The Evaluator
The Evaluator
Your go-to blog for insights on AI observability and evaluation.
What is an agent harness?
A version of this article originally appeared on X. Someone asked me at a hacker event last week: “Can anyone actually tell me what a harness really is?” It was…
What is an agent harness?
A version of this article originally appeared on X. Someone asked me at a hacker event last week: “Can anyone actually tell me what a harness really is?” It was…
Beyond models: How context and evals make agents work in production
Building an AI agent has never been easier. But getting one into production that’s reliable is still hard. Most teams can ship a working demo in a day. The agent…
Beyond models: How context and evals make agents work in production
Building an AI agent has never been easier. But getting one into production that’s reliable is still hard. Most teams can ship a working demo in a day. The agent…
How to add an evaluation harness to your Gemini CLI coding agent
Coding agents can update prompts, wire in tools, and change application logic across your codebase in a single run. The hard part isn’t getting the agent to make changes, but…
How to add an evaluation harness to your Gemini CLI coding agent
Coding agents can update prompts, wire in tools, and change application logic across your codebase in a single run. The hard part isn’t getting the agent to make changes, but…
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Code is free, technical debt isn’t: Notes from AI Engineer Europe
Keynotes at Europe’s first flagship AI Engineer Conference shared one theme: code generation has accelerated past our ability to verify it, and the industry is quietly reorganizing around that fact….
Code is free, technical debt isn’t: Notes from AI Engineer Europe
Keynotes at Europe’s first flagship AI Engineer Conference shared one theme: code generation has accelerated past our ability to verify it, and the industry is quietly reorganizing around that fact….
Data Fabric: Querying agent traces in BigQuery
How to join LLM traces with billing, infrastructure, and customer data using Iceberg and BigQuery If you run AI agents in production, you’ve probably run into a simple problem: you…
Data Fabric: Querying agent traces in BigQuery
How to join LLM traces with billing, infrastructure, and customer data using Iceberg and BigQuery If you run AI agents in production, you’ve probably run into a simple problem: you…
Building smarter AI agents: architecture, evals, and lessons from the field
Shipping an AI agent is easy. Understanding whether it actually works in production is not. That was the common thread across two AI Builders events in San Francisco at GitHub…
Building smarter AI agents: architecture, evals, and lessons from the field
Shipping an AI agent is easy. Understanding whether it actually works in production is not. That was the common thread across two AI Builders events in San Francisco at GitHub…
How Arize Skills Improved RAG Recall from 39% to 75% in 8 Hours
The Pain of Iterative RAG Development If you’ve built a production RAG system, you know this cycle. Tweak parameters, re-index, re-evaluate, repeat. It’s slow. It’s manual. The feedback loop between…
How Arize Skills Improved RAG Recall from 39% to 75% in 8 Hours
The Pain of Iterative RAG Development If you’ve built a production RAG system, you know this cycle. Tweak parameters, re-index, re-evaluate, repeat. It’s slow. It’s manual. The feedback loop between…
From First Eval to Autonomous AI Ops: A Maturity Model for AI Evaluation
Every team runs evals. Almost none have an evaluation practice. The difference is the gap between a one-off notebook and a system that continuously assesses, alerts, and acts on what…
From First Eval to Autonomous AI Ops: A Maturity Model for AI Evaluation
Every team runs evals. Almost none have an evaluation practice. The difference is the gap between a one-off notebook and a system that continuously assesses, alerts, and acts on what…
100 AI Agents Per Employee: The Enterprise Governance Gap
100 AI agents per employee: The enterprise governance gap NVIDIA CEO Jensen Huang recently described a future where companies operate with roughly 100 AI agents per employee. That future is…
100 AI Agents Per Employee: The Enterprise Governance Gap
100 AI agents per employee: The enterprise governance gap NVIDIA CEO Jensen Huang recently described a future where companies operate with roughly 100 AI agents per employee. That future is…
Managing Memory in AI Agents: Beyond the Context Window
This is part two of our deep dive series on how we built Alyx 2.0, our AI engineering agent. Watch us discuss it above, or keep reading for the full…
Managing Memory in AI Agents: Beyond the Context Window
This is part two of our deep dive series on how we built Alyx 2.0, our AI engineering agent. Watch us discuss it above, or keep reading for the full…