Route AI Models By RevOps Risk, Not Vibes
RevOps teams should route AI models by workflow risk, not model preference, so cost, quality, permissions, and review match the job.
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9 min read
AI Sales Coaching Needs Call Type Labels Before Call Summaries
AI sales coaching needs call type labels before summaries, or managers get generic advice scored against the wrong sales motion.
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9 min read
You Can't Automate an Undefined RevOps Workflow
Define the RevOps workflow before adding AI. Otherwise automation speeds up bad handoffs, fuzzy permissions, and broken CRM logic.
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9 min read
What Should RevOps Teams Automate with AI First?
RevOps teams should automate repetitive, high-context workflows that humans can verify before they automate judgment or customer-state changes.
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8 min read
How to Use Claude Code for GTM Operations
Use Claude Code for GTM operations when the work is structured, artifact-based, and tied to a real operating question, not vague prompting.
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9 min read
How HubSpot Admins Should Use Coding Agents Without Breaking CRM Ops
HubSpot admins should use coding agents for bounded analysis, QA, and workflow drafting, not blind production changes.
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11 min read
Prompt Engineering vs Context Engineering: What Actually Improves AI Output?
Prompt engineering helps, but context engineering usually matters more once AI is part of repeated operator work.
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10 min read
How to Set Up a Claude Code Project Without Overbuilding It
Set up a Claude Code project by starting with one real workflow, minimum context, and one durable output artifact. Skip the theater.
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9 min read
AI Memory Layer for Workflow Automation: What It Is and Why It Matters
An AI memory layer is the durable context system that keeps repeated work from resetting to zero every session.
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8 min read
What Is AI-Ready RevOps Infrastructure?
AI-ready RevOps infrastructure is a Revenue Operations system with clear entities, stable definitions, governed fields, and reliable process context, so AI can support decisions without amplifying confusion.
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4 min read