Arize AI, the AI observability platform co-founded by Jason Lopatecki and Aparna Dhinakaran, announced a definitive agreement to be acquired by Dynatrace, a software intelligence company, to accelerat…
Arize AI and Atlan report that enterprises running over 100 million AI evaluations monthly still face agent failures because model choice alone cannot ensure reliability, with context and harness engi…
Arize AI launched Signal, a managed agent built into its Arize AX platform that continuously reviews production traces, identifies recurring failure patterns, groups them into ranked issues with root-…
Only 2 out of 9 self-improving AI agents running in production actually have a verifier grounded in real-world data, according to an analysis by an unnamed expert. The verifier is the key bottleneck, …
Only 2 of 9 documented production use cases qualify as truly self-improving loops, according to a new analysis by Loadbearing Tech. The analysis highlights Replit's product development agent and an Op…
Arize cofounders Jason Lopatecki and Aparna Dhinakaran at Arize Observe 2026 outlined a shift from human-operated agent development to systematic, automated agent improvement, arguing that as agents s…
An experiment comparing PostgresFS, a Postgres-backed filesystem abstraction, against a SQL skill for AI agents found that the SQL skill achieved higher overall accuracy and lower maintenance costs. T…
At Observe 2026, Arize AI launched new Arize AX capabilities designed to automate the agent improvement loop for production systems, including Signal for continuous failure detection, agent orchestrat…
Arize AI cofounder and CPO Aparna Dhinakaran demonstrated a method for improving AI agents by building a better harness around the model, using traces and evals to debug failures. In a live demo with …