3d ago · 6 min read · Startups today are building products in an environment where speed is everything, but so is reliability. This becomes even more critical when artificial intelligence is involved. Unlike traditional so
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Apr 29 · 59 min read · How do you write a test for a response that is confidently wrong? This is the most urgent open question in software quality right now — and most teams have no answer. Target Audience: AI Engineers ·
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Apr 21 · 18 min read · tldr: Every article ranking for "software testing strategies" lists the same eight strategy types from a 20-year-old syllabus. Those categories were invented when writing a test cost a day of engineer
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Apr 20 · 7 min read · How to Test Agentforce Agents the Right Way You built your first Agentforce agent. It handles cases, routes requests, maybe even drafts email responses. It works great in your demo. Then it hits production and tells a customer they're eligible for a...
Join discussionApr 17 · 25 min read · tldr: The AI testing market has split into four distinct philosophies. Expect generates tests from your git diffs inside coding agents. Agent-Browser gives AI models a fast Rust-powered browser. Stage
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Apr 17 · 18 min read · tldr: Playwright 1.59 ships the Screencast API, browser.bind() for shared browser sessions, CLI debugging for agents, and await using for automatic cleanup. It's the first release designed around AI a
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Apr 17 · 7 min read · How to Test Agentforce Agents the Right Way You built your first Agentforce agent. It handles cases, answers questions, and even routes customers to the right team. It works great in your demo. Then it hits production, and suddenly it's telling cust...
Join discussionApr 17 · 7 min read · Agentforce Testing Center: How to QA Your AI Agents You built your first Agentforce agent. It handled a few test conversations in the preview panel and everything looked great. Then you deployed it, and within a week, tickets started coming in. The ...
Join discussionApr 15 · 4 min read · Most people talk about machine learning as models and algorithms.Today I learned something far more important: ML systems fail not because models are weak — but because quality is ignored across the
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