How to Debug Coding Agents with LangSmith Traces
Use LangSmith to trace coding agents across Claude Code, Codex, Cursor, Copilot, and more. Inspect tool calls, subagents, errors, costs, and retries. Context & related coverage →
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Use LangSmith to trace coding agents across Claude Code, Codex, Cursor, Copilot, and more. Inspect tool calls, subagents, errors, costs, and retries. Context & related coverage →
Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector... Context & related coverage →
Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, where direct paper-to-repository comparison is prone to hallucinatio... Context & related coverage →
Multi-label classification assigns several co-occurring labels to each aerial scene, yet deployed models often encounter data distributions different from their training. Feature-statistics augmentation such as MixSty... Context & related coverage →
AWS and Anthropic have released the Claude apps gateway for AWS, a self-hosted control plane that centralizes identity, policy, telemetry, routing, and spend caps for Claude Code and Claude Desktop. The gateway runs a... Context & related coverage →
Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task actually requires. They often follow a maximum-context-first strateg... Context & related coverage →
simonw/pedalican Clearly I wasn't paying attention when these were first announced back in May, but today I accidentally activated a "pet" in Codex Desktop - a little animated robot, reminiscent of Clippy - and then l... Context & related coverage →
At this year's AIE World’s Fair, AI engineering entered a new phase: building systems around agents, rather than just building with agents. Context & related coverage →
Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when their internal belief is unchanged. We cast this as a failure of i... Context & related coverage →
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. Context & related coverage →
Release 0.145.0-alpha.13 Context & related coverage →
The shared language of a software project is not English or Python but it is the common understanding of what its concepts mean, where the boundaries are, which invariants matter, who owns what, and why the system has... Context & related coverage →