Scaling Uber with Thuan Pham (Uber’s first CTO)

Summary

Podcast Summary: Scaling Uber with Thuan Pham (Uber’s First CTO)

The Pragmatic Engineer
Host: Gergely Orosz
Guest: Thuan Pham (Uber’s first CTO)
Date: April 1, 2026

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Episode Overview

This deep-dive conversation charts the extraordinary journey of Thuan Pham, Uber’s first CTO, highlighting how Uber’s explosive scale was managed from a technical and organizational standpoint. Thuan shares lessons from his personal background as a Vietnamese refugee, reflections on early career choices, and the strategic decisions that shaped Uber’s now legendary engineering organization. The episode is packed with stories about rewriting the dispatch system to stave off collapse, launching Uber in China in record time, navigating organizational growth pains, transitioning to microservices, and building world-class engineering culture.

The episode is a must-listen for software engineers and tech leaders, offering candid, actionable insights on scaling teams, surviving hyper-growth, and remaining an effective technical leader in the age of AI.

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Thuan’s Origin Story: Refugee Roots and a Self-Taught Engineer

[01:10–06:01]

• Thuan recounts fleeing post-war Vietnam as a child, surviving hazardous journeys, and arriving in the US with no English or resources.

• His interest in computers developed by chance, thanks to a friend’s IBM PC. He taught himself BASIC programming:

  “I don’t like to do the same thing twice. So computer programming was perfect...” (Tuan, 06:03)

• Early jobs included automating accounting work with Lotus and Dbase 3, showcasing a problem-solving drive from the very beginning.

• His skills led him to MIT and then to Hewlett Packard Labs, where he quickly moved from research to a strong desire for work that users depended on.

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Learning from Early Tech Industry Waves

[07:05–14:21]

• Early projects at HP Labs & Silicon Graphics included pioneering interactive TV—years ahead of its time, offering practical lessons about “the world being ready” for innovation.
• With NetGravity (later DoubleClick), Thuan helped build the first dynamically targeted ads for web pages.
• Observed the impact of focusing on profitability vs. growth in startups:

  “Sometimes you’ve got to seize the market...there’s a company that formed much later than us, but did an ad service bureau and that took off.” (Tuan, 14:34)

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Lessons from the Dotcom Bust and Transferability of Skills

[15:29–19:38]

• Explains the exuberance and subsequent crash of the dot-com bubble, and how fundamentally strong businesses survive market cycles:

  “Talents are always talent...if people just be complacent, atrophy with time, when rough times hit, it’s very, very hard to recover.” (Tuan, 19:38)

• Joined VMware pre-hockey stick, building the first versions of their software management suite, learning the value of organizational structure, and scaling.

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Thuan’s Management Style: Getting Comfortable with Discomfort

[23:57–25:42]

• Tracks a pattern of joining organizations when small and leaving when things get “too comfortable.”
• Always looking for opportunities to do something new and learn, even if it means starting over from a VP to an IC at a new company.

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Joining Uber: From Curiosity to CTO

[25:53–32:37]

• Uber opportunity surfaced through reputation and past connections, not active search:

  “People always come and go throughout the industry, but if you’re good with them, they tend to remember that.” (Tuan, 27:53)

• Bill Gurley, recognizing Thuan’s work at NetGravity, reached out after seeing him leave VMware.

The Legendary Uber Interview

[28:30–30:57]

• Travis Kalanick, Uber’s then-CEO, conducted a rigorous 30-hour interview process across two weeks, “simulating” what it would be like working side-by-side.

  “After a while, I forgot I was being interviewed. It was like two people sharing ideas...” (Tuan, 28:40)

• Travis meticulously covered topics like hiring, firing, code quality, design, organizational culture, and more, demonstrating a deep interest in technology as a key business driver.

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Uber’s Early Engineering: Scrappy Startups, Existential Crises

[32:47–39:04]

• When Thuan joined, Uber was running 30,000 rides a day with 40 young engineers; the system crashed multiple times per week.

• Services were built for functionality, not scale—a feature-first approach.

• Thuan’s first major focus: rewrite the critical dispatch system before New York City hit the “brick wall” of unscalable architecture.

  “Without dispatch, there is nothing...We have to rewrite it in a really scalable way.” (Tuan, 35:33)

• He led the team to prioritize survivability and simplicity over perfection, with ruthless focus on scalability:

  “If my requirement for the engineer was build a system that will scale infinitely...we’ll die before then.” (Tuan, 39:53)

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Launching Uber in China: Scaling at Warp Speed

[40:17–46:33]

• Travis Kalanick issued a nearly impossible mandate: launch Uber’s entire stack in China in two months.

• Compliance with Chinese regulations required building data and compute isolation from scratch.

• Despite all expert estimates, the team delivered in five months, with the hardest city (“Chengdu”) first:

  “By doing the hardest thing first, once you launch that, everything else is downhill.” (Tuan, 44:12)

• This feat built enormous organizational confidence and resilience.

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Uber’s Organization and the Microservices Explosion

[46:50–52:35]

• The “program and platform” org structure was invented to untangle functional teams and move faster.

• Cross-functional teams—each “owning” a slice of the product—became the model.

• As Uber scaled, monolith APIs became a bottleneck. The now-famous microservices split was a necessity to unblock parallel team progress, not a planned architecture:

  “No one should be blocking anybody else. No one can block anybody else.” (Tuan, 51:04)

• The monolith ‘decomposition’ was continually outpaced by business growth, leading to thousands of microservices. This was later rationalized—but only became manageable after business growth stabilized.

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Internal Tools & Open Source: Building What Didn’t Exist

[52:57–56:24]

• Uber initially leaned on standard open source, but as demand and scale grew, they often hit breaking points (e.g., random Postgres failures).

• Solution: develop internal tools like Schemaless (trip data), Jaeger (tracing), M3 (metrics), and many more—often later open-sourced.

  “I remember the time where I had to go on LinkedIn begging...anybody...with Postgres knowledge...terrifying because open source, there’s no single person...willing to pay anything.” (Tuan, 54:13)

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Project Helix: The Uber App Rewrite

[56:24–59:11]

• “Helix” required rewriting Uber’s app from scratch for flexibility and scalability of user experiences.

• Involved 6–700 engineers over 7–8 months—one of the largest app rewrites at the time.

• Tight deadlines were a feature, not a bug, of Uber’s culture:

  “Everything we do had a tight deadline. That’s just how the culture roll.” (Tuan, 57:18)

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Naming, Promotions, and Culture: Growing Pains

[59:11–63:41]

• Internal communication: Named “not a Mickey Mouse shop” after frustration with playful/unhelpful service names when onboarding engineers.

• Re-defined senior engineering levels (introducing L5A/L5B grades), based on observed development plateaus and to break up the long journey from “senior” to “staff.”

• Pushed radical moves like enabling internal transfers and job boards—minimizing process friction and incentivizing managers to invest in their reports’ growth, not retention by force:

  “It’s not a jail. We can’t lock anybody down. Everybody have free will...” (Tuan, 65:51)

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Leadership, Legacy, and Perspective

[66:11–69:44]

• Thuan’s outlook centers on humility, purpose, and impact:

  “When I’m gone, the thing I’m most proud is how many people remember how I was good to them or helpful to them and for how many years.” (Tuan, 67:40)

• Networks, Thuan repeats, are built quietly by doing great work and being good to people:

  “They came because they still enjoy working with you...there are people who work with me for five different companies over 28 years.” (Tuan, 70:19)

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Building World-Class Teams: Talent is Global

[70:36–71:42]

• Uber’s approach to distributed offices was talent-driven—not efficiency or cost-driven.
• Offices in Denmark, Lithuania, India, and elsewhere evolved around high-caliber engineers, bringing opportunity to world-class talent everywhere.

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CTO as a Strategic Role: Looking Around Corners

[90:21–94:34]

• CTO’s essential jobs:
  • Build high-talent, high-trust teams and culture.
  • Predict and plan for future technical and organizational needs—see “around the corner.”
  • Align organization and processes to future business requirements.

  “When you’re in any level, your job is to see a little bit further out than your folks...if you don’t do that, then no one, it’s your job...” (Tuan, 92:43)

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AI’s Impact: Software Engineering in the New Age

[85:04–89:50]

• AI is dramatically boosting productivity and transforming the nature of engineering work at Fair and elsewhere (e.g., “swarm coding” with agent orchestrators).
• The traits distinguishing great engineers—curiosity, innovation, fearlessness—matter even more in AI-driven environments:

  “Complacency is death. The world will move faster and faster and the moment we stand still, we are falling behind.” (Tuan, 89:50)

• The business impact—not raw code output—is still the most meaningful measure.

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Advice for Engineers at Every Stage

[94:41–97:06]

• Early years: push for the hardest challenges and accelerated learning.

• Later: seek impact opportunities and stretch your skills at growing organizations.

• Senior phase: Give back, develop others, and focus on broader organizational contributions.

