Traces
Traces on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on traces in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around traces, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Presentation: Can Claude Fix Itself? Using LLMs for Incident Response
Incident response demands speed and precision. Join Anthropic reliability engineer Alex Palcuie as he shares practical lessons on leveraging Large Language Models (LLMs) for real-world troubleshooting. This presentation clarifies where AI excels—acting as a superhuman observer of logs and traces—while also highlighting persistent challenges in root-cause analysis, specifically distinguishing causation from correlation. Palcuie outlines how engineering leaders can effectively integrate AI into on-call workflows, preserving crucial human expertise.
A single AI agent conversation can look perfect and still be broken, leaders from LangChain, Conviva and CoreWeave said at VB Transform 2026
Evaluating AI agents requires a shift from scrutinizing individual conversations to analyzing user cohorts against a baseline, according to leaders from LangChain, Conviva, and CoreWeave at VB Transform 2026. The disconnect between seemingly flawless agent interactions and underlying product issues is driving this change. Teams are moving toward treating evaluation criteria as a living product specification—akin to a product requirements document—rather than a static test suite. This approach, alongside cheaper, narrower judge models, promises a more reliable path to robust AI agent performance.