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Thrive TRM’s AI Capabilities Turn Years of Executive Search History Into Faster, Smarter Hires

The executive talent platform built for private equity and venture capital, in-house teams, and search firms is now available with secure AI that compounds intelligence with every search. PHILADELPHIA — Thrive TRM today launched a significant evolution of its executive talent platform, introducing secure AI capabilities that activate the proprietary relationship data, search history, and […]

We haven't written up this one. Financial Post has the full story — the link below goes straight to it.

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How Do You Threat-Model an Application That Uses Autonomous AI Agents?

You spent years building a threat model you trust. You know your trust boundaries, you've mapped your data flows, and your team can recite STRIDE in their sleep.

  • Autonomous AI agents act on untrusted input, unlike traditional software.
  • Prompt injection is the new SQL injection risk for AI agents.
  • Threat modeling must include agent, tools, and memory as assets with trust boundaries.

I finally cut AI context bloat by 80% and the fix was embarrassingly simple

A few months ago I watched an agent do something deeply cursed. It had already fetched the data. It had already parsed the data. It had already stored the useful fields.

  • AI agents previously included entire raw tool responses in subsequent model calls
  • Solution was to store full results in structured state outside the model
  • This change improved agent quality and efficiency significantly

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