Proactive Customer Support

Standing agents per top account: scheduled value-showcase reports, post-meeting follow-ups, integration history, and "what changed since last touchpoint?" briefings on demand.

What it does

Each top account gets a per-customer working directory in the swarm's shared filesystem (agent-fs). An agent maintains running notes, integration history, open questions, and recent activity. On a cadence (or on demand), the agent produces a customer-facing value-showcase report: data-driven usage + outcomes framed in their language, not your internal feature names.

Agents

• Lead — receives the ping ("report for account X"), routes the data pull, runs the redaction gate.
• Researcher — pulls usage data from the product DB, behavior data from analytics, cross-references meeting notes.
• Forward-Deployed Engineer (ours is named Jackknife) — owns engineering-level customer questions and the technical-state side of the report.

Tools & Skills

Built-in (ships with agent-swarm)

• agent-fs — per-customer working directories. Persistent across sessions; each account accumulates institutional knowledge over months. See the Per-Customer Working Directories pattern.
• slack-post — internal handoffs + human review before send.

Custom (swarm-managed)

• agentmail-sending — sends the report from the swarm's verified AgentMail domain (signing + signature rules enforced).
• customer-value-report — two-stage flow: Stage 1 (internal) data-driven usage breakdown from the product DB; Stage 2 (customer-facing) strips internal jargon and reframes raw usage as outcomes ("you ran 1,200 E2E checks across 3 critical flows, catching 4 regressions before deploy").
• granola-api — fetches meeting notes/transcripts from Granola post-call; the agent ingests and updates the per-customer directory automatically.
• posthog-interaction (behavior via PostHog), clerk-analytics (account state via Clerk), turso-interaction (Turso-side state).

Third-party providers

• Granola — meeting notes/transcripts ingested automatically post-call.
• AgentMail — per-account inboxes; customer replies route back into the swarm.

Workflows / Schedules

These tend to be on-demand rather than scheduled — every top account has different reporting needs and cadence (monthly QBR vs. weekly check-in vs. milestone-driven).

The recurring pattern:

1. Trigger (Slack ping, calendar event, or a per-customer schedule).
2. Researcher pulls usage + behavior data into the customer's agent-fs directory.
3. Agent drafts the value-showcase report (Stage 2 of the skill).
4. Human reviews + edits in agent-fs.
5. AgentMail sends the final.
6. Replies route back via the per-account AgentMail inbox.

Post-call automation: a Granola webhook fires after every customer meeting → agent ingests the transcript → appends to that account's directory → flags follow-ups.

Patterns used

• Per-Customer Working Directories — persistent per-account context that compounds over months.
• HITL Gates — a human signs off before any direct-to-customer email.

Tips for new swarm users

• Per-customer working directories are the unlock. A 6-month-old note like "they care about EU data residency" is what makes the next report feel personal.
• Frame reports as outcomes, not features. "You caught 4 regressions" lands; "you consumed 1,200 credits" doesn't.
• Strip internal jargon before sending. A Stage 1 → Stage 2 split routinely catches internal project codes leaking into draft copy.
• Don't auto-send. Even with great drafting, a human signs off on any direct-to-customer email — that's your reputation insurance.
• Use AgentMail per-account inboxes so customer replies route back into the swarm for thread-aware follow-up.