16 Rich Sutton - AGI-Based Agents and the OaK Framework
5:38 John Carkmack Experiential AI and Keen Technologies
6:31 Our project's processing loop
8:39 The Static Prompt (Drives a Dynamic Context)
11:37 Interative, Dynamic (and LLM Augmented) Prompt
12:08 Wrapping up/What's next 🔧 Technical Stack
AGI Engine: Adventure Game Interpreter
Backend: CrafterCMS + Spring AI Framework
AI Models: Grok + Grok Vision (xAI)
Protocols: Model Context Protocol (MCP) 📚 Related AI Research
Rich Sutton: OaK Architecture & SuperIntelligence - https://www.youtube.com/watch?v=gEbbGyNkR2U
John Carmack: Keen Technologies Research - https://www.youtube.com/watch?v=iz9lUMSQBfY
Rich Sutton: https://www.youtube.com/watch?v=zZuh8YUBeDY 📚 Similar Projects
The Chaos of AI Agents https://www.youtube.com/watch?v=2YYjPs8t8MI #AIAgents #LLM #MachineLearning #ArtificialIntelligence #AgenticAI #OpenAI #GoogleAI #AnthropicClaude #GrokAI #xAI #SpringAI #ModelContextProtocol #MCP #AIResearch #GameAI #LLMEvaluation #MultiModalAI #AIBenchmarks #RetroGaming #SierraGames #LeisureSuitLarry #AITesting #MLEngineering #AIArchitecture #LangChain #AIAgentFrameworks <!-- SC_ON --> submitted by /u/Russ-Danner (https://www.reddit.com/user/Russ-Danner)
[link] (https://www.youtube.com/watch?v=oxa1z_zKQ0Q) [comments] (https://www.reddit.com/r/programming/comments/1n5ambd/building_ai_agents_to_play_the_famous_game/)