Systems | Development | Analytics | API | Testing

Who's Responsible When AI Gives You the Wrong Answer? Andy Cotgreave and Francois Lopitaux Debate

If an AI agent gives a business user the wrong number, and a consequential decision gets made off it, who's responsible? The data analyst who built the semantic layer? The platform? Or the business user who asked the question and acted on the answer?

Connect AI Agents with MCP | Do It Better with FME & Snowflake

See how AI agents use Model Context Protocol (MCP) with FME to connect complex enterprise and spatial data to Snowflake. In this episode of Do It Better with Snowflake, Safe Software CEO Don Murray demonstrates how FME extends Snowflake Cortex AI Agents with FME workflows for data integration, transformation, and spatial analysis. See how Snowflake + FME can help you: Connect complex data: including GIS, CAD, 3D, LiDAR, BIM, ERP, and unstructured data.

Snow Report: What's Happening At Snowflake in August

The August Snow Report is LIVE Two GA launches for CoCo, warehouse tuning that handles itself, and World Tour in 23 cities. What's new CoCo Desktop is GA A native IDE inside your governed Snowflake environment, so it knows your data models and access policies from day one. Up to 2X faster on complex tasks with 51% fewer tokens than third-party assistants. Cloud Agents are GA Run agentic workflows from your browser in Snowsight. Start with a prompt, close your session, and the agent keeps working on Snowflake's managed infrastructure.

How to fix API contract drift with AI agent skills | SmartBear Swagger Contract Testing

Your AI coding agent can already write code. Can it verify a contract, run provider checks, and tell you whether it's safe to deploy? This video shows you how to set up SmartBear Swagger Contract Testing drift AI Agent Skills, so your agent can spot API drift and write the missing tests for you, without needing the context multiple times.

Claude + MCPs Isn't a Semantic Layer: What Breaks When You Analyze Your Business Without One

Ask Claude for your average sales cycle today. Ask again next Tuesday. Same prompt, same MCPs, same playbook. There is a real chance the two numbers do not match. The reason is not exciting, and it costs you decisions. If you have wired Claude to your CRM, product, and finance tools through MCPs and given it a detailed playbook, you are already ahead of most companies asking whether AI can analyze the business. The gap between that and running the company off the answers is real, though.

Agent Product Use Case - Slack & Jira Discrepancy Workflow

Customers and champions report problems in Slack, but if nobody files the ticket, the issue disappears before it ever reaches Jira. In this video, we use AgentSpot to build a Slack to Jira Coverage Workflow that reads your champions channel every morning, cross-compares it against your Jira backlog, and emails you a report of every issue raised in Slack that no one has filed yet. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.