  “The earlier and harder you work early on, the better you have in the future. If you take it too easy right now, then the road in the future might be a little harder.” (Tuan, 95:14)

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Notable Quotes and Moments

• On leadership:
  “Your job is to see a little bit further out than your folks…if you don’t do that, then no one…” (Tuan, 92:43)

• On internal mobility:
  “It’s not a jail. We can’t lock anybody down…why make it so hard and end up leaving the company? That’s just a silly thing.” (Tuan, 65:51)

• On building a reputation:
  “Just do the work, right? Don’t do the work in service of that goal—just be genuine, just be yourself…” (Tuan, 68:10)

• On AI and engineering:
  “To me, it is an incredibly powerful tool… you can wield the tool properly, you can do extraordinary things…” (Tuan, 90:06)

• On managing scale:
  “Thousands of microservices happened because every time we tried to decompose the monolith, the business was growing so fast that other teams were adding to it faster than the decomposition team could pull things out.” (Tuan, paraphrased—see 52:35–53:21, 97:14 Host wrap)

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Timestamps for Key Segments

• 01:10 Origin story, Vietnam to US, discovery of tech
• 07:05 Early research/industry experiences, first lessons on innovation and timing
• 14:34 Lessons in startup growth/profitability vs. scaling
• 27:53 Getting recruited by Uber, the power of reputation
• 28:30 The 30-hour, two-week Uber CTO interview (Team & Culture Topics)
• 34:54 Uber’s existential scaling challenges, Dispatch rewrite
• 40:17 How Uber launched China in (almost) 2 months
• 46:50 Program & Platform, birth of Uber’s org model
• 51:03 Microservices: history, necessity, and scale consequences
• 54:13 Why Uber built and open-sourced infrastructure tools
• 56:24 Project Helix: Uber App rewrite, deadlines as culture
• 59:11 Naming culture, promotions restructuring (L5A/L5B)
• 63:41 Radical internal transfer policies, building a “non-jail” organization
• 66:11 Leadership, legacy, and humility
• 85:04 AI’s impact: swarm coding, AI-augmented engineering at Fair
• 90:21 What does a great CTO do?
• 94:41 Advice to new engineers entering the industry

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Final Thoughts

This episode is a behind-the-scenes case study in scaling complex tech organizations under intense pressure. It distills decades of lessons in growth, leadership, talent strategy, and managing technological paradigms shifts (from monoliths and microservices to AI). Thuan’s career illustrates that good technology follows good people; maintaining trust, humility, and resilience are as important as any particular technical skill—even, or especially, in the AI era.

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Links Mentioned:

• Pragmatic Engineer Newsletter

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Transcript

[Host]

When Tuan Pham joined Uber as the company's First CCO in 2013, the company had 40 engineers, did 30,000 rides per day, and the system crashed multiple times per week. He had five months before Uber's Dispatch system would hit a brick wall with no way out. Seven years later, he left the CTO of one of the most complex engineering organizations ever built. In today's conversation, we discuss Tuan's interview with Travis Kalnick for the CCO role, which lasted 30 hours, spread over two weeks, scaling through chaos, rewriting Dispatch before it collapsed, launching China in five months, and the full Apple ride known internally as Project Helix. Why Uber ended up with thousands of microservices and hundreds of internal tools because existing solutions could not handle Uber's scale at the time and many more. If you've ever wondered what it's like inside the room when a company is growing faster than its systems can handle, and what are ways to get things under control, this episode is for you. As a side note, I've been lucky enough to work at Uber while Tuan was the CTO and Tuan is the real deal. This episode is presented by Static, the unified platform for flags, analytics, experiments and more. Check out the show notes to learn more about them and our other season sponsors, Sonar and Workos.

[Travis Kalnick]

Tuan, it is so good to have you here in person.

[Tuan Pham]

It's my pleasure. It's so good to connect with you again after all these years.

[Travis Kalnick]

And it's so good to reconnect. We worked together for almost four years at Uber, probably my first month. I already met you in some really fun, stressful circumstances during Helix, the Uber app rewrite, which was a crazy project. But before we get into any of that, how did you get started, not just in tech but in life? You had a pretty rough start.

[Tuan Pham]

Yeah, I grew up in. I was born in Vietnam and I was a child, I would say, of the Vietnam war. So in 1975, when the south of Vietnam. I was from the south of Vietnam, my father was tied to the military of the south of the south. And when the country was unified, the south has lost and the north has won. And there were a fair amount of repercussions, right? People who associated with the southern regime would not have much of an opportunity growing up. Education, opportunity, all these other opportunities. That was again, the way it was at the time. That's not necessarily true right now, but that was. And my mother then made a very bold decision that she wouldn't want her two son growing up with no opportunity and so we had to flee the country. And at the time there was a massive wave of exodus called the Boat People, where people just get onto a rinkety boat, fishing boat or whatever thing they can get their place in and escape the country in the middle of the night. People did not know at the time and nobody thought about it, but the chance of survival was about less than 50%. About 2 million people left. About a million people survived the crossing because these boats are not seaworthy. And we crossed the ocean and. Yeah, but we were the lucky. We were lucky half really. But no one thought about. If people think too much about it, they probably wouldn't do it. But everyone just like, well, we need to escape. We need to, you know, give ourselves a shot of a better life. And so we did. So we, we left Vietnam. It took many try and took it depleted the entire, you know, saving of my parents because it was a scam. People would say pay up half now, half later. And then the book never shows up. And finally on the fourth try, we actually made it. And then we were lucky that we have a really good captain who actually navigate through storms and all that. And we survived even pirates from Thai. I was around, I think 11, 12 somewhere. And so we crossed that and we survived three days, four nights of the crossing of the South China Sea to Malaysia. Then we went into Malaysia. We thought we were done a week later we got tower back out and dump it in Indonesia a few days later. And that's where the government there accepted us in and put it on a deserted island at the time. And we formed a refugee camp there. So. And then we were waiting to be processed. We got interviewed by all the different countries and the US gave us a refugee settlement because we were tied to the old regime that were supported by the Americans. So we were very, very thankful to get here the land of opportunity. And we didn't know any English, we didn't have any penny to our name. We were sponsored by a church. The first set of clothing we got was from the donation closet at the church. But we have to build from the ground up. And so that was how I grew up and that's how I got here.

[Travis Kalnick]

And I'm from this like absolutely not just unconventional, but just extremely hard start. How did you eventually get your interest into computers, into tech?

[Tuan Pham]

Just like most things in life is by happens and or luck. I was pretty good in math and science. As most kids in Asia we were growing up, we learned that. And when we got here, I had a friend in high school who had Received a gift from his dad, an IBM PC. That was one of the very first one, the one with like two floppy disks.

[Travis Kalnick]

Was this in 80s or 70s?

[Tuan Pham]

This was in the 80s, this was in 1980. Yeah. So freshman year. So after school I would hang out at his place and he's got a new toy. And so we were you know, writing little BASIC program and playing game and all that stuff. And we learned how to use word processors and Lotus and Word Stars and all that. And I started coding in basics. And then I just realized that, oh, it comes very natural to me. I can think very algorithmically. And then there's another weird thing I sometimes tell people. I am generally a procrastinator. I don't like to do the same thing twice. So computer programming is perfect for me. You solve the problem one, that's the creative part. After that I get bored, I got to do the next problem. And so writing program was like the perfect fit for me.

[Travis Kalnick]

You do not duplicate your code.

[Tuan Pham]

Yeah, I don't like duplicate the code. I don't like to do the same thing twice. And so yeah, when you write it and then it executes way faster than you can do it by hand. So that was really wonderful. I just taught myself that. And then I volunteer at a government agency to write code for them after school. And so I did that and I went in there and I basically stitched together Lotus Dbase 3 with all the scripting languages and automate the entire financial accounting and reduce the workload. At the time, that too's accountant had to spend about three weeks or so every quarter reconciling everything. I did all that stuff with a purchase button and took about three hours for the whole batch to run. And so they were so happy. When I graduated high school, I think they wrote me a really good recommendation letter and with other things that were going on and the good grades and everything else, I got accepted MIT and then I got there and I really learned computer science. Like the fundamental of computer science. Back then I was just like a kid who just write programs.

[Travis Kalnick]

And then during or after mit what was your first professional job where you got paid and you worked full time on. On technology.

[Tuan Pham]

With technology, one thing lead to another. When I was at MIT there was a multi year co op program with some of the best company tech company in the world at the time at and T. Bell Labs, Xerox, parc, HP Labs and all these companies. Bellcore all over the country actually. And so we applied for it and then the kids with the best grade got prioritized Then the company had to go through a selection process. They ranked all the kids and then the kids all ranked the company that they got ranked. And then there was a matching process and I ended up coming to Hewlett Packard Laboratories. And HP was on an awesome company at the time.

[Travis Kalnick]

Back then there were massive and like

[Tuan Pham]

very, right, very innovative laser printers, you know, workstation computer systems, all of that stuff. I was in the HP lab, which is the research lab where a lot of the really innovative stuff happened. And so it was a dream job as a student I get to work on cutting edge research with all the other PhDs around. I get to write the joint thesis for my bachelor's and my master's with the work there. That was part of the arrangement. And when I graduated HP just hired me straight into that research lab. So I became one of the researcher, although I didn't have a PhD. And after that, that was a few years of that. Then I went into the industry and write code that people would actually use. I really enjoy my time at HP Lab because you get to do cutting edge stuff. We were working on medical informatics at the time where right now you go to every doctors, all your rectors are following you. Back then we actually have a network distributed system architecture where every physician workstation that you go to, right, had your X ray and everything followed. And then you have like knowledge base that actually look at for drug interaction. Oh we actually did that research back in the mid late 80s actually. And so these are cutting edge stuff. But then the thing that I find unsatisfied, unsatisfactory at the time for me was we published great paper and then didn't go anywhere. It was not productionized. And I'm just like, I want, this is so cool. Why can't we bring it to the user? But that wasn't the setup. The setup was research lab, worry about research. And then we have like a tech fair every year and and the general manager of every product division swing by and then decide what they want to pick up and productize. And so I didn't feel empowering beyond the research phase. So I just had to go find a place where I can write code and people actually use my code. So I went to Silicon Graphics. At the time we were also trying to invent the future and we actually did a prototype of that. That was interactive tv where back then now we could take for granted a streaming video, video on demand, online game, right, Cooperative game. Back then we didn't have cell phone Internet yet and we can cobble 4,000 homes together in an 18 trial that has cable. And then we invent like network protocols and all these things. And we actually found a set top which is like tube tv, not even a flat screen TV with a set top box on top, which is a Silicon Graphics box. And we can implement online shopping, movie on video on demand.

