Lessons in product leadership and AI strategy from Glean, Google, Amazon, and Slack | Tamar Yehoshua (Product at Glean, ex-Google and Slack)

**Tamar Yehoshua** (0:00)
Make sure you go somewhere where you have a good engineering partner, because if you have great ideas of what to build, but you can't get them built, then you go nowhere. So that has to be part of your evaluation criteria that you meet and value your engineering partner before you join. And then I think what's really important is that you're aligned. You understand your roles and responsibilities and where you're gonna divide and conquer and where you're gonna be aligned. You don't want any of this, like people in the organization, they ask mom, they ask dad, and they got different opinions and claim one against the other.

**SPEAKER_2** (0:31)
Like that doesn't work.

**Lenny Rachitsky** (0:36)
Today, my guest is Tamar Yehoshua. Tamar is currently president of Product and Technology at Glean, one of the most successful enterprise AI companies out there right now. Prior to joining Glean, Tamar was chief product officer at Slack for four years, where she led product design and research as the company scaled, 10x the revenue, went through IPO and then got bought by Salesforce. Tamar also led product and engineering teams at Google, where for many years she was responsible for the Google search experience. She also spent five years at Amazon as director of engineering and vice president at a9.com. She was also venture partner at IVP and has been on board of directors for ServiceNow, Snyk, RetailMeNot, and Yext. In our conversation, we get into all kinds of juicy advice, including why companies don't have to be run well to win, why you don't need a career plan, the two habits she credits most for helping her succeed throughout her career, what she learned from Jeff Bezos and Stewart Butterfield and Mark Benioff, how to build stronger cross-functional relationships, and a bunch of advice on AI, including how it will likely change your jobs, examples of how she and her colleagues are already using AI to be more productive in their work, and what she's learned about building AI-based products that are non-deterministic and can be very unpredictable. This episode is for anyone looking to level up as a leader and get a better sense of how AI will change your job. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes and it helps the podcast tremendously. With that, I bring you Tamar Yehoshua.
Tamar, thank you so much for being here and welcome to the podcast.

**Tamar Yehoshua** (2:15)
Thank you so much for having me.

**Lenny Rachitsky** (2:17)
I bet so many people recommend you coming on this podcast. I'm really happy that we're finally doing this. I want to start with a question that I've started to ask people who have had extraordinarily successful careers which you've had. So let me ask you, what are one or two specific skills or mindsets or habits that you think most contributed to your success during the course of your career that you think might be helpful to people who are trying to figure out how to accelerate their career or just be more successful in their career?

**Tamar Yehoshua** (2:47)
One of the things I think is overlooked is do a really good job at whatever your job is at that point. So people have a tendency, especially product managers are very ambitious and they want to get to the next level and they're always eyeing the next job, but you're not going to get the next job unless you do really well at the job that you're in. Like knock it out of the park, however simple, however easy it may be to you, do a great job. And in tech jobs, there's like table stakes. There's table stakes of you need to be technical, you need to know the latest technology, you need to understand your product, the product you're working on, no matter what your role is, you have to understand it deeply, you need to understand metrics. So especially product managers have kind of a wide breadth of things that they need to understand. So those are a given, you need to do that.

**Lenny Rachitsky** (3:40)
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