Building an Alien Language from Scratch with LangChain
Harish Kotra's project explores the creation of an alien language using AI agents that evolve a shared vocabulary through trade. The agents operate without pre-programmed definitions, relying solely on reinforcement learning to establish meaning. Utilizing LangChain SDK, the project demonstrates how AI can negotiate and communicate effectively in a simulated environment.
- ▪The project involves 100 AI agents with unique personalities negotiating trades using abstract symbols.
- ▪No hardcoded symbol meanings or mock data were used, allowing for genuine language evolution.
- ▪LangChain.js serves as the backbone of the project, employing various patterns to manage agent complexity.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 101279) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Harish Kotra (he/him) Posted on May 29 Building an Alien Language from Scratch with LangChain #ai #programming #productivity #dailybuild2026 How 100 AI agents evolved a shared symbolic vocabulary through trade — with no pre-programmed definitions, no mock data, and no shortcuts. The Core Idea Most emergent communication demos cheat. They hardcode symbol meanings, or use mock LLM responses, or simulate the entire thing with random number generators.
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