HeyJaredSuneet Malhotra
- Indexed articles, last 90 days
- 4
- Latest publication
- Sep 17, 2026
- Outlet visibility, for InfoWorld
- Top 500K sites
- Earliest in this view
- Jul 15, 2026
Latest articles
Your AI testing dashboards are green. That’s the problem (opens the original)
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The green dashboard is one of the most comforting objects in software engineering. It says the build passed, the tests passed, the service is healthy and the incident queue is quiet. When an AI agent is writing code or repairing tests, though, those green signals can become dangerously local. Each layer can report success while the system’s actual behavior drifts away from what a human intended. I have seen this most clearly in test automation. A locator breaks. An automated repair finds a nearb
Nobody's agent fleet fails the way the vendors say it will (opens the original)
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I run 49 scheduled AI agents on one laptop. Another 24 sit beside them, deliberately switched off. That distinction matters more than it sounds. After eighteen months, I have stopped being surprised by model errors. Models misunderstand requests and occasionally produce confident nonsense. I expect that. I test for it. What still catches me is how rarely those errors cause an outage. No serious failure in my fleet has started with a bad model answer. They start lower in the stack: a job never lo
Shipping an MCP test agent: The boring parts nobody demos (opens the original)
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The demo videos always end at the same moment. A figma frame turns into a passing test in twelve minutes. Someone in the room says the word “productivity.” The recording stops. The parts that come after that moment are the parts I actually get paged about. Who owns the ticket the agent opened at 3:14 a.m.? Which model call produced the assertion in test case 47? What closes the 17 draft tickets a stuck run left behind before the next sprint planning notices them? None of that shows up in the dem
What 80% AI-written test pipelines actually cost (opens the original)
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The first time I heard someone say their AI now wrote 80% of their tests, I asked the obvious question. Eighty percent of what? After 20 years building and leading test automation for consumer-scale platforms, my honest answer turned out to be eighty percent of the typing, not eighty percent of the engineering. The remaining twenty was where the work still lived. Budgeting for two percent of leftover effort was the mistake. When the real number was closer to thirty, that gap was the difference b
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