多模型分工抗「Agent 老化」架构：Argon 负责多模态遥测流
介绍一套反老化 Agent 架构，Gemini 4 Argon 负责高吞吐多模态遥测与原始状态流，Jev 做 14ms 系统一决策，GPT-6.1 Sol 与 Opus 5.5 各司其职。
holy sh*t Researchers from frontier AI leaders (Anthropic, OpenAI, Google, NVIDIA) just solved agent aging When developers run 300 autonomous agents across a 12-hour horizon, models collapse at Turn 25. The runtime suffocates them in context rot, burning $48,000/mo on 10-second decode loops just to answer binary yes/no questions and linter checks The Anti-Aging Architecture splits the cognitive stack: non-autoregressive System 1 (Jev) decides in 14ms ($0.042/M in, $0 out), while frontier models synthesize The cognitive division of labor: > Gemini 4 Argon streams high-throughput multimodal telemetry and raw state > Jev System 1 handles sub-second binary gates, hazard tripwires, and routing in 14ms > GPT-6.1 Sol explores speculative rollout trees and high-entropy code branches > Claude Opus 5.5 audits production architecture and locks canonical diffs 5 GitHub repos applying Jev Engineering and the Anti-Aging Architecture to save agent runtimes from cognitive collapse: want 1M tokens of raw terminal and tool logs compacted without lossy summarization? -> fast-jev-compaction [ 7.6k stars // 185k views ] line-item relevance pruning collapses 1,000,000 tokens down to 86k in 1.1s with zero generative summarization and zero memory rot repo: http://github.com/tamaratran/fast-jev-compaction want to stop burning frontier tokens on simple routing and safety checks? -> system-one-adapter-python [ 2.4k stars // 94k views ] non-autoregressive Choice, Score, and Noul primitives evaluated in <150ms before touching frontier APIs repo: http://github.com/typesafe-ai/system-one-adapter-python want UI and browser agents that do not freeze on 50-step DOM interactions? -> jev-ultrafast [ 22.6k stars // 410k views ] non-autoregressive action routing across DOM trees that cuts latency by 12x and feeds clean state to Gemini 4 Argon repo: http://github.com/browser-use/jev-ultrafast want multi-turn agents that do not contradict their own architecture past turn 25? -> jev-state-machine [ 3.1k stars // 112k views ] non-volatile JSON disk queues (research, write, review) that eliminate revision aging and state drift repo: http://github.com/rjz/jev-state-machine want an autonomous agent OS with pre-execution safety and trading gates built in? -> QuantDinger [ 12.7k stars // 320k views ] full AI OS using Jev for sub-second pre-execution guardrails before firing live API or market actions repo: http://github.com/OpenByteInc/QuantDinger The verified results across a 12-hour, 300-agent run: - API spend drops from $140 down to $1.20 per verified run (116x reduction) - Context rot: 0.0% - Memory compaction: -88.6% stale tokens evicted - Zero cognitive collapse across 1,850+ tasks You stop burning frontier tokens on single-bit outputs You let System 1 route in 14ms, and let frontier models build save this
这条是引用着另一条写的：x.com/marfinxx/status/2103801809428955509