[Travis Kalnick]

You're building all of this stuff. We built all of that without having,

[Tuan Pham]

without having any of this stuff right here. Wow. And then celebrity like Michael Jackson came by, saw demos and we saw Spielberg. We saw everybody. We thought really believe that was the future. And it was the future. The problem was it's way, way ahead of the time, right? Then I learned a big hard lesson. It's not about just a technology, it's about whether the world is ready for it, whether it's economically feasible.

[Travis Kalnick]

And back then, what was the point where you realized like this is not going to work, even though we're doing

[Tuan Pham]

this awesome stuff after a year, right? Because it took like a hundred million dollars back in $1994 just to provision the head end. Silicon Graphics love it because they sell all these massive server to pump out video. And then the set top itself is a Silicon Graphics workstation that costs four or $5,000, right. People would not buy that, right?

[Travis Kalnick]

Especially like, like in today's money that will be like 10, 20,000, something like that.

[Tuan Pham]

The early adopter enthusiastic maybe, right. But it's not for the mass market. And so when we, and we did that trial incredibly successful, we definitely all saw the future. And then we did the same trial, a similar trial with a different set of software that we wrote for ndt, Nippon Telephone Telegraph in Japan. We went to Japan, deploy that, very cool, had a really great time. But then it fizzled out because it would not be commercially viable. And so that was a really first life lesson that I learned. It's not just the technology, right? You got to be at the right place at the right time and the right price point. And then after that I went to a startup founded by a former office mate at sgi. So we were doing Internet advertising. The Internet was about to take off. Then Mosaic browser search came out. Netscape was being formed. And yeah, in the early days of Netscape. And so we saw very clearly that the advertising model worked for tv. So it has to work for the Internet, right? Because all these content people would use it if it's free. But then who has to pay for it, the advertising? So we, we, I joined a company initially we call ourselves Netvertiser, which is like you know, payoff and then change it changes name quickly to net gravity and then it's so enterprise software to put ad banners, dynamic ad banners on cnn, on Netscape site and all that. I was one of the very early engineer there. I was the fourth engineer, I believe. Yeah. And so um, people don't know this but a buddy of mine, we were the first app engineer to put the first dynamically targeted ad on the. On the Yahoo page on the Internet

[Travis Kalnick]

and dynamically targeted meaning that it showed

[Tuan Pham]

different ads based on the different apps before.

[Travis Kalnick]

Like whatever.

[Tuan Pham]

Yeah. The version before I came in was a script that crawled through and just put a static banner ad and rotated through every hour. But then we, it's like we got to target it and then we start using cookie. We started at first it was a content of the page and the person and then we actually use that to actually target that different ads and then we have ad sequence and all that stuff. And that was the very first one. Of course we had some success there. That company went public. But another thing that I learned was sometimes you've got to seize the market. Right. There's a company that formed right. Much later than us, but did an ad service bureau and that took off because it take a lot less investment for people to. You just stick a banner, a tag on your HTML page and then revenues come your way. Right. Because the service bureau to kind of stick the app there dynamically, all that kind of stuff. We had wanted to do that in our company but then one of our board members said no, you should focus and get the profit first before you expand. And we went down to profitability path and we then become like, you know, a bigger robust enterprise solution. Whereas the other one is. And try to get profitable and the other one is just expand through the Internet like raging wifi. Then after that years later don't got bought by Google. So that was the journey there. There's a lot of lesson there about how to build things.

[Travis Kalnick]

Do I understand that you saw that what happens when there's a big market and you focus on profitability, which should make sense. But a player focuses on growth even at being non profitable, it might be able to swallow you in the end.

[Tuan Pham]

That's right. Look at what happened to at Uber. Right. We did the right move.

[Travis Kalnick]

I'm starting to see how these things are coming together. So now you're at the startup which almost took off, but not quite. And then what was your next step?

[Tuan Pham]

That company went public and then got absorbed. And after about seven years there, I had made it to the VP level. I joined as an IC along the way. I knew that from my inspiration at the silly Citron Graphics day that if you want to do something really big, you need to leverage other people. You can't do it with your bare two hands. So then I switch over to the management track and I honed the skill and I got up to directors and senior directors and then ultimately got the vp. And then after about eight years, seven years, you're there. The dot com bust happened right at that time. And then I said, well, maybe it's time to prove to myself whether or not I'm just a one hit wonder or I actually have skill that are transferable.

[Travis Kalnick]

Just, just one thing on the dot com bus because you kind of swept over it because you've now seen a lot of like ups and downs. But can you take us a little bit back what actually happened with.com bus? Because the people I talked to especially were new grads. It sounded very, very scary. What, what did you feel like and what did people, professionals, engineers around you feel like?

[Tuan Pham]

The.com bus was, was kind of scary when the correction happened. Right. But before that there was this exuberance that everything is.com, right, pets.com, fubar.com everything is a.com web fan. Yeah, all of that. I still have the wet fan bin in my, the brushes actually. And so yeah, but then there was a shakeout. Eventually there has to be sound business model that makes sustained profit, right. Growth and profit growth alone eventually burn, you know, money and that's not good. You can grow fast but eventually you have to turn that into profit to be a durable company. And so in that.com wave there were massive companies that emerged, right? There was Yahoo, that's Google, there's Amazon, all of those company. There's also a bunch of other company, Webvan and others, whatever that would go under because they didn't have like a strong value proposition that lasts the test of time. Right? So yeah, it's all about what value you deliver and whether or not it's beneficial and valuable to the customer that they're willing to pay. Right. And I think that's one thing that we learned which one is like a real fundamental strong business even though it might not be a profit initially but which one are just a Me too, right? Just put a.com on something and it's hot. There may be a lot of AI things that's going on right now. Right. Eventually some of these things will consolidate, some will go under Some will become really awesome solutions and all that stuff and so but the market will sort it out in the end. The customer will vote on what they want to spend their money on.

[Host]

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[Travis Kalnick]

and there was a lot of layoffs, companies going bankrupt. Did that worry people around you? Did that worry you that you know your your job could be in danger or you might have a harder time switching jobs or did you not? Was it a very short lived?

[Tuan Pham]

It lasted a couple years, I remember and during that time it was definitely hard to to get a job especially for new college grad. That's always the first layer that get hit, right? When everything retrenched. People want more experienced people, people want to stretch existing folks rather than keep on hiring entry level folks that you have to continue to invest in. Right. So it's just the economy of time, it comes and go in waves. Yeah, so that was certainly a very scary time. But of course, you know, in the longer range of history things generally tend to recover. But it caused a rearrangement and yeah, so during that time it was certainly tough. However, the way I look at this thing is like talents are always talent, right? So people are really strong talents and who's really hungry is always try to punch above their weight will always be marketable. Right.

[Travis Kalnick]

Even in a downturn.

[Tuan Pham]

Even in a downturn. So I think the Key thing is how people should, even in peacetime, invest in that skill. Never be complacent, constantly try to be better. And then in wartime or in rough time, those things will save you. Right. If people just be very complacent, atrophy with the time, and then when rough time hit, it's very, very hard to recover from that.

[Travis Kalnick]

And then you went to VMware this time.

[Tuan Pham]

Yeah. So let's see. After I went from double click to that, and then I jumped into a four person company again, leaky roof and everything, classic startup. That business did not succeed. It took about three years or so, got to about 40, 50 people in size and then kind of ran out of money and then got acquired by another entity that was built with a security appliance product, would try to solve the problem of, you know, intermediation of web services, traffic they're going through. And it was a very interesting security niche, but it's not a mass market thing. And so it's hard for a company to kind of break through like that. Right. But eventually it went away. But even then, you know, those three years taught me a lot. Okay. That you can survive even when you do it from the ground up, then you still have skill that you can pick up, despite the fact that that journey might not end in like a commercial success. But your skills still get better.

[Travis Kalnick]

So you are getting better as a professional, even though that's the thing, we have to trust.

[Tuan Pham]

We invest in ourselves, but of course we invest in the company or vehicle that we are part of. And ideal case, both sides succeed. But if the other succeed, at least if you work really hard, you will gain some skill. And then based on that, then you can then leverage all the things that you learned so far and all the mistakes that you've made. It got you smarter and better and wiser to look for the next opportunity. So right after that I look at a bunch of other things when that company was acquired. Then I went into VMware again when VMware was pretty small, not very well known yet. So it was a 40 person organization and sort of that built software to stitch together.

[Travis Kalnick]

So VMware was still early, VMware was still early.

[Tuan Pham]

Yeah, there was three division, one division that did the workstation desktop app, and then there was the division that does the hypervisor, which is the OS underneath the os. And then there was my division that was building enterprise software that stitched together all of the hypervisor into like a cloud platform management platform. Right. So I was the one for that. It was about 40 people. And we kind of built the very first product suite for VMware, we call Virtual center that tied to ESX. So that was a really, really fun. Right. Very smart people.

