Charlie Fuller · AI in customer success

AI in customer success, mapped.

What’s solved, what’s a trap, and where the edge is. Eight diagrams on one through-line: the risk math is code, the language is the model, and the trust is the moat.

Solved for drafting. Summarizing, surfacing, briefing, pre-call. The productivity layer a platform ships — and the ceiling it hits.
Not solved for prediction. Churn forecasting fails on context. The agent that reads the account weekly and hands the CSM a call they can defend.
Code decides, model narrates. The risk math stays deterministic and auditable; the LLM only writes, grounded and human-gated.
Trust is the moat. Shipped evidence, not claims. The agent never sends; a human does. Outcome measured in revenue, not hours.
Deterministic code-first Human above the loop Grounded cites the signal Honest eval 85.7%, not 100%

The fix is four moves, and the agent is all four.

Start here: the health agent → Read the territory →
The story
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