agentic-rl

band: coolmomentum: stable score: 0.002

temperature history

Episodes (7)

Independent evaluations will determine whether EvoHarnessRL’s learned self-evolving runtime harness materially improves long-horizon LLM-agent performance over fixed harnesses.

expiredknownscott: medium

Prime Intellect's large-scale agentic-RL environment program will produce transferable capability gains for models trained on SWE, terminal, and search tasks.

expirednovelscott: low

Independent integrations and training runs will determine whether Harbor’s token-in/token-out proxy can connect existing agent harnesses to reinforcement-learning systems without harness-specific modifications.

expiredconvergesscott: medium

Independent use will determine whether InclusionAI’s AReno provides a practical self-contained stack for single-node RL, SFT, DPO, serving, and agentic post-training.

expiredconvergesscott: medium

Independent replication will determine whether CUDA Agent’s large-scale agentic-RL training produces materially better CUDA kernels than training-free refinement and conventional compiler-assisted generation.

expiredknownscott: medium

Independent deployments will determine whether K7d can reproducibly fork live multi-node Kubernetes VMs in under a second and materially improve environment branching for infrastructure-agent reinforcement learning.

expiredknownscott: medium

Independent deployments will determine whether Microsoft’s Agent Lightning v1 provides a practical runtime-independent framework for training, optimizing, and evaluating existing AI agents.

expiredconvergesscott: high

Trajectory notes

2026-09-04T23:30:31Z: microsoft-agent-lightning-v1 closed (faded) — Microsoft’s runtime-decoupled training proxy independently operationalizes Scott’s trace-backed agent comparison, observability, and evaluation-driven development positions, creating a strong dated-receipts and hands-on validation o
2026-08-26T22:38:32Z: prime-intellect-agentic-rl-365k-envs closed (faded) — No intersection found. The wiki_hits and radar_hits are both empty — Scott's own wikis contain no pages touching Prime Intellect, agentic RL at scale, or this specific research program. The radar also has no prior tracking o
2026-08-23T01:27:45Z: cuda-agent-kernel-generation-validation closed (faded) — The case restates Scott’s existing requirement for independent, version-bound evaluation before spending seller-reported performance claims, as carried by Capability Audit and the Evidence Class Ladder. It matters beyond
2026-08-22T08:28:14Z: areno-single-node-post-training closed (faded) — Converges with Scott's established position on local/self-contained AI infrastructure — the dev wiki shows extensive hands-on work with single-node LLM serving, local post-training, and agentic tooling (gamepc, openclaw, ask, gpt
2026-08-20T16:40:07Z: k7d-kubernetes-vm-forking closed (faded) — The radar already tracks essentially the same validation question on “Independent reproduction will determine whether Kimi K3’s AgentENV can fork dirty-memory microVMs in roughly 100 milliseconds,” alongside Kubernetes agent-sandbox an
2026-08-19T22:34:07Z: harbor-token-proxy-agentic-rl closed (faded) — Harbor’s proposed proxy converges with Scott’s model-plus-harness architecture, proxy-routed backends, and trace-backed comparison work by attempting to make existing harnesses reusable as RL environments through a stable interface
2026-08-15T17:29:39Z: evoharnessrl-self-evolving-agent-harness closed (faded) — The radar already tracks this development’s central validation question on `radar:trained-harness-cross-model-transfer`: whether a learned harness produces transferable gains without overfitting. Independent results woul