01The shift
SyncSmart builds data-integration products — connecting HubSpot, NetSuite, ConnectWise and adjacent platforms — and when core team members left, I became effectively the whole customer-facing function: solutions, support, escalation, partnerships, and the communication that holds it together. The honest problem was capacity. That much surface area normally needs a team, and the reflex answer is to work longer hours and hope. I did the opposite: I changed the operating model so one person could actually run it.
02The hub
I connected Claude to the systems the operation actually runs on and made it the hub the work flows through — data flowing in, drafted actions flowing back out. I'm the one driving it; the hub is what lets me be in every system at once.
One hub, eight systems. I direct it; it reaches the systems I can't sit inside all at once — reading their data, drafting the action, handing me the last-mile judgment.
Each connection does real work. Pylon is the support source of truth for customer relationships and issues; HubSpot is the CRM context behind every account; Gmail is where drafts get written and where a daily scan surfaces threads I haven't closed; Slack gives full channel-and-DM overview with replies staged in place; Linear is our engineering and escalation source of truth — 83 tickets filed through it this year, close to ten times my pre-April pace; Fathom and Zoom recordings and transcripts turn calls into follow-ups, communication and tickets; Google Calendar and Drive keep the schedule and the documents in reach. And MongoDB — reading the product's own configuration and activity data — is the one that changed what I can do on my own.
03What the hub lets me do
The connections aren't the point — the leverage is. With the stack wired together, a handful of things that used to be impossible for one person become routine:
- Diagnose past my native depth. I read production configuration and activity data straight from the database and have it extracted and analyzed in seconds — work that would have taken me hours by hand, if I could do it at all.
- Stay ahead of the customer. A daily operations scan across the inbox surfaces unresolved topics and threads before they turn into escalations. Nothing quietly slips.
- Turn every call into action. Recordings and transcripts become drafted follow-ups, clear communication, and filed tickets — so conversations reliably convert into next steps instead of good intentions.
- Feed engineering clean work. Escalations reach the engineering queue with a root cause and evidence attached, not a symptom — so their time goes to fixing, not triaging.
- Document as I go. I've used the hub to document our integrations and publish customer support articles — contributing to a knowledge base of 92 articles across 10 product lines, including authoring the ConnectWise+HubSpot onboarding series. It's also how I got comfortable running scripts locally and living in the terminal.
04Where it earns its keep
The hardest version of this work is a production defect on a live customer's integration — and it's where the hub proves itself. Take a recent one. An enterprise customer's parent-company associations had silently stopped syncing. Working through the hub, I traced the deployed configuration in the database, pulled the parent-association subflow out of a 3.7 MB workflow export, read the connector scripts, and separated three distinct defects — handing engineering six tickets that named the exact properties and code locations.
Active human attention came to a few hours across a handful of days — most of it pasting logs, checking records, and making calls. Blind to the connector internals, that's an estimated three-to-five-day investigation solo, and the deep code-tracing likely wouldn't have been finished at all — it would have reached engineering as "associations don't work," no root cause attached. One clean 16,132-record historical re-sync even ran unattended overnight on scheduled check-ins, instead of someone watching a progress bar.
And it's a pattern, not a one-off — other production defects taken the same route:
- Silent data loss in the mapping UI — an unguarded state-sync effect was wiping unsaved work on every re-render, fired by the connection-status poll. Routed to engineering as a scoped fix.
- Empty invoice syncs — an unmapped field threw and killed the entire line-item batch after the deal was already created. Corrected the mapping; the whole class of silent failure now surfaces in the logger.
- A field overwritten with null — an API key missing read permission returned an empty source that clobbered good data. A permissions fix, not a sprint ticket.
- Custom fields that wouldn't load — queried the production database, found the property cache held only 6 of ~15 record types from two partial runs, and escalated with an evidence-backed schema-timeout hypothesis.
Each one left my hands as a scoped ticket or a config fix — not a mystery for someone else to untangle.
05Why it matters
The result isn't a single number — it's a change in altitude. One operator now covers ground that would normally take a team, with more rigor rather than less, because the hub reads the actual code and data before anyone makes a call.
The clearest tell is a clean before-and-after in one system. My engineering-ticket filing went from roughly ten in the first stretch of the year to about seventy-three once I was working this way — close to a tenfold jump, same person, same tools.
Engineering tickets filed, before and after I wired Claude into the debugging loop. Same person, same system.
06What I'd take forward
This is the shape of how I work now, and how I'd run product or operations at a company hitting its own capacity wall. AI leverage doesn't replace the operator — it raises the ceiling on what one operator can hold. The organizations that figure this out early get a step-change in output per person; I've already built the playbook for it, on live customers, under real stakes.