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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Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/harishkotra/building-an-alien-language-from-scratch-with-langchain-43ji |
| Publication time | Fri, 29 May 2026 16:07:37 +0000 |
| Retrieval time | 2026-05-29T16:20:02.338Z |
| Last seen | 2026-05-29T16:20:02.338Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | l5u1zylkFWkr |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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