Algorithm & Blues
AI research translated into decisions executives can actually make. One clear argument per issue, published weekly.
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Published every Sunday since May 2025. No hype, no filler, one clear argument per issue.
MCP's Attack Surface Is Broader Than Most Teams Realize
MCP has become common infrastructure for agentic systems fast. A new paper maps 23 attack vectors across the protocol, tools, agents, and environment — and finds no single defense covers more than a third of them.
Benchmark accuracy is getting better, but reliability — consistency, robustness, predictability — is not keeping pace. A Princeton study across 14 models and 18 months of releases shows why that distinction matters.
The prompt still matters, but it's only one part of the system. Once agents carry state, retrieve information, and hand work off, what drives behavior is the context surrounding the decision, not the instruction that started it.
There's a pattern behind most self-improving AI systems: the agent improves, but the thing evaluating it doesn't. A new approach drops that constraint entirely.