The Agent Trust Blog

The latest trends and news in data observability and agent observability.

Most recent

The 5 AI Agent Evaluation Metrics Every Team Should Be Tracking Right Now

So you built an AI agent. Great. You shipped it, your boss is impressed, and somewhere a CFO is staring at an Anthropic invoice with the kind of quiet horror usually reserved for medical bills. Welcome to the part of the AI cycle where the vibes-based deployment ends and someone, probably you, has to answer … Continued

Data trust used to come after the fact. With Claude, it ships with your code.

Built for the enterprise, ready for AI: Under the hood of Monte Carlo’s platform updates

New Monte Carlo Research: Two-Thirds of Orgs Ship Agents Before They are Ready to Support Them

The Memory Problem Changes When Agents Stop Waiting to Be Prompted

Enterprise AI Confidence with Atlan + Monte Carlo

What is AI-Ready Data? Redefining AI-Ready for Production.

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Learn how today's data teams apply automated lineage to boost productivity, reduce time to incident resolution, and more.

Download

Data Quality Statistics & Insights From Monitoring +11 Million Tables in 2026

Build vs. buy: The real token economics of agent observability

Your Data Isn’t as Clean as You Think. Here’s How Data Quality Automation Helps

How to make Claude a trusted analyst for your whole company

Claude and Cursor Can’t Do Data Right

Monitoring Cortex Agent Performance With Trace Data

AI Observability

Garbage data, garbage agents: Scaling your Cortex Fleet starts here

What it takes to trust AI in production: Lessons from Salesforce and Dropbox at Snowflake Summit

How Monte Carlo’s agentic observability caught a $16K/day bug in our own revenue data

Integrating trust into the Agentic Control Plane: Observations from Snowflake Summit

Axios at Snowflake Summit: Building a Culture of AI Trust with Monte Carlo

Why AI agents fail in production, and how to fix them with Monte Carlo and Snowflake

Data Platforms

What is a Data Platform and How Do You Build One?

Open Source Business Intelligence Tools

Cheat Sheet: A Data Leader's Guide to Data Metrics

Access the must-have metrics today's data leaders use to measure data quality, platform ROI, team productivity, and more.

Download Your Copy

What Is Model Context Protocol (MCP)? A Quick Start Guide.

Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences

Data Warehousing Guide: Fundamentals & Key Concepts

The Future Of Business Intelligence: 5 Trends To Watch In 2026

AI Culture

Going Agent Experience First: What We Built, What We Broke, What We Learned

The Ultimate Guide to Data Product Management

Learn how to build, manage, and scale reliable data products in our latest how-to guide, written by and for data product managers.

Download

What the EU AI Act Actually Requires (And Why Your Current Solutions Won’t Get You There)

We Went All In on AI. Here’s What We Shipped in Just One Week.

Trading Places in Financial Services: How Accountability Changes Seats in Agentic Systems

When Agents Manage Agents, Blame Disappears. Consequences Don’t.

Know Before You Go: Gartner Data & Analytics Summit 2026

Data Reliability

The Ultimate Guide To Data Lineage

Data Contracts 101: What They Are, Why They Matter, and How to Implement Them

2023 Modern Data Leader's Playbook

Stay up-to-date with the latest technologies, trends, and processes shaping modern data management.

Access Today

The New Dictionary of AI Reliability

Monitoring Through Disaster: Why Multi-Region Hosting Matters

Data Remediation: Ensuring Data Quality and Reliability in Modern Data Pipelines

Data Munging That Actually Works

Data Discovery

6 Tips For Better SQL Query Optimization

Star Schema vs. Snowflake Schema: Which One Should You Use?

The Best Snowflake Orchestration Tools

Data Catalog vs. Data Dictionary: 5 Essential Differences

Tired of Broken Pipelines? Here’s How ETL Orchestration Can Help

Messy Files and Confused Teams? You Need Product Data Management

Case Studies

Morningstar Accelerates Validations and Resolutions for Key IP With Monte Carlo

How Much Does Bad Data Cost You?

Do you know the cost of data downtime? This guide will help you calculate the cost of bad data for your company.

Download

How Axios Is Delivering Reliable AI with Agent Observability

How Pilot Flying J Scales Production AI with Monte Carlo

How T. Rowe Price Reduced Time To Resolution 83% with Monte Carlo

How M&T Bank Scales Trusted Data With Monte Carlo

How Calendly Reduced Data-Related Bug Tickets 40%

Announcements

Enterprise AI Confidence with Atlan + Monte Carlo

Data Observability, ML Model, and Agent Observability In A Single Pane Of Glass

Discover All Cortex Agents In A Single Click: Agent Observability for Snowflake Intelligence

From Insight to Action: Operations Agent is now Generally Available

Monte Carlo Named to G2’s Best Software Products of 2026

Debug Problematic Agent Behavior 4x Faster with Agent Observability

What is AI-Ready Data? Redefining AI-Ready for Production.