[Travis Kalnick]

And then VMware really took off. So virtualization as a whole took off in the early 2000s. VMware was core part of it. It was one of the. So it was just. Was it a kind of hockey stick ish experience?

[Tuan Pham]

It was not to the extreme of Uber, but it certainly was because it was a industry changing technology. It was a game changer. Right. Before that there was anything like that. At first people thought, oh, this is a kind of interesting tool on the desktop for you to run a couple of Mac and PC OS on top on a PC. But the true power was the esx, right? Yeah. And then that's what you power Data center. And then of course that's the hypervisor. But I think the key feature that made VMware so useful was the whole vmotion thing. When you take a virtual machine and you can migrate it from hardware to hardware without any perceivable downtime of the application run on top with that capability. Unlock the whole cloud thing. Right. Because you have 1000 machine, it can look like one, it can look like a C machine. And so application inside of a machine will just scale and it will just move itself and it can do whatever you need to do. Right. You can do. Dr. You can do, you know. Yeah. All kinds of things with it. Right. So that actually make it very much like a cloud operating system.

[Travis Kalnick]

And then at VMware we also grew with the company. Right. So. So again, it seems you have this history of you were a VP of engineering at the startup, you stepped down to a small startup, you then joined VMware and eventually you became VP of Engineering at VM where it was a lot, right?

[Tuan Pham]

Yeah. Yeah. I have this weird thing where when I get. When the thing gets large and I start to feel too comfortable, I get nervous.

[Travis Kalnick]

Really?

[Tuan Pham]

Yeah. And so that's where when at doubleclick when I got to VP and I managed hundreds of people, I was like, is this a fluke or is it real? So I had to go back to a four person company and try to see if it's real or not. That didn't succeed really well. But the engine was healthy, it was good. And then when a VMware again is a smaller company and it go big and when you get really big again, when you get to a point where you're just running things rather than breaking ground and doing this thing or hard learning, then you got to do something different. Right. So I keep on going back small, and when I get big, I might go back small again.

[Travis Kalnick]

And, yeah, so I'm seeing the pattern. So you got big at VMware, and VMware was doing amazing. What made you look around and how did you find this very small company at the time called Uber? Or it might have been Uber Cab. I'm not even sure how it was called.

[Tuan Pham]

It was Uber at the time.

[Travis Kalnick]

It was Uber already.

[Tuan Pham]

Uber Cab was way before that.

[Travis Kalnick]

That.

[Tuan Pham]

Yeah, yeah, it was. When after eight years of VMware. And sometimes people change, sometimes company change, sometimes both sides change. And so, yeah, for me, what changed personally for me was I have reached to the point where I didn't feel I could do much more there. Right. I'm running 800% engineering team. We're building this software, and it's been like the third generation of that software already. We're tweaking, we're adding more feature to it. I love my team and all that, but, you know, it's just more of like, keep it steady, keep it growing, and add more feature. And then the company has also changed along the way. You know, the original founder left, new crew came in, and there's a fair amount of changes in personalities and all that. And after a while, it just felt like it's time.

[Travis Kalnick]

So now with your background, like, you now have a super impressive background, you probably could have gone anywhere, large or small. What was your search process look like? And then how did you come across it again? Because Uber was still pretty obscure.

[Tuan Pham]

Yeah. Here's a really interesting thing. People do ask me about what the search process looked like. How did you stitch together a career like that? My honest answer is I didn't do any of that. And it wasn't luck that you bumble around and you find one thing after another. It's actually something different. If you try to do a really good job at every company, you've been working well with all the people that you work with, including your own team, your peer, whatever it is, over time, very slowly, you accumulate a decent reputation in people's mind. And people always come and go throughout the industry, but if you're good with them, to them, whatever, they tend to remember that. And then when you become available, then people come to you. How about this? How about this? How about this? And then you actually look at all those things, and then you can dig in and you can decide. And so that played out multiple times for Me in the Valley. And especially I think the biggest breakthrough was Uber. Again, when I left VMware, I didn't plan to do anything. Right. I was like, well, let's sit back and take a look, see what's going on. And then Bill Gurley from Benchmark Capital, who invest an early investor in Uber, and guess what his tie was. He knew me from that Net Gravity startup a decade before. And so we kind of knew each other and then. But of course, when we know someone, you follow their reputation. And it was Bill who come to me after he knew that I'm living VMware. Hey, can you take a look at this one? I'm investing. It could be really interesting. So I went up to his. His office in Sandhill, and he shared with me the board deck and how the company is growing. And then I understood the. The business model. Right. To all of you. Back then when I tried to recruit some people, it was like, why Don? Why are you joining a taxi company? Right.

[Travis Kalnick]

Yep. I. Everyone's asking me.

[Tuan Pham]

Exactly. And so. But I knew that. And of course that we have to go to like a pretty rigorous interview process with Travis. And. Yeah, but ultimately it's about the connection that lead to the right thing. But that connection and the opportunity basically tied to your reputation.

[Travis Kalnick]

And then back then, as I looked it up and you also helped me with this, Uber just raised a series B, which was $30 million is valued at $300 million, which was sizable, but still not nearly the. The gigantic company that later became. And one fun fact that I read about is you had this very rigorous interview travelers with process, which was tens of hours or something like that.

[Tuan Pham]

Can you.

[Travis Kalnick]

Can you talk about how that went?

[Tuan Pham]

It was impressive on that he did that. It was. He committed over 30 hours interviewing me one on one.

[Travis Kalnick]

Wow. Yeah, that's like several days of like,

[Tuan Pham]

long two weeks worth of interviewing every single day, a couple hours each day, minimum. Yeah. With passion, with intrigue. And we end up, after a while, I kind of forgot that I was being interviewed. It was like two people kind of sharing ideas, exchanging idea, and sometimes disagree something and then kind of work it out.

[Travis Kalnick]

And then you showed me, you took a photo of like, some topics that you talked about. Like, can you like, summarize what those were?

[Tuan Pham]

Yeah. My very first meeting, I drove up to San Francisco and saw Travis in the office, and we immediately went to the whiteboard and he wrote down all the topic on his head that, you know, he want to talk about with me. That was a really long list. There's a big long list of general topics about, you know, hiring and firing and communications and all of that stuff. Org design, everything else. And then there's a shorter list of very engineering specific stuff. What about code quality? What about qa? What about design? All that. And then there is also a list of shorter list of the five things that he want to see in an engineering team and the culture of an engineering team. And yeah, and so that was the list. And so after we wrote the list, we start talking, picking up some item off the list and talk. Of course, you know, in two hours I was supposed to meet him for an hour. It lasts two, which is actually good because we got totally into it. Time ran out. And then as soon as I drove out of the office, I barely get to the exit. I got a call from the exit recruiter saying Travis, want to see you again and talk some more. And so we did that. And of course he's very busy. He's traveling around all the regional offices to run the business. And so we set up a Skype session every single day for two hours each day. And we will pick one of the topic. That's why I took a picture, a photo of that whiteboard. And he did the same thing as a list of topics to talk about. And I still have it on my phone today.

[Travis Kalnick]

It's so important to be that. Because we'll share that list in this episode as well, that screenshot. But that the fact that the CEO would go into things like code review the hiring topics. I understand. But that he was so engineering minded. Or did you get a sense that he had the vision that technology and engineering would be just key to Uber?

[Tuan Pham]

Oh, absolutely. I mean, he knew that and it was very clear from the very beginning that he viewed the business has two major engine that powers it. One is the operation, you know, bits and atom. Right. You gotta have wheels physical thing moving around the world. And then there's technology. And technology is a key part of that. Right. No one side is appeal to the other, but it requires both of those. Yeah. And so that was very key. And I think he also knew what he wants also and what he want in whoever it is. And so I think this list and this serious conversation was for him to vet that. Yeah. Later on, I think either he said something or I figured out that it was actually a simulation of what it's like to work with another person in that capacity. In the end, when we're inside, we all working with each other all the time. And can we disagree on something? Can we work things out. Do we have generally similar philosophy and principle? And he did it himself. Yeah. And so. Yeah. And the level of passion and commitment he showed was just really impressive from this side, I can tell you. For example, there's some session when we totally, you know, in the middle of that and two hours gone by and he had to, like, stop and catch a flight to go somewhere else. He literally stopped and told me, just wait. And he pick up his phone, call his EA and say, can you move my flight and continue the conversation? Who has that level of commitment? Right. And passion and stuff like that. And when you see that, it actually draws you in.

[Travis Kalnick]

Yeah. So I guess it was another question that you joined, but can you recall what was it like from the inside, especially from an engineering point of view, from a system's point of view, from, like, what was going on?

[Tuan Pham]

So it was still pretty small. It was about 30,000 rides a day when I pulled the data. The weekend, which is always the busiest time when people move around. Yeah, that weekend, the day, the Saturday or Sunday before I joined, I joined on Monday, was about 30,000 rides a day. And Uber was, I don't know, 20 something cities around the world at that point, 20, 30. And so it was very modest. There are certain things that were going for it already. The engineering team was very young, but pretty scrappy and pretty committed and talented where whatever we need to get done by hook and by crooked, cobbled together. Right. And so. And as a result, though, the service was beautiful. Anybody who rides, we only had black car service at the time, but the experience was beautiful when for all the people who ride it, that's why word of mouth is, you know, raging around and. Yeah, and so that was the really good part. Now, the thing that maybe Travis had foreseen, or whatever it is, was the next phase, which, as the company grow faster and faster, what happened? Right. And by the way, the 40 engineer were very, very young, I think in the 20s, all of it. And the system was built not to scale. Right. It was built for functionality. Exactly.

