Operating Memory Lead

About the role

The bet - turning human judgment into compute - has a precondition: the judgment has to be written down. AI doesn't magically understand a company. It works only when the business is documented clearly enough for systems to retrieve the right context, recognize the workflow, handle the edge cases, and escalate when a human is actually needed. Right now most of Harper's operating knowledge lives in people's heads: how a top rep prioritizes quotes, how service handles an edge case, which underwriter to chase, what a customer really means when they push back at bind, why a workflow changed yesterday. That works at small scale and breaks at ~1,000 new customers a month. The next bottleneck here isn't engineering - it's knowledge. Every process that lives only in someone's head is a future failure mode. Every undocumented edge case is rework. A workflow that isn't clear enough for a new hire isn't clear enough for an AI agent either. You turn that messy operating reality into structured, AI-legible knowledge - and make sure Harper's knowledge compounds instead of disappearing.

Responsibilities

• Capture tribal knowledge. Embed with sales, intake, service, placements, and renewals. Sit with operators, shadow workflows, listen to calls, read transcripts, and document what people "just know."
• Build operating memory. Turn transcripts, Slack threads, Looms, and one-off explanations into source-of-truth docs, decision logs, playbooks, process maps, onboarding paths, and glossaries.
• Use AI as a force multiplier. Build repeatable workflows that turn raw context into decisions, owners, open loops, SOPs, training material, and product requirements.
• Find the edge cases. Document where workflows break - reworks, escalations, stale quotes, underwriter follow-ups, payment/binder gaps, COI delays, customer confusion.
• Translate ops into product. Sit between operators and engineering; capture what people do, where tools fail, what workarounds exist, what needs to be built.
• Maintain the knowledge base. Keep docs current, assign owners, kill stale guidance, make sure people know where the truth lives.
• Turn repeated problems into systems. If the same issue happens three times, it becomes a playbook, a QA check, a training artifact, or a product requirement.

Requirements

• An exceptional writer and synthesizer who can turn a messy transcript into a clear operating doc the same day.
• Curious about how organizations actually work, and you like sitting with operators.
• You notice hidden assumptions, missing ownership, and contradictions other people walk past.
• Structured but not bureaucratic; you care whether documentation changes behavior, not whether it looks polished.
• Low-ego, persistent, and allergic to "someone should probably document that."

Additional Information

Operating Memory Lead Harper is an AI-native commercial insurance company in San Francisco. We're not bolting AI onto insurance - we're rebuilding the entire business as software, on a simple bet: turning expert human judgment into compute is one of the largest transitions left to make, and a trillion-dollar industry still run 90% by hand is the place to prove it. We've grown ~100x in the last year and we move at that speed - on-site, in person, long days, very high standards. Almost no one joins Harper for insurance ; they join to build the company that replaces how it works.

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