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ai deep-dive

Braintrust: Closing the LLM Evaluation Loop from Datasets Back to Production

Braintrust connects versioned datasets, immutable experiments, scorers, and production traces into one evaluation loop. Its value is not another score but the ability to turn production failures into offline tests. The company announced an $80 million Series B in February 2026; its customer list is company-reported.

ai deep-dive

Helicone Deep Dive: LLM Gateway, Request Tracing, and Cost Analytics

Helicone is an open-source LLM gateway and observability platform: requests sent through its compatible endpoint automatically capture model, latency, tokens, cost, and custom properties, while managed credits or BYOK enable routing and fallbacks.

ai deep-dive

LangSmith Deep Dive: From Agent Traces to Offline and Online Evaluation

LangSmith structures LLM applications as projects, traces, runs, and threads, then uses datasets, evaluators, and experiments to turn production failures into offline regression tests. It observes any LLM application and does not require LangChain.

ai guide

Langfuse Complete Guide: LLM Application Observability from Scratch

Langfuse is currently the most mature open-source LLM Observability platform. This post covers four core capabilities — Tracing, Prompt Management, Evaluation, and Datasets — showing you how to use them in real projects.

RAG Observability Tool Landscape: Choices in 2026

Rolling your own traces is good enough, but open-source tools save you a lot of work. Langfuse, Phoenix, and LangSmith each have their niche — the right choice depends on your trade-offs around self-hosting, open source, and integration complexity.

RAG Observability: Per-Node Tracing to Turn the Black Box Transparent

The hardest part of a RAG system isn't building it — it's figuring out why a particular answer went wrong. Pipeline Tracing records every step's decisions and data so debugging has a clear trail to follow.