[Travis Kalnick]

And it worked.

[Tuan Pham]

Yeah, and it worked. And it worked beautifully. Right. But it wouldn't scale and it would crash and burn all the time, multiple times a week. And that was our lives in the franchise as the hockey stick actually happened. Yeah. Everything breaks and we have to basically race against time to actually figure out what was the next most critical thing that would break and how to get ahead of it. And one of the things that Travis always tell me, even from the interview days, is you got to see around Corner So I try my very best to see around corner. And one of the first thing I did in the first couple weeks were beyond getting the getting to know the engineer and build relationship and build trust was to start examine what we currently have and what we need. And dispatch was the first thing. Without dispatch there is nothing. Right, so that's where you match the riders and drivers.

[Travis Kalnick]

Yeah, it's our matching service. Right. When it has the drivers, the riders and doesn't match.

[Tuan Pham]

Yep, that's right. And without that there's no business. Right. There's already, there's nothing. And so yeah, and I start. That was the first system I looked at and I asked some, I reviewed the architectures, I reviewed the implementation plan and it was very obvious that it wasn't going to scale. It was a JavaScript, it's Node JS and it was a single threaded thing. And the engineer at the time where when the city get larger and larger, they need more out of that piece of code to power that city. They would move that piece of code into a larger machine with a faster processor.

[Travis Kalnick]

Vertical scaling only gets you exactly so far.

[Tuan Pham]

So my role also to do things, but also to teach people along the way. And so I was just asking leading question to the team and the team only had three people, three or four people at a time. And so I asked the engineer, okay, what would happen if the city gets larger? And you have to support that because every city is getting larger, the ride volume is getting larger and larger. Then entry base said, oh yeah, we just move it to a more powerful processor and say what happened if you get to the fastest processor you can, oh, there are multiprocessors and then you can get a four way box and then you can put multiple of these processes on them. And then you say, well you got three or four of these things servicing the same state. Do they talk to each other? Do they share the same state? Not really. Right. So it becomes very partition. So pretty soon by asking those leading questions, the engineer now discovered a flaw that this thing would not scale. Right. And then, and then I have to establish the limit of where is the brick wall. And I basically sort of what's the biggest city do we currently have in terms of ride volume? And they say New York City. And I said okay, when is New York City is going to. We can run out capacity even here in New York City, even on the biggest box that we can get our hands on. It's about October and this is around May. Okay. And so it's like what we have to rewrite it, don't we? And we have to write it in a really scalable way. And I only have two requirements that all I need. One is a city has to be powered by multiple boxes.

[Travis Kalnick]

Yes.

[Tuan Pham]

And a box has to power multiple cities. That's it. So you can have N by M.

[Travis Kalnick]

You gave them these two constraints.

[Tuan Pham]

No new feature necessary. Just make sure that we can do that and then that allow the business, the company, to just pour a whole bunch of hardware behind that and it will scale. Technically, it will scale infinitely. Right. And so the engineer did that. And because the requirement is very simple, we have to do it really, really quickly before we run out of time, run out of Runway to survive. And so they did that and we actually deployed that right around August, September, right before it actually hit. And then onto the next problem database, it's going to be the next choke point. Right. And then the API monolith is going to be the next choke point. And we keep on identifying all these things. So there's all these threats coming at us and we have to establish, like, how much Runway we have until we, like, really get in serious trouble. There's no way out, and then get ahead of it.

[Travis Kalnick]

And so this was then the reason that we had so many rewrites. I joined later, but rewrites were still continuously happening. And I think when you come in, you ask, like, why could have they not written it properly the first time? Or like. But. But I guess, do I understand correctly that it was because A, sometimes you just build a system to solve your problem and. And B, you don't always know how big this will sell. A good example is the New York problem. And then you take those constraints and then you build a system. And then if those things change later, you might need to build a different system.

[Tuan Pham]

Yeah. It also depends on how fast you're growing. That dictates how you make. And because the faster you grow, the shorter Runway you have to survive. Right. Given whatever architecture and system that you currently have. And yeah, the question about how big it can possibly grow, nobody knows really, but it's actually not fruitful to pontificate on that. It was all about how much time we have to live. Right. We hit the brick wall and it's no way out. Right. So, yeah. And if that time is really short, then don't overthink it. Just survive that and give yourself enough Runway to then live to fight another day, is what I like to say.

[Host]

Growing fast like Uber did is a good problem to have for startups until it's not. And the pain points that come with fast growth is a good time to mention our season sponsor, WorkOS. If you're building any SaaS, especially an AI product, surprisingly you reach the need to build enterprise features like saml, Edge cases, directory sync, audit logs, and all the things enterprise customers expect quickly. Building that infrastructure yourself takes months. WorkOS gives you APIs to ship it in days, authentication, SSO, SCIM, RBAC, audit logs, and more, all designed to integrate directly into your product. That's why companies like like entrophic, OpenAI and cursor already run on workos. Skip the rebuild, keep shipping. Visit workos.com with this let's get back to Tuan's team rewriting the dispatch system and the short breeding space that this first rewrite gave them.

[Tuan Pham]

So that's what with dispatch we knew we had to do it very quickly, maybe by ourselves another 12 months. And after we get through that point, then we have another 12 months to think about the next phase of survival for that team. That's why the system needs to be rewritten several times. Let's say if my requirement for the engineer was build a system that will scale infinitely to the test of time, it might take a year. We never get there. We'll die before then. Yeah.

[Travis Kalnick]

Speaking of dying before, you were given in 2014 a seemingly impossible task. Travis told you you have two months to launch in China. And apparently launching in China was not as simple as just like opening your API and allowing the firewall. What was that project like? I heard it was an absolutely manic and crazy project. Can you take us back what it was like?

[Tuan Pham]

Yeah, that was one of those craziest thing we've ever done, but it's also one of the most amazing things we've ever done. And now explain why that is so so I remember very, very clearly right around Christmas time, 20 2014, we were all hanging out indoor the the big room in 1455 and Travis made a declaration that okay, come the new year I'm going to light it up and we're going to go into China. Okay. And then he turned over to me. It's like I want the and one of the requirement at the time was that we have to run our services on China soil. Right. And data center physically there physical data

[Travis Kalnick]

center needs to be there.

[Tuan Pham]

Until then we kind of dabble into the water by powering it from the U.S. okay and we have a limited time to do that, but he's going to light it up. I'm going to do that. And he's like two months. And I said well that's really tough. And he's like, why is that? Because I can go rack all the machine and copy the software over. Shouldn't take more than two months. And then I have to like explain that it's not that easy because when you do that then it work on day one and then the two drift and how you're going to maintain that. Right. We don't have twice the engineering team to actually manage two different systems that deviate. So the right way to do that is you build re architect whatever you need to do to kind of build one system that can be partitioned, right. So I think there's a huge security concern, right. Because anything that runs over there cannot presume to have any level of privacy or anything like that. But over here we have to protect everything, right? So we have to build that same system that has completed partition of data and controls and everything else so that, yeah, nothing bleed across. But it has to be every time you deploy code, you have to code everywhere, right? So you have to react, rebuild a lot of things. And so I went to the TPM team and asked the team to actually scope it out.

[Travis Kalnick]

And I think that TPM technical program

[Tuan Pham]

manager, Program manager and I think the best path for us was about six months and that was the fastest we can even imagine, right. I benchmark with a few of my friends in the industry and they kind of laugh at me and it's like 18 months minimum. But you know, that was uber. So we just like we didn't think too much about it. We say what let's do that. And then Dravidin like the six months. So we are kind of sat around four months, right? So and so because he didn't like we just split the difference, we didn't know anything but we just want to heads down and start getting to it. And so we look at oh what need to change given like this is the end goal and the requirement and then with everybody start getting really busy, working a lot of hours to start making these changes and four months come and we are still a month or so short. So we slept, we went to Travis and he's not too happy about that, but it's fine. And then five months comes around and we are very close but we are not there. We are about to slip again. And so it was not definitely not happy then, but we actually talk it out and I said the team feel very confident that within a month we can launch. But he had to give us something that mean, give us a ability to incrementally launch. Instead of lighting all the city in China all level once, let. Let us do it in phase, right. Every single week we'll launch a number of cities and then we're going to do it in the process of like a few weeks and then we're done with that. And he said, okay, that's reasonable. But he won the. The biggest city first and that's Chengdu.

[Travis Kalnick]

So he agrees to the incremental launch. But you need to start with the biggest part.

[Tuan Pham]

Start with the biggest part.

[Travis Kalnick]

That's so. Travis, no.

[Tuan Pham]

Yeah, exactly. But it is brilliant though, now that you think about it. I thought a lot about that over time and that was the most brilliant thing because by doing the hardest thing first once you launch that everything else is downhill from there. The team had this swag. The team know would go into the next set of cities with confidence. Had we done the traditional way. Let's start with the safest one, the smallest one for us, the next one, we step it up. On the surface, it seemed like, oh, it's a very good risk control measure. But every single week we'll be holding our breath until it's done. It's not done right. But this time we did everything we can to do the hardest thing first. And after that it's just the routine process throughout the rest and that it worked out exactly like that. And so, yeah, we got it done and a bunch of people were really burnt. And then they take like a month off, go to the beach and did nothing except stare at the water. I know some other entity did that. But after that, though, we're not fearful of anything. We did kind of the impossible.

