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LinkedIn’s product evolution and the art of building complex systems | Hari Srinivasan (LinkedIn)

Hari Srinivasan is VP of Product at LinkedIn Talent Solutions, where he oversees LinkedIn Recruiter, LinkedIn Jobs, and LinkedIn Learning. He’s also a frequent guest lecturer at Stanford University.

Hari SrinivasanguestLenny Rachitskyhost
Jul 15, 20231h 4mWatch on YouTube

Summaries, chapters, transcripts, and FAQs on this page are made by uListen, not YouTube.

At a glance

WHAT IT’S REALLY ABOUT

LinkedIn’s skills-first revolution and secrets to managing complex products

  1. Hari Srinivasan, VP of Product for LinkedIn’s Talent Solutions, explains how LinkedIn is evolving from title-based to skills-first hiring and how this shift is reshaping the global job market. He details how LinkedIn navigated COVID-era dislocations (e.g., moving hospitality workers into customer service roles) and how features like Open to Work, company interest signals, and skills profiles increase hiring odds. Hari also breaks down how LinkedIn manages an extremely complex, interconnected product ecosystem through clear mission alignment, decision frameworks, and marketplace thinking. Finally, he discusses LinkedIn Learning, his internal PM ‘university’ turned public course, career advice for aspiring PMs, and his personal bias toward building and side projects.

IDEAS WORTH REMEMBERING

5 ideas

Embrace skills-first positioning on your LinkedIn profile.

Recruiters increasingly search by skills rather than titles (Hari cites ~47% explicitly using skills), so explicitly add and evidence skills on your profile—attach work samples, recommendations, and credentials tied to each key skill.

Use LinkedIn’s intent signals: Open to Work and company interest.

Turning on Open to Work and marking yourself ‘interested’ in specific companies and job types creates high-signal intent markers in Recruiter, substantially improving your chances of being surfaced and contacted.

Target roles where you have relevant industry context, not just PM skills.

For breaking into PM or moving up, Hari recommends focusing on domains where you already understand the industry (e.g., automotive, healthcare); domain expertise meaningfully differentiates you among many similar applicants.

Think and design in systems and loops, not isolated features.

At LinkedIn, every product change interacts with multiple marketplaces (members, recruiters, learners, advertisers), so PMs must reason about second- and third-order effects and design flywheels and loops rather than one-off optimizations.

Anchor decisions to a clear mission and explicit decision-owners.

LinkedIn consistently uses its mission—‘connect people to economic opportunity’—as the north star in product reviews, and operationalizes complex decisions through frameworks like RAPID (clear DRI) and a five-day escalation rule to avoid stalemates.

WORDS WORTH SAVING

5 quotes

We made a pretty big push in something we call skills-first hiring.

— Hari Srinivasan

Everything at LinkedIn is a very connected ecosystem… but we make decisions based on how we’re connecting people to economic opportunity.

— Hari Srinivasan

I remembered at that point, if you're gonna go in and you only have one more shot, just do something you believe in.

— Hari Srinivasan

I’ve actually never seen a great PM who’s in the center of that triangle. I find that great PMs live on the edges.

— Hari Srinivasan

As long as we stay focused on that [mission] and each of our decisions start moving in that direction, hopefully the product will continue to deliver.

— Hari Srinivasan

Read the available transcript
Shift from title-based to skills-first hiring and its impactHow LinkedIn’s feed and content strategy evolved to be more valuableDesigning and operating complex, interconnected product ecosystemsLinkedIn features and tactics to improve job search outcomesLinkedIn Learning and Hari’s product management courseCareer advice for aspiring and current product managersLinkedIn’s culture, mission (“economic opportunity”) and decision frameworks

High quality AI-generated summary created from speaker-labeled transcript.

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