Tag: AI
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Harness Engineering: The Real Differentiator in Agentic AI
Prompts and context are table stakes. Reliable AI comes from the harness: validation, state, controlled execution, permission boundaries, and observability.
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AI Strategy Theater Is a Liability (Here’s What Works Instead)
Most AI strategy today is optics. Real ROI comes from redesigning workflows, tying AI to revenue outcomes, and building governance before you scale.
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If You Don’t Have Observability, You’re Not Doing AI
AI systems rarely fail loudly. They drift quietly. Observability is how you catch data and model issues early, tie performance to business impact, and avoid “it worked yesterday” disasters.
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NemoClaw vs. OpenClaw: How Agentic AI Becomes Enterprise-Ready
Agentic AI is shifting from generating content to executing workflows. Here’s why that changes the risk model, what OpenClaw enables, what NemoClaw adds for governance, and what enterprise leaders should do next.
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AutoResearch: the autonomous loop that breaks the 90-minute priority meeting
Two engineers walk into a planning meeting. One brings a 6-month backlog. The other brings an autonomous loop that just ran 100 iterations of research. Guess who gets budget. What AutoResearch actually is AutoResearch isn’t a tool. It isn’t a model. It’s a methodology: a loop where AI defines the problem, proposes directions, tests them
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AI Customer Service Isn’t a Win If Customers Like You Less
AI support can resolve issues while quietly destroying loyalty. If customers like you less afterward, it’s not a win—no matter the resolution rate.