RAX: coding agents explore robots and compile skills—no demos
At a glance
RAX (Robot Agent eXploration) lets a frozen LLM coding agent drive real robots via APIs, explore online, and compile successful perception–planning–control loops into reusable programs—no teleop demos or policy training; +37.4% avg vs baselines in sim; open skill libraries per embodiment. This workflow is listed under robotics, coding-agents, exploration, skill-library, learnable-paradigm.
Open method: Blast/Mid/Inner write at system/subsystem/local altitude, then fixed T1 structural → T2 bug/ops → T3 adversarial gates with handoff packets—agents get AGENTS.md + prompt files, not a vague “please be careful.”
AWS Labs open-source (5k+★): one harness-neutral core turns Claude Code/Codex/Cursor/Copilot/Kiro/opencode into structured, verifiable delivery workflows via `aidlc config --harness` + doctor—install script, not a new agent.
Thenovi AI (Band) launched a desktop app plus CLI so engineers can see fleets of coding agents at once—projects, ownership, blockers, questions, progress—and intervene without manually shuttling session context between isolated harnesses.
JetBrains Junie Local ships native support for NVIDIA RTX Spark (up to ~55 tok/s in early tests, auto-sized context, FP8 + speculative decoding) and moves Windows Ampere+ 24GB RTX from experimental to stable—free local coding agent with no token charges and code that never leaves the machine.