Systems | Development | Analytics | API | Testing

Salesforce MCP: Is CRM Data Enough for Your AI Agent?

Connecting Salesforce to Claude via MCP is the advancement the SERP says it is. You authenticate once, your AI agent queries live CRM data, and you stop copying deal records into chat windows. For a Revenue Operations Manager who spent Q1 begging an admin to export pipeline snapshots, that matters.

How Xray's AI Test Prioritization Helps Teams Focus on High-Risk Tests

Test execution is one of the most time-sensitive stages of software delivery. Teams are expected to validate functionality, ensure stability, and support release decisions within increasingly shorter development cycles. Even with strong automation in place, there is rarely enough time to execute every Test before a release. This makes prioritization a critical part of the QA process.

Perforce Autonomous Testing for Web, Mobile & Desktop Apps

Traditional test automation is slowing teams down with brittle scripts, constant maintenance, and growing complexity. Perforce Autonomous Testing changes the game with enterprise-grade AI-powered testing that helps teams create, execute, maintain, and analyze tests using natural language—without scripts, frameworks, or ongoing upkeep.

Introducing the N|Solid Plugin for AI Coding Agents

AI coding agents have quickly become part of the daily workflow for Node.js developers. Whether you're using Claude Code, Codex CLI, OpenCode, Antigravity CLI, or Pi Agent, these tools are great at generating code, explaining implementations, and automating development tasks. But debugging production systems is a different challenge.

Best AI Visibility Tracking Tools (2026)

If your brand does not appear when buyers ask ChatGPT, Perplexity, or Google AI Overviews for recommendations, you are invisible to hundreds of millions of potential customers. ChatGPT alone now reaches 900 million weekly users. The shift is clear: buyers now get answers directly from AI engines rather than clicking through to websites.

AI tip #2: Improve pull requests with AI

AI tip: For pull requests, let your AI agent take the first pass before your team ever sees it. That's the workflow Ilia Mogilevsky, Software Engineering Manager at SmartBear, built. By packaging prompts into a skill loaded with Git history, Jira context, and CI checks, he turned a basic AI assistant into a reviewer he trusts. The skill then generates a structured report with approval-ready fixes. Accept the changes, adjust what's off, and push – review cycles shrink and deploys move faster.