really like how DSPy turned RLM into plug-and-play. Super simple integration, way more reliable than manual prompting. This is gonna help a ton with our upcoming stuff.

Experimenting android studio atm. OMG this is so cool haha so much opportunities for RLM to be used in daily life

Really good blog post by Prime Intellect on RLMs (Alex L Zhang and Omar Khattab’s work). I believe 2026 is going to be dominated by two paradigms: RLMs, and the semantics constraints we’re working on at .txt. More on that soon 🙂 primeintellect.ai/blog/rlm

GM $RLM Community💻

The recent paper on Recursive Language Models (RLMs) has sparked a lot of discussion. At a high level, RLMs do not expand an LLM’s native context window. Instead, they propose a practical way for models to explore large external data by using simple tools in a REPL-like

Fundamentally, what really is the difference between an RLM and S={context folding, Codex, Claude Code, Terminus, agents, etc.}? This is the last and most important RLM post I'll make for a while to finally answer all the "this is trivially obvious" from HackerNews, Reddit, X,

Jensen Huang's AI five-layer cake: energy, chips, cloud, models, apps. RLM here living rent-free in the models + applications layers, turning reasoning into real-world action. Time to agent-ify the cake

Update on the RLM → ElizaOS work 🚧 Followed Shaw’s feedback and pushed a clean plugin-based implementation. What changed since the last PR: • Moved RLM fully into plugins/plugin-rlm/ (no core changes) • Switched to Eliza v2 declarative model registration

Meanwhile we wait for final checks by Shaw for Eliza integration, I made a research paper decomposer using RLM that can take any research paper into pieces and process and spit it out info as output. Will integrate this into the frontend later and will tweet out from the main

RLM is already exciting. But once it’s faster and runtime-efficient… it’ll be dangerous for the agentic economy.

I’m turning this account into an automated reply bot. It scans mentions (later follower tweets), extracts context, then replies using an RLM-style loop (draft→critique→refine) instead of one-shot prompts. Rate-limit safe: 15–30m polls, caps, filters, dedupe. Source code will

Hi, we are BACK!!!!! Seems like our RLM implementation on Eliza might be shipped together with v2.0.0 Eliza release👀 github.com/elizaOS/eliza/…

Development takes time but we are building slowly but surely

I registered an Agent RLM instance on ClawArcade today and have been running experimental matches for several hours. The platform lets agents compete autonomously in over fifty games (including Snake, Chess, and MEV Bot Race) with no human players in the ranked tournaments.

Welcome AgentRLM onboard 🤝