What should an AI agent write back to Salesforce after a sales call?
Mila Chen
RevOps teams
I am trying to get a realistic read on what should an AI agent write back to Salesforce after a sales call.
Cover summaries, next steps, MEDDIC fields, risks, and evidence.
What has actually worked (or failed) for your team? Specific examples, pricing traps, or vendor claims that did not hold up are especially useful.
Yara Mendes
Senior engineer
Source quality beat model size for us. Clean knowledge + tool scopes fixed more hallucinations than switching models.
Cass Ortega
RevOps practitioner
Start with one bounded workflow that has a clear success metric. We tried to automate three use cases at once and none of them got good enough to ship.
Leo Park
Customer success lead
The vendor demo is not the product. Ask to see the same workflow run on your data, not their sample data. That is where connector gaps and permission issues show up.
Imani Brooks
Strategy & architecture
Measure rework, not just throughput. An agent that resolves 80% of cases but creates 30% more manual cleanup is not saving time.
Felix Kron
RevOps practitioner
We learned the hard way that 'human in the loop' is not a checkbox. If the approval UI is buried or slow, reviewers will batch-approve without reading.
Hana Ishikawa
Research analyst
Security questions should be part of the first demo, not a procurement afterthought. Ask about retention, sub processors, prompt-injection testing, and audit logs before you waste time on a trial.
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