[Travis Kalnick]

And I talked with a friend at Uber who worked at the IT team at the time, and his job was just to get the servers physically set up. And he said that the timeline was so impossible. I think they had two weeks from start to finish. They had a little bit of time to plan, but they were on the site, they were just. And when I gathered stories from the software engineers who worked on it, everyone had their own impossible task and project and they all thought it could not be done. And then somehow it all came together.

[Tuan Pham]

That's right. None of us thought the whole thing that could be done, but we just got our heads down and we just break it apart and just do it one step at a time.

[Travis Kalnick]

And then I think. Needless to say, but the China launch was a massive success. Uber started to compete head on head with the leading Chinese provider, Didi and there were is pretty much head on head, very intense competition, all the while competing with the rest of the world as well.

[Tuan Pham]

That's right, yeah.

[Travis Kalnick]

So that was something incredible.

[Tuan Pham]

That was something incredible. And I think just the experience having gone through that and doing things that initially you didn't think was possible just increases everyone's confidence and range and that's what stretching all about. And I think there's a saying that Travis like to say that sometimes you have to be willing to redline yourself a little bit. Right. And that's how you prove that you can actually do a lot more than you can. That was the fearlessness of the and the risk taking culture that he won in the company in the first place.

[Travis Kalnick]

One thing that Uber has been very, very well known about from the outside is microservices. And from the inside one thing that has been very talked about is a program and platform split. Can you tell us which one came first and how did we get to as many microservices as we did?

[Tuan Pham]

The program and platform came first. Yeah. And the microservices came later. And the platform and programming platform as an organization structure came first out of necessity. When I came In April of 2013 we had 40 engineer and three product managers. By the end of that year we had about 100 engineer and a dozen or so product manager. Even at that really small size, we ground ourselves to a halt with a functional org structure. Imagine those who are engineer, there are about up to eight or 10 mobile developers, a number of infrastructure engineers and a bunch of backend engineers, et cetera, et cetera and five, eight people or so at dispatch now but every feature that we want to put out has to be queued up on mobile development bandwidth, dispatch bandwidth and it become impossible to navigate trade off because every feature you want to do you have to go negotiate with so many teams, right? And so then the team wanted to move fast and start to feel that friction and complain right away. And that's a good thing, right? You know, we raised the concern and so I remember Travis and Jeff Holder and I saw that and we got together for a couple days actually. And I remember we had sticky note all the different colors, each color represent a different function engineering product designer. And we put one person name to each of the sticky note and then Travis gave a talk about what are the most important area of the business that he thinks, right? And at a time there were like 17 area that he can think of the world of Uber can carbon 17 area turned out to be a lot more than that, but at the time it was 17, we didn't have enough to fund 17, we had enough to fund seven, plus a few more. Right. So we fund seven with partially the next four and that's it. And the rest can remain empty until we hire more people and we fund it. And so that was the thing. But then as part of that process, we then put sticky note onto each of these area has to be a cross functional team because we can no longer afford to run. No, yeah, cross functional team rather than

[Travis Kalnick]

a functional team, which means that there's like a back end, a mobile and whatever else they need, like a design, if they need, etc.

[Tuan Pham]

That the concept is that team has to have all the skill set necessary

[Travis Kalnick]

to just get it done.

[Tuan Pham]

Whatever they need to do, they just go off and they do that. Right. So that was the principle behind that decision. And then we call some of those program and some of them platform. So programs are the team that build things that end user actually use and the platform are the thing that build tools and layer that other program team use. And that was it sort of horizontal versus vertical kind of thing. So. And that's that. And then after we define that, then we start putting the right sticky note onto that box. And then that's how the first version of programming platform came about.

[Travis Kalnick]

And then how did microservices start and how did they blossom as much as they did?

[Tuan Pham]

Yeah, again, you know, none of us wanted to go through that extreme. But lots of time when you are under a lot of pressure and no time to react other than just to survive that scale that keep on coming at you, you have to make decision that increase speed and velocity, because speed and velocity allow us to build things quick enough to survive. And so we knew right away that the backend API, which is a monolith, is the thing that will prevent speed from happening. So we made a declaration. Anything that is new need to be built outside of that as a microservice. And then there's a team that's dedicated to decompose that monolith, that API monolith into a bunch of services.

[Travis Kalnick]

Yeah, we used to call it API. Right, exactly.

[Tuan Pham]

We call it API. Right. And I think that project name is called Darwin.

[Travis Kalnick]

Yes, Darwin. Oh, I remember.

[Tuan Pham]

Yeah. And interestingly, had we freeze time, that piece of code could be decomposed in a matter of three to six months. But it took us two years to do that because as we peel out a piece of code, the business keep on going forward. Right. These hockey sticks are laying on top of each other as we launch New city and happening fast.

[Travis Kalnick]

New city and new product. Uber.

[Tuan Pham]

That's right. Feature has to be added on. Right. And so the philosophy we all operate at the time was no one should be blocking anybody else. No one can block anybody else. And so when a team that needs to build feature and that thing hasn't been pulled out of the monolith, they ask to the monolith, right. And then the team that pulls it out do the best that it can. And then we kind of keep chasing our own tail until eventually, you know, something get completely pulled out. And as it happened, it bulges up like this. The monolith, right. If you pull out one thing, the remaining stuff grew even faster than the stuff that you put out. So the code base get larger and larger, eventually reach to a certain point where they start to come down. And that's why it took two years. And meanwhile, everything that is new must be on because we don't keep on adding stuff right to the monolith. And so that's how it came up to like, you know, thousands of microservices. But that was utter necessity so that we can just fan out and solve every problem all at once. And then over time, after things stabilize and so the business more mature and growth is not as violent like that anymore, then the team, we actually have a project called arc. We're going to look at this stuff and how do we clean it all up? So we put like domain interfaces on top of a whole bunch of microservices that are within the same domain.

[Travis Kalnick]

It's funny because I remember that around like 2016 or so, there was a published Uber blog post that Uber about 5,000 microservices. And I just saw about a few months ago, Uber published another one and they have about 4,500. So in that 10 years, the number has gone slow down, right?

[Tuan Pham]

To go down. But even then, even though right now

[Travis Kalnick]

Uber has so much more complexity, right?

[Tuan Pham]

That's right. Yeah, there are process took a little while, but when, yeah, the team had to look at everything. And how do we simplify that? Right. And then to make sense out of that, new tool has to be invented by us, Jaeger, the tracing tool, all of that stuff. And so that'd be really great tool that we open source.

[Travis Kalnick]

Let's talk about how and why Uber built so much internal tools and also open source a bunch of them. Jaeger was one of them. But internally we had Schemaless, a trip data store, T channel and RPC protocol ring pop, Guelp spatial placing clay service framework. You monitor observability. And there's like hundreds of others, some of them open, some of them not. How were you thinking about that? Like, did it not seem like a lot of waste for us to build this or was it again, necessity?

[Tuan Pham]

It was mostly necessity. I can't claim that every single one of those things were absolutely necessary, but all the important one were absolutely necessary. The thing is, when I started Uber used pretty much all the open source stuff. We use redis, we use everything, right? Because the engineer there just focused on putting together a service that actually moved cars. But then as we scale, we keep on using, pushing the boundaries of the capability of those open source stuff and to the breaking point. And at certain point, if we don't invent something to power our own need, by the way, this is 2013, 14, 15, 16. It's not as mature as we did

[Travis Kalnick]

not have the kind of the big tech investment in open source back then, there was very little. And most of the big teams like Google and Facebook, they were keeping their inside.

[Tuan Pham]

Yeah, I remember like for example, a very painful example of that we had to face early on was we use postgres, all right? And we got to a certain scale that postgres would randomly fail and that take our services down randomly. We don't understand it's inside the kernel. I remember the time where I had to go on LinkedIn begging people who, anybody on LinkedIn that has any knowledge of Postgres to be our consultant to help us diagnose this problem. And we spent several weeks and during that it was terrifying because I don't mind if we think we can do something of our own problem. It's terrifying when we have a major problem and we depend on somebody else and we don't know because open source, there's no single person, no single company. I'd be willing to pay anything if someone can give me an answer. But there was no one. Right? And so that was one of the motivator to kind of build our own data layers and all of that stuff as well, so that we would use this generic database and we end up using MySQL just as table Data store, all the logic on top, we have to build for our own use, right? Because then we control our own desktop and we only build the feature that we really need. Right. And so that was one of many example. And eventually we run into other brick wall of scaling. I remember in 2015, right around the holiday, I was taking a holiday trip. I go to the Airport and I, I took an Uber ride as usual. The receipt didn't come for two days after that. Right. Why is that? Things were queuing up. We weren't processing things enough. Right. And so. Yeah, but that's not a deal breaker for many people because they just ride and then receipt come later. That's fine as long as the billing and all the stuff. Even when you bill people late, they don't really mind that either. Right. But as long as the ride happened, the rest of the stuff can be processed later, but it's still not great. Okay. When I dug into it, like, our data processing capability is at capacity, right? So we have to rewrite a bunch of stuff and then our capability to monitor things is reaching a breaking point with the open source tool that we use. So the M3 has to be invented. Right. And all of that stuff. So we have to do things because we, at the scale where we broke all the open source stuff that we

[Travis Kalnick]

use at Uber, we did unusual things. One of the most unusual projects, which is where you and I met when I joined Uber, was called internally called Helix. It was completely writing Uber's app. And as I understand what happened is Uber's user experience was starting to degrade because it was really cluttered. Travis got a bit fed up with it. The designer team came up with a solution which was a very nice and clean ui, which kind of. The engineering team looked at it and it would have been a full rewrite. And then we just did a full rewrite. Back then, I remember we had a million or 2 million lines of code. We had 2 or 300 mobile engineers working on this. This was a massive business and there was an extremely tight deadline set. Can you take us back on why

[Tuan Pham]

did we even do this?