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

AI Observability Tools

What’s AI observability, when do you need it, and what are the best tools to deliver reliable data and agents at scale? Check out our list of 17 AI observability tools.

Learn more

Redefining AI-Ready Data for Production

AI-ready data is about more than what you do before deployment. Find out how to implement an operational model that will enable you to drive AI reliability and adoption in production.

Learn more

Data testing vs. data quality monitoring vs. data observability: What's right for your team?

In the fight against bad data and broken pipelines, there are a few popular options. But what makes the most sense for your data quality needs? We’ve got the answers.

Learn more

The Agent Trust Blog

Most recent

The 5 AI Agent Evaluation Metrics Every Team Should Be Tracking Right Now

Data trust used to come after the fact. With Claude, it ships with your code.

Built for the enterprise, ready for AI: Under the hood of Monte Carlo’s platform updates

Featured

New Monte Carlo Research: Two-Thirds of Orgs Ship Agents Before They are Ready to Support Them

The Memory Problem Changes When Agents Stop Waiting to Be Prompted

Enterprise AI Confidence with Atlan + Monte Carlo

Editors picks

What is AI-Ready Data? Redefining AI-Ready for Production.

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Data Quality Statistics & Insights From Monitoring +11 Million Tables in 2026

Build vs. buy: The real token economics of agent observability

Your Data Isn’t as Clean as You Think. Here’s How Data Quality Automation Helps

How to make Claude a trusted analyst for your whole company

Claude and Cursor Can’t Do Data Right

Monitoring Cortex Agent Performance With Trace Data

AI Observability

Garbage data, garbage agents: Scaling your Cortex Fleet starts here

What it takes to trust AI in production: Lessons from Salesforce and Dropbox at Snowflake Summit

How Monte Carlo’s agentic observability caught a $16K/day bug in our own revenue data

Integrating trust into the Agentic Control Plane: Observations from Snowflake Summit

Axios at Snowflake Summit: Building a Culture of AI Trust with Monte Carlo

Why AI agents fail in production, and how to fix them with Monte Carlo and Snowflake

Data Platforms

What is a Data Platform and How Do You Build One?

Open Source Business Intelligence Tools

Cheat Sheet: A Data Leader's Guide to Data Metrics

What Is Model Context Protocol (MCP)? A Quick Start Guide.

Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences

Data Warehousing Guide: Fundamentals & Key Concepts

The Future Of Business Intelligence: 5 Trends To Watch In 2026

AI Culture

Going Agent Experience First: What We Built, What We Broke, What We Learned

The Ultimate Guide to Data Product Management

What the EU AI Act Actually Requires (And Why Your Current Solutions Won’t Get You There)

We Went All In on AI. Here’s What We Shipped in Just One Week.

Trading Places in Financial Services: How Accountability Changes Seats in Agentic Systems

When Agents Manage Agents, Blame Disappears. Consequences Don’t.

Know Before You Go: Gartner Data & Analytics Summit 2026

Data Reliability

The Ultimate Guide To Data Lineage

Data Contracts 101: What They Are, Why They Matter, and How to Implement Them

2023 Modern Data Leader's Playbook

The New Dictionary of AI Reliability

Monitoring Through Disaster: Why Multi-Region Hosting Matters

Data Remediation: Ensuring Data Quality and Reliability in Modern Data Pipelines

Data Munging That Actually Works

Data Discovery

6 Tips For Better SQL Query Optimization

Star Schema vs. Snowflake Schema: Which One Should You Use?

The Best Snowflake Orchestration Tools

Data Catalog vs. Data Dictionary: 5 Essential Differences

Tired of Broken Pipelines? Here’s How ETL Orchestration Can Help

Messy Files and Confused Teams? You Need Product Data Management

Case Studies

Morningstar Accelerates Validations and Resolutions for Key IP With Monte Carlo

How Much Does Bad Data Cost You?

How Axios Is Delivering Reliable AI with Agent Observability

How Pilot Flying J Scales Production AI with Monte Carlo

How T. Rowe Price Reduced Time To Resolution 83% with Monte Carlo

How M&T Bank Scales Trusted Data With Monte Carlo

How Calendly Reduced Data-Related Bug Tickets 40%

Announcements

Enterprise AI Confidence with Atlan + Monte Carlo

Data Observability, ML Model, and Agent Observability In A Single Pane Of Glass

Discover All Cortex Agents In A Single Click: Agent Observability for Snowflake Intelligence

From Insight to Action: Operations Agent is now Generally Available

Monte Carlo Named to G2’s Best Software Products of 2026

Debug Problematic Agent Behavior 4x Faster with Agent Observability

Editors picks

What is AI-Ready Data? Redefining AI-Ready for Production.

The Top 5 AI Reliability Pitfalls

In the AI Kingdom, Experience is King

Related resources

AI Observability Tools