Derek Lin - Product Manager

Product Manager turning complex workflows into products teams can scale.

I’ve spent the past four years untangling healthcare workflows, building operational products, and introducing automation and AI into systems used by frontline teams.

Start with understanding Real product problems are shaped by people, workflows, constraints, and incentives - not just feature requests.
Build on evidence Strong recommendations are built by connecting signals across users, operations, business priorities, and engineering.
Make tradeoffs visible Every recommendation creates tradeoffs. Good product decisions make them explicit.
Learn continuously Shipping isn't the end of the process. Every launch creates evidence for the next decision.

Selected work

Major initiatives shaped by messy real-world workflows

Deep case studies about ambiguous systems, consequential product decisions, and the tradeoffs that shaped the outcome.

Mini cases

Focused examples of smaller product decisions and their operational impact.

How I think

A working model for finding the problem beneath the request.

This way of thinking came from working inside complex operational systems, where the request on the surface rarely captured the full problem underneath. I use it to connect the lived workflow, the system behavior, the available evidence, and the decision in front of the team.

WORKFLOW

Get inside the work

I map the official process, then look for the handoffs, exceptions, and workarounds it leaves out. When shadowing is not enough, I learn the job by doing it.

FRAMING

Separate the request from the problem

A feature request is evidence, not the answer. I keep widening the frame until the visible symptom, underlying constraint, and actual user need are distinct.

JUDGMENT

Make the tradeoff explicit

I turn competing perspectives into a recommendation: what it enables, what it costs, what must be true, and what the team is deliberately leaving for later.

LEARNING

Let evidence change the model

A target is not a baseline, and launch is not the end. I use outcomes, operator feedback, and edge cases to revise the product and the assumptions behind it.

Working with me

A point of view teams can examine and improve.

I make disagreements concrete.

I translate across operations, engineering, data, leadership, and external partners without flattening the differences that matter.

I bring a recommendation.

I show the evidence behind it, the tradeoffs it creates, and the conditions that would change my mind.

I choose the tool after understanding the work.

I use AI where interpretation and scale justify it, and simpler automation where a deterministic system is the better product decision.

I stay with the decision after launch.

I document why it was made, watch how it behaves in the real workflow, and treat maintenance and edge cases as product work.

Contact

Let's talk about the product problems your team is navigating.

Bay Area based. Open to Product Manager roles focused on complex workflows, enterprise platforms, healthcare technology, and AI-enabled operations.