[Travis Kalnick]

Because from. It didn't feel. It felt existential threat from the inside, but it was not like a Google vs Facebook existential thing. And how did we decide on that short deadline?

[Tuan Pham]

Yeah, it seemed like a recurrent theme that keep on coming up was a tight deadline, right? Everything we do had a tight deadline. That's just how the culture roll. Anything we want to do, we want to do as fast as we can. But going back to why Helix, actually, Travis has a vision, right. And it's actually not just the designer. Travis and Yuki, the lead designer at the time, they pair up and then all these storyboards and everything else. And he has a vision where the current app back then was too limiting. Yeah, it's really good. Push a button, get a ride, all that stuff. But if you Want more services to hook in other things. Right. Messaging and all these other things. As people were writing, the new architecture was much more open. Right. To all those things. And so that was the division behind that. And then when we're doing that, the aesthetic is really important, the icon change and all of these things change.

[Travis Kalnick]

Oh, yeah.

[Tuan Pham]

And so. But that is. Yeah, it's beautiful. Right. That's actually Travis and Yuki. Right? They were. And then of course, when that fleshed out to a certain amount, then the engineering team, the mobile team get involved. And it's not just the mobile engineer. The backend has to be written to

[Travis Kalnick]

everything we changed from the heartbeat where every five seconds we would pull and it was pretty painful to an actual push, push channel.

[Tuan Pham]

This path by that time. It's called real time system now, right? Yes. Yeah. It has to change, Backend has to change, everything has to change to support the new flows and all that stuff. And so, yeah, it took, I don't know, 6, 700 engineer all told, 7, 8 months to actually do it. Then we put it off and it still lived. Today it's still on that same architecture. It was so far well thought out. It's almost like future proof in that design that I still use today. It's still beautiful today. And if you compare that with the previous version, it actually was definitely the right.

[Travis Kalnick]

Yeah. And it was scalable user experience.

[Tuan Pham]

I take no credit in that. It's like the genius of Travis and Yuki.

[Travis Kalnick]

You every now and then send emails to all of engineering on different things. And I remember this really, really emotional email coming from you about naming.

[Tuan Pham]

I see all this and I understand young engineer want to have fun.

[Travis Kalnick]

We were having fun.

[Tuan Pham]

Yeah. And naming things in a goofy way. I think the trigger for that was a service named Mustafa. I have no idea what it is. Right. I look at that stuff and by that time we were already very complicated. Right. And we had to onboard new engine all the time. We want builders to ramp up quickly, et cetera, et cetera. And I can imagine an engineer coming here and have all these weird name, have no contact to it at the time. Our tooling wasn't that great either. Right. You blame didn't come into existence yet. Right. And so there's no mapping, so people discover what this really means and then those renaming schemes. So I got to the point where I'm kind of fed up, so I send that email out. Of course, you know those mass emails sometimes you regret after you send it out because it has some effect, but it didn't really solve it and I

[Travis Kalnick]

think it was very quoted because you specifically wrote this is not a Mickey Mouse shop.

[Tuan Pham]

Exactly. We're not a Mickey Mouse. And yeah, again, it was a growing up phase for everyone in the company. But it was my frustration at the time was look at this scale inside. We got to take ourselves seriously. We got to do things better, faster and this is not helping.

[Host]

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[Travis Kalnick]

We started to do better names. One other thing that was very, very unique to Uber across the industry and it caused a lot of confusion from the outside is Uber senior level. For a while Uber had a senior engineering level called L5 which is common. And then at some point you or the leadership team cut it into two. There was L5A and L5B. Senior one, senior two. Can you tell us about why you did that and where did you get the idea from?

[Tuan Pham]

I did that. I'm not apologizing for it. I think it was a good move at the time. And the principle was we want people to grow. Right. But we have a very clear definition and expectation of what it is at the staff engineer level because we benchmark ourselves to all the groups. Great company out there, Google, Facebook and all that. And then I realized that for many engineer crossing from senior engineer, I mean engineering two pass through the senior engineer to get staff. It could be a five year journey. Okay. It's a long time. And so I just want to break it in two so that people get a sense of progress. And then also not everybody can make it to staff. Right. But some people is good enough to make it to senior two seniors too.

[Host]

Yeah.

[Tuan Pham]

And I think that's a benefit. It's not right. But versus like not Doing it and everybody kind of just get lost in that five year, you know, journey. Yeah. And so that was the motivation behind that.

[Travis Kalnick]

So you saw a problem and then this was a solution. And it worked. We can say, right, it worked for a while.

[Tuan Pham]

Right. And then people were acclimatized to that and then they start complaining. It's like, oh, why? There's two level. We need to get to staff faster. And then while I was there, I held on to that because I was a principal and staff is staff compared to the best of the industry. And later on after I left, I think it got really.

[Travis Kalnick]

They got pushed down. L5B is now staffed.

[Tuan Pham]

Inflation. I didn't want to do the title inflation thing.

[Travis Kalnick]

I appreciate that. Another email that I remember from you is in 2016, you sent an email saying you've heard the feedback that NGOs are unhappy because their managers did not support them. And then what you wrote is like, we are creating a very easy internal transfer process. You can move teams. How was that received? And again, how did you decide that we need to do this?

[Tuan Pham]

I look at the talent base and I think it is best for us to create opportunity for people to keep on growing with fresh new challenges within the company. Because if we don't do that, they would leave the company and seek as well. And then I thought about the next logical step, which is, hey, if people come to us and just resign, they didn't tell us when they interview. Yeah. And so why the heck do we have like these rigorous process when you have to ask your manager for permission to go to another team, why do we make it harder for ourselves? Right. When our own engineer go from team A to team B have to ask for all these our, you know, permission where they don't have to ask if they interview outside.

[Travis Kalnick]

Yeah.

[Tuan Pham]

That just doesn't make any sense.

[Travis Kalnick]

Basically, it's easier to interview outside or it was easier to interview outside.

[Tuan Pham]

So that didn't make any sense to me. And so I said, well, let's not have that. Right. And that also has maybe a good side effect where manager now need to be incentivized to take care of people. Great. Develop them, grow them, you know, put position the best people into the best assignment for them to grow and then they not like to leave their own team. Right. If they continue to grow. So there's all of that, you know, that back pressure might cause engineer manager to be a little bit more responsible too. So that was that. And I remember that get quite a bit of pushback because it'd Be radical at the time, but we just did it anyway. And so that turned out to be the right thing to move. And I would rather people trust each other. And when an engineer want to go, they should have a really great relationship with their manager where they just talk to the manager, hey, look, I want to do this. And the manager should be generally supportive instead of saying, no, you belong to me, that kind of thing, which is the wrong thing. I have a saying that I share with you guys all the time, right? It's not a jail. We can't lock anybody down. Everybody have free will. If they want to work somewhere, they should have the ability to do that. And we should create more opportunity. And then we also to support that, we publish internal job board. Anything on the outside see, we see on the inside. And you should be able to shop within all the opportunity to have inside the company and stay with the company. And why make it so hard and end up leaving the company? That's just a silly thing.

[Travis Kalnick]

I remember at Uber, in some of the meetings, either all hands or team meetings, you gave talks that were memorable and one of the most memorable. I asked around former Uber folks and Charles specifically, he was on the podcast. He told me that his most vivid memory of you is this talk or this topic about behaving work in the perspective of death.

[Tuan Pham]

Yeah, I don't remember that exact speech, but I do have that line of thought in my head all the time, right? And sometimes I would change, share with different audience with different context, but it is. It's all about finding one, you know, purpose and not take oneself too seriously. Right. If you look at people, the most accounted people don't take themselves that seriously, right? The more you know, the more you know, you don't know kind of thing. And people who are arrogant tend to like not know enough yet or they have all that, right? So, yeah, So I always take opportunity to remind people to kind of be humble. And the example I use always is use myself, right? I said, look, you know, when you're in an important position, people treat you really well. But don't let that get to your head. It's not you, it's a position you hold. And I remember saying this. We were like, the moment I stop being CEO of Uber, nobody can care or know about me. They go top of the next cto, right? And that's always happened, right? The world forget about us, right? So the only thing we can really do is in any job that we do, do the best that we can to help each other to leave A lasting positive impression in each other. And one day everything ends, a job end, and then I'll get to the morbid stuff, like life even end itself. And so then I measure myself like, what is my achievement that I would be most proud of? And I said, well, when I'm gone, the thing I'm most proud is how many people remember how I was good to them or helpful to them and for some number of years, right? And that is that because I can't take anything with me. And so live in the moment, be as best as you can to everyone and be very as constructive as you can and leave a good life behind you. So that was a whole gist of that.

[Travis Kalnick]

It feels to me sometimes there's talk about how you can network better and grow your network, but sounds like this is almost like it's not a hack. It's just do the work, right?

