AI made your team faster. It didn’t change how your company runs.

I embed with your team, find where the work actually breaks, and build the fix where people already work, one function at a time.

I’m Sarah Wissel. A product-minded founder and startup leader. I’ve run product and engineering orgs as well as the teams that talk to customers.

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What I build

Systems, not one-off automations

Examples of what I’ve designed and built, alongside the teams who run them, inside the tools they already use. What each company needs is different, but the patterns are the same.

Product ops

Automated product operating cadence

Problem

Nobody owns product full time, so planning starts from a blank page. Everyone has AI and the rhythm hasn’t changed: prioritizing, sizing, and writing the update are all still manual.

System

Planning walks in with a ranked, sized list, so the meeting spends its time deciding. Risk surfaces mid-cycle, and the recap and company update write themselves.

Engineering + Support

Support-to-engineering quality loop

Problem

Both teams use AI every day, and the handoff between them is still one person remembering to tell someone. A fix ships, support doesn’t know, the customer’s ticket sits on hold.

System

Triage starts from a draft. Support sees bug status without asking engineering. Every deploy names the customer to follow up with.

Leadership

Leadership visibility layer

Problem

What customers are telling you is scattered across tickets, sales calls, and product usage, so you find out the quarterly goal didn’t move after the quarter is already over.

System

Three pieces. A dashboard tracking the key result month over month, not activity. A weekly read on customer sentiment and the feedback themes showing up across support tickets and sales calls. A daily briefing across the tools the work lives in.

Org design

Operating system rebuild

Problem

Losing product headcount means backfilling fast or watching the work stop. The AI everyone already has doesn’t help, because the work lives in people’s routines instead of in the system.

System

The system carries what people used to carry: the cadence, the quality loop, the visibility layer. Roles get rewritten around what’s automated, so the work doesn’t depend on who’s in the seat.

Any function

Institutional knowledge layer

Problem

Your AI has access to the docs and none of the knowledge that actually resolves things. That part lives in people’s heads: the workarounds, the exceptions, what’s really true.

System

Mine the history once, split it into what’s officially true, how things actually get resolved, and how the best answers sound. One owner keeps each current.

About

Sarah Wissel

I co-founded Repeat, a software platform that helps CPG brands turn one-time buyers into loyal customers. When Tiny acquired us in 2024, Repeat folded into Stamped. I stayed on to run customer success and support, then became CPO over product, engineering, and support for a suite serving 10,000+ Shopify merchants.

I rebuilt how those functions ran, with AI at the core. Now I do that for other companies. The team is the user, so I build with them rather than for them: find where the work breaks, build the fix, own the outcome, then move to the next function.

I care about the problem more than the technology. Sometimes the right answer isn’t AI, and I’ll build the thing that is.

AI made your team faster. It didn’t change how your company runs.

Systems, not one-off automations

Automated product operating cadence

Support-to-engineering quality loop

Leadership visibility layer

Operating system rebuild

Institutional knowledge layer

Sarah Wissel

Learning in public

Strip AI

Claude Setup Builder

Last Week, Reviewed

Think Bigger

If you want to change how your team works with AI, let’s talk.