Building Trustworthy AI for GTM Workflows
AI Engineer · youtube · 2026-07-11
This talk focuses on AI reliability in GTM scenarios, highlighting that the core issue isn't just AI making things up, but generating plausible yet incorrect results.
Speaker Alex Bauer shares several practical approaches used at Upside:
- Assigning a librarian to every agent, acting as a business knowledge and context verification layer that must be consulted before taking action.
- Using a jury + judge mode for tasks where a single answer isn't reliable enough, especially for high-risk subjective judgments, allowing multiple perspectives to review together.
- Clearly identifying tasks that models are inherently unsuited for, avoiding their use in scenarios where they lack capability.\n
The video also includes live demos and real-world failure cases. The overall theme is designing AI workflows to mitigate hallucinations and misjudgments in high-stakes tasks like revenue, attribution, and GTM data.
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