#multi-agent
4 articles
01
·Agents·★ MEMBER·PAPER·10 min read
Multi-Agent Design Patterns — Division, Debate, Verification
Stack as many agents as you like — if they all fail the same way, you have one agent and a larger bill. The condition under which voting actually helps, written down, then the three patterns that follow from it: division of labour, debate, and adversarial verification — plus when one agent is enough.
02
·Paper Deep-Dives·★ MEMBER·PAPER·11 min read
Paper walkthrough: Apodex 1.1 — scaling agents around completed work
Not a bigger model and not more thinking time — Apodex 1.1 scales two other surfaces: the environments an agent learns in, and the way work is organised across agents. A walkthrough from the task contract to the AgentOS delivery gate, the numbers, and the limits.
03
·Agents·★ MEMBER·PAPER·12 min read
Paper Explained: Co-RL — Reasoning Without Labels, Emerging From a Diverse Cohort
Grade your own answers long enough and the model collapses. Co-RL breaks that loop by rewarding each agent against a peer's majority vote, matching supervised training without touching a single ground-truth label. The mechanism, the dynamics, the numbers, and the traps — straight from the paper.
04
·Agents·★ MEMBER·PAPER·9 min read
Paper Explained: Co-Evolution in Agentic Systems — Three Stages Toward Self-Directed Evolution
Why do agents that are supposed to keep improving after deployment hit a ceiling? A ground-up walkthrough of a survey that organises the field into three stages — evolving peers, evolving environments, and an evolving evolution mechanism — with the defining equations, representative methods, and the open problems in evaluation and safety.