-
Opik Release Highlights: Real-Time Alerts, No-Code Evaluation, & Generative Prompt Tools
As LLM applications and agents scale, visibility and iteration speed matter more than ever. This month’s Opik updates close the…
-
Human-in-the-Loop Review Workflows for LLM Applications & Agents
You’ve been testing a new AI assistant. It sounds confident, reasons step-by-step, cites sources, and handles 90% of real user…
-
Best LLM Observability Tools of 2025: Top Platforms & Features
LLM applications are everywhere now, and they’re fundamentally different from traditional software. They’re non-deterministic. They hallucinate. They can fail in…
-
Context Engineering: The Discipline Behind Reliable LLM Applications & Agents
Teams cannot ship dependable LLM systems with prompt templates alone. Model outputs depend on the full set of instructions, facts,…
-
LLM Tracing: The Foundation of Reliable AI Applications
Your RAG pipeline works perfectly in testing. You’ve validated the retrieval logic, tuned the prompts, and confirmed the model returns…
-
LLM Monitoring: From Models to Agentic Systems
As software teams entrust a growing number of tasks to large language models (LLMs), LLM monitoring has become a vital…
-
Opik Release Highlights: GEPA Agent Optimization, MCP Tool-Calling, and Automated Trace Analysis
As AI agents and LLM applications grow more powerful and complex, this month’s Opik updates integrate leading-edge technologies to help…
-
Thread-Level Human-in-the-Loop Feedback for Agent Validation
Imagine you are a developer building an agentic AI application or chatbot. You are probably not just coding a single…
-
Introduction to LLM-as-a-Judge For Evals
In recent years, LLMs (large language models) have emerged as the most significant development in the AI space. They are…
-
The Ultimate Guide to LLM Evaluation: Metrics, Methods & Best Practices
The meteoric rise of large language models (LLMs) and their widespread use across more applications and user experiences raises an…


















