Brian Tolkin

AI collapses the product development funnel but not the PM job. Brian Tolkin’s core claim: the PRD-to-Figma-to-code relay compresses into “let’s just build a prototype, let’s skip the documents stage” — yet the actual skill, “you got to go talk to users, you got to go figure out what people want… and how do I know type one from type two decisions,” doesn’t change in a pre- or post-AI world. The tool chest gets bigger; the judgment stays scarce.

On the AI skill curve, host and guest split then converge: Brian says engineering becomes more important; Harry argues less, because tooling commoditizes everything below “top 1% performance-based model optimization” while design pros pull away from AI’s “good enough.” Brian’s synthesis is the tradeable line: “the top 1%, the top 5% of all of the skill sets get a lot more valuable and the median gets a lot less valuable.”

Tech debt at Series A is probably premature: posed a hypothetical $2M→$8M company, Brian’s answer is that at that stage it is probably too early to pay it down — “you have to earn the right to exist in the future, and paying down tech debt doesn’t pay the bills.” In a land grab (Uber for years), velocity philosophy wins; slowing down early to pay down debt is “a bit challenging.”

Multi-product has a 2x2: new products need a contained sandbox (Uber/Opendoor can do it by city; Uber Eats was “totally separate everything”), and the second product needn’t benefit the first — but new customer set plus new capabilities “is probably just a new company.” Opendoor’s own miss: years building buyer-side (retail buying, mortgage) when the win was existing customers/new capabilities — “the right to win for sellers is where a lot of the magic is.”

Consensus product decision-making is “challenging and wrong.” Brian’s middle path between Spotify CPO Gustav’s “talk is cheap so we should do more of it” and Harry’s “dictatorial product leadership is underrated”: gather every opinion, then decide — “slow decision making is expensive… very rarely does a slower decision lead to a better outcome.” Disagree-and-commit works for a sprint, not a career: “if I’m disagreeing and committing too much… I’m in the wrong place.”

“You hire your strategy”: the person you pick defines how success gets defined, so hire for PM-team fit (a mathy PM for an algorithm product, a tinkerer to energize a staid team), not generic smarts. Failed hires are “never just the responsibility of the person being hired” — it’s unclear success criteria, wrong skill-set match, or ambiguity above the person’s ability to distill.

Best and worst Uber Pool decisions bookend the episode: best was upfront pricing (replacing post-hoc minutes-and-miles calculation); worst was defaulting riders into Pool even after they’d chosen UberX — “we prioritized the needs of the business above… respect for the user’s choices,” a lesson he says he deeply internalized.

🔗 Original source & video: Brian Tolkin, Head of Product @Opendoor: How to Hire the Best Product Teams | E1257