[Tuan Pham]

Do the work and then the right thing happens, right? But you can't do the work in service of that goal because that's very artificial, right? Just be genuine, just be yourself, be helpful, be constructive, uplift everybody, help people along the way. Coach being doing it altruistically. And let me show you another angle too, which I personally experienced over and over again. It's not only that other people around the industry pull you into good stuff. When you pull in and you don't have people to support you succeed, you would not succeed also. And here is an example at Uber, right when I came in again, the engineering as we talk about very, very young inexperience, did not know how to build system at scale, reliable, all that stuff. And the network that I have, who really knew how to do that was from VMware where you're building system software, we're building operating system. Right? Rigorous principal level engineer experience.

[Travis Kalnick]

No, like in their sleep, they can do it. Right?

[Tuan Pham]

Right. So when I came in and when I have to like work with the team on dispatch, I pull in the first engineer from Uber to lean land on that team. His name is George. And so he there and he worked for everybody else. Uplift with everybody there, right? That and then from VMware. Yeah, yeah, yeah, yeah. And then when I built payment system, had to pull in another a few more ones. And then when we get to build schema less, it was the Denmark team, right. I pulled the top four engineer from my VMware team and I moved them down from one floor to the next in Denmark.

[Travis Kalnick]

This is why we had a Denmark office, which was correct. Which was one of the best infrastructure Offices at Uber.

[Tuan Pham]

And they built schema less they built

[Travis Kalnick]

schemas, they built a lot of other.

[Tuan Pham]

Right. And so now if I weren't a good person doing a good job for them with them or whatever, why would they come?

[Travis Kalnick]

They would, they wouldn't answer the phone.

[Tuan Pham]

Yeah, they wouldn't answer the phone. Right. But every single one that I call because I really needed help, they all came initially they all asked the same question, why a taxi company? But when they understand that, they came. Right. But they came because they still enjoy working with you. Right. There are people who work with me for five different companies over 28 years

[Travis Kalnick]

and that always surprised me. And I think this is something that, that people might overlook a little bit as they're building out offices. I'm talking with founders is one thing is where you can hire the other things where the good people stay for a long time and there's a lot of value in that. And Denmark kept being very core critical infrastructure.

[Tuan Pham]

Yeah, core infrastructure software team. And that's one of the things we had to build at Uber because back then when I came in, we didn't build infrastructure software. Right. We just used existing open source stuff. Right. And we built that. And another thing, thing that I discover along the way is great talents are everywhere, but you have to bring opportunity to them. They don't necessarily relocate from Denmark to San Francisco. And so that's why we end up having nine ng offices around the world because we have a lot of work need to be done. We didn't go to other places because of cost savings, anything like that. We go there because we have needs and we have world class talent and we just cherry pick the world class talent, doesn't matter what size it is. And Denmark team was small compared to team in India, et cetera. But you know, there was really great talent infrastructure and we'd invest on that Lithuania, amazing DevOps team. And so we just go to where the talent is and then we bring the great work to the great talent and then we establish a structure to manage and give people first class ownership of the problem. And then, you know, everybody's kind of equal at Uber.

[Travis Kalnick]

You, you talked about several times of your three chores of duty. Which ones were these?

[Tuan Pham]

Yeah, again it comes back down to purpose. So when I do something, I try to be intentional about why am I doing something, what's my purpose of doing that? And so of course my purpose to come into Uber was hey, let's build this business. I just build a tech that support the business. And so the first couple years, 18 months, 24 months were fixing a lot of the broken stuff. Things weren't reliable, become more reliable, et cetera, et cetera, rebuild things. Basically just get things to work and work well. And then along the way, you know, these things don't end. And beginning on a particular day, it just phase in and out, right? So the phase two that will call us, my second tour of duty was scale. Worldwide scale. That was China. That was massive scales everywhere in every dimension. And so, yeah, so at each of those phase, when you're done with that phase, you ask yourself, am I still useful? Do I want to re up? Right. My commitment and energies and everything else. And so the first two phases were, no question, right? We're there to do that. And then as phase two were about to wrap up, right about 2017, we actually kind of stabilized. We're really big now. I was actually asking myself that question, am I needed here anymore? And I was actually about to wrap it up that summer because, you know, at that point we had also another SDP that was higher. And I think he's really, really great technically. And I can like feel very at peace kind of, you know, there's. There's someone who really take it on even better because the person has done even bigger thing at Google, right? Yeah. And then. But that didn't work out. And then Uber has a really rough year. So then I have to like sign myself to the third tour of duty, which is. And what is the purpose of that? You know, help the company get through the turbulent years. And I had no idea at the time when that phase would end. I just kind of know the condition for that to end, which is whenever the next CEO arrive, right. And then after that, whether that person like me, I like that person, or whatever it is, that's to be decided. But that third phase, I have to stick it through because, you know, we owe it to ourselves and we owe it to everyone along the way who have built Uber to that point, right. To. To get through that turbulent phase. So we did that. And then now when the new CEO come in, and, you know, I stayed on until 2020.

[Travis Kalnick]

And so in 2017, I remember it was really turbulent. Travis had to step down for a while. A group of, I think 14 people who were Travis's direct reports, they took over steering the company. You were one of them. So this is the point where you decided that if everything would have gone smooth, you might have actually just left, but you decided to stay on to help the company, help the team, to help us get Through.

[Tuan Pham]

Because Uber was built by tens of thousands of people, right? Past and present. The fact that people built somewhere and then left already before, that's so fine. That work was still in there in some way, right? That led to that Uber that we have there. And it was a really important thing that we all built that many of our lives were.

[Travis Kalnick]

And then just to suck it up, we went public, which, which, which went good. And then it went okay. And then of course, Covid happened, which really hit Uber. And a few months later, into Covid, you did step down. Why did you leave Uber? And, and why. Why was the timing when it was. And what motivated you to say, okay, this is the time to, to go?

[Tuan Pham]

Yeah, it, it didn't have anything to do with COVID really. It. You know, I was. I'm lucky enough to arrive at a point in life where money doesn't matter, right? And so then I asked myself, why am I doing anything? If I wake up every day and spending X number of hours on doing something, why would I do that versus something else? And so it comes down to three things. One is, do I really love the mission and what I'm doing? And the second one is, do I feel like my being anywhere, right. Is making a really big impact? And the third one is, am I enjoying the company of people I'm working with? Right? And if several of those dimensions are lacking, then at some point it's not enjoyable in totality anymore, right? Then it comes down to, okay, when you wake up and you spend 50 hours a week doing something where money doesn't matter anymore. I live very modestly, so it doesn't. Doesn't change anything. So then why would I do that versus doing some other thing? And so I think that was, that was the realization at that point where I'm more like, okay, I'm there doing a big job, but more or less running things rather than, you know, being very much more effective in building the company, like in the early days. And so, and at that point, I think it's actually much better for other people who take a crack at that job again. It's, you know, like, everything ends, right? And so you have to decide yourself.

[Travis Kalnick]

And it did give opportunity to other people, right? So like, and they did pick it up. Now after Uber, I, I remember you did an interview with, with a publication. I think you said that you're thinking of retiring or you'll see, but then you are not done. Oh, no, you, you did other stuff. Coupang Nubank Fare. Can we talk about what, what, what what happened? What was your thinking? And you never even left for. For a moment, honestly.

[Tuan Pham]

Well, I blame that on Covid. So seriously, that one Covid had everything to do with it. So when I left we had a plan to travel the entire summer because our daughter was between eighth grade and ninth grade when she was about to enter high school. We had African safari plan, we have all the other travel plan. Everything got shut down. Everything got shut down. All the flight get canceled, all the country closed and so we stuck at home. Right. And I don't remember at a time where I'm the only one who go to supermarket and then like very sparse to kind of race through it, pick up what you need and you get out with all the mass and yeah. And so we kind of bored though. And so I'm bored. So I sit at home and we all got on video zoom call and lots of people want to kind of chat with me to not surprising. And so I took a bunch of call and one of them was the founder of Coupang and we had really great chat and you know, like hard charging person wanting to get a lot of things done and I really like that and I think, well, I'm not doing anything here anyway so might as well make myself useful. Right. Again, it's about how you spend your time. And so as I did that and yeah, I joined there and I helped some but I learned also a ton because that's also a very interesting area. Right. Of Amazon style logistics. And the way Coupang does it is to talk about five hours, six hours delivery.

[Travis Kalnick]

Wow.

[Tuan Pham]

Yeah. You order before midnight and the thing show up on your doorstep five o' clock in the morning, five, six. And I, when I was there, I joined the delivery truck putting packages in front of people's home like 2, 3 o' clock in the morning. And it's, it's brilliant. Right. And all those things that you learn and you, you, you learn a whole bunch of these things. And so yeah, it's a really great use of time. Right. Given the circumstances. Yeah.

[Travis Kalnick]

And then you became, was it, is it an advisor or a board member at nubank?

[Tuan Pham]

A board member, yeah.

[Travis Kalnick]

And Nubank is for, for those that don't know and outside of the US or Europe, it is the most successful and highest valued non US companies, the largest growing bank in Latin America. It's, it's, it's extreme. It's as it's engineering culture. I hear amazing things about. You're the first person I'm actually talking about. So what did you learn there? And you're still involved, right?

[Tuan Pham]

Yeah, yeah, I'm still involved, but as a. In the. As a board member capacity. And for a while, I also took on a more active responsibility to mentor the cto. Right. A couple of them. And so. Yeah. And so, again, it's all about being useful. We all learn a lot in our journey and working with really smart people, really motivated people younger, and impart that knowledge and sharing