Product Lead

Seed-stage AI startup

Outcome

MVP shipped to first 10 customers in 8 weeks

Client context

Two co-founders, both with backgrounds in applied ML at larger AI labs, had raised a $3.2M seed nine weeks before they reached out. They were building agentic workflow automation for operations teams inside mid-market companies, with an initial wedge into finance ops. The team was six people: two founders, three engineers, and a part-time technical writer. They had 14 design partners signed under a no-cost pilot agreement, and roughly half of those had committed to a paid conversion if the product crossed the line on three specific use cases by end of quarter. The founders had been doing customer calls themselves, taking notes in a shared Notion, and shipping a new internal build roughly every nine days. The pace was real, but the loop between customer conversation and committed roadmap was breaking. Two of the design partners had quietly gone cold because nobody had followed up on commitments made in earlier calls.

The challenge

Both founders had strong technical instincts and one of them had real product taste, but neither had the bandwidth to run customer development at scale or own a roadmap that the engineering team could plan against. They had interviewed four product hires through their investor network. Two were senior PMs from public companies who balked at the idea of writing Loom walkthroughs themselves. One was a former founder who was great in the first conversation but failed the working session because he kept reframing the company's wedge instead of executing against it. The fourth wanted equity and a title that did not match the stage. The lead investor told us bluntly that this was the highest-leverage hire of the year. The wrong person would burn six months of runway and lose at least three of the design partners. The right person would turn a pilot book into paying customers before the next round.

Search strategy

We scoped the role tightly around shipping cadence and customer development, not strategic vision. The scorecard required evidence of personally running at least 30 customer interviews inside the prior year and converting them into shipped, measured product changes. We sourced from seed and Series A AI companies inside the agentic, workflow-automation, and developer-tooling adjacencies, plus a small set of operators who had been the first product hire at a now-Series-B AI company. 38 candidates were mapped, 19 were approached, 9 took the first call, and 5 cleared a paid working session where they had to listen to two real anonymized customer calls and produce a one-week build plan. 3 finalists were presented on day 11. The hardest filter was not technical depth. It was finding candidates who would happily run a 45-minute support call themselves and then write the bug ticket on the way home.

Result

The new Product Lead started the following Monday and inherited a roadmap that lived across three Notion pages and one of the founders' brains. In her first two weeks she ran 12 fresh customer calls, restarted conversations with the two cold design partners, and wrote the first proper product spec the company had ever produced. Engineering started shipping against weekly demo milestones rather than ad-hoc commits. The MVP for the three priority use cases reached general availability for the design partner cohort eight weeks after her start date, exactly on the timeline she had committed to in week one. Ten of the original 14 design partners converted into paying contracts inside that window, with combined ACV of roughly $340K. The founders later told us the most valuable thing she did was force a written product spec into the workflow, because it ended the pattern of engineers building from memory of a Slack message. She is still in the seat heading into the Series A.