29 summarised stories about Agent Benchmarking, each linking back to the original source. Browse all topics →
Amazon Web Services 1 month ago 30
The Agent Evaluation Metric (AEM) was introduced to evaluate multi-turn agents at the level of individual turns, since one early error can corrupt later turns that holistic scoring misses.
rubyonrails.org 1 month ago 22 ● 2 sources
Claude’s Fable 5.1 and Z.ai’s GLM 5.3 Flash were rerun and posted on the Agents on Rails benchmark leaderboard with updated results. Fable 5.1 solved 58 of 63 runs (92%) at a $75 total price for all 63 runs, with 5.4 minutes median per run. Fable 5.1 takes the top position on multiple marks including price and security performance, and the previously stealth GLM 5.3 Flash is now listed with 52 of 63 runs (83%) for $3.31 total cost.
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19 October 2026
Agentic AI is leaving the lab and heading straight into the messy parts of work—then running into the equally messy parts of security. Atlassian’s “Agentic Multiplayer Protocol” is built around attribution, showing agent contributions in document history so accountability stays with the user, not “the AI did it.” That governance impulse is echoed elsewhere as teams try to treat agents like managed services instead of novelty software: Pax8’s 8os lets IT partners govern multiple vendors’ agents with per-customer separation and hard usage caps, while Motive Technologies pushes fleet automation from passive alerts to autonomous actions, pitching faster ROI through fewer preventable operational problems. Even property management is getting the agent layer, with Vessla aiming to coordinate leasing and building operations while keeping human approval for judgment calls.
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