From Proposal to Verified Effect: Praxa, an Evidence-Bound Harness for Governed AI Agent Execution
arXiv cs.AIen
arXiv:2610.00015v1 Announce Type: new Abstract: Large-language-model agents can propose and execute actions, but proposal, authority, dispatch, verified external effect, and serving promotion are different claims. We present Praxa, an agent harness that represents these states explicitly through deterministic admission, brokered execution, external read-back, reconciliation, and reviewed promotion. We report four evidence lanes. First, an author-run repository-local audit at a pinned revision passed 1,027/1,027 unit tests and 89/89 Workerd tests, instrumented all 363 expected source files, and met four coverage floors; raw per-test transcripts and independent reproduction are unavailable. Se
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Forskning
- Agenter
Related AI news
- Google's first Suncatcher satellite reaches orbit to test AI chips in spaceDIGITIMES · October 2, 2026
- AutoSynthData: Generating Training Data for Enterprise AgentsHugging Face · October 2, 2026
- Meta vill sälja AI till företag – men vågar företagen lita på Meta?Computer Sweden · October 2, 2026
- Characterizing a Configuration Where Inference-Time PRM-Pruned Fragment Grafting Is Inert: Evidence from Three Reasoning LMsarXiv cs.AI · October 2, 2026
- Benchmarking Prompt Optimization of Large Language Models With ChessarXiv cs.AI · October 2, 2026
- Build2SPARQL: A Large-Scale Text-to-SPARQL Benchmark Dataset for Building Knowledge Graph QueryingarXiv cs.AI · October 2, 2026