A read of DRIFT and TELBench, which drop to the claim level to flag the error spans that affect the answer. Finding harmful spans climbs past halfway, but the first error stalls around 20%. Series Part 4, the finale.
A method-first read of the three papers for evaluating custom agents (MAST, AgentRx, DRBench): a vocabulary for failure, a way to pinpoint where it broke, a testbed shaped like your data. How a builder borrows research-scale work. Series Part 3.
A method-first read of the three papers that evaluate well-packaged agents (TRACE, DeepHalluBench, TRAIL): the altitude that rewrites the score, the one that verifies claims, the one that changes the substrate. Series Part 2.
A read of DRIFT and TELBench, which drop to the claim level to flag the error spans that affect the answer. Finding harmful spans climbs past halfway, but the first error stalls around 20%. Series Part 4, the finale.
A method-first read of the three papers for evaluating custom agents (MAST, AgentRx, DRBench): a vocabulary for failure, a way to pinpoint where it broke, a testbed shaped like your data. How a builder borrows research-scale work. Series Part 3.
A method-first read of the three papers that evaluate well-packaged agents (TRACE, DeepHalluBench, TRAIL): the altitude that rewrites the score, the one that verifies claims, the one that changes the substrate. Series Part 2.
Starting from the high-score illusion where the top-accuracy model ranks last on utility, this piece lays out why evaluation is moving to process and maps the methods of seven papers. Series Part 1.
Analysis of Langfuse and Dify's open-source monetization. Explains why observability layers are structurally superior to frameworks due to higher switching costs and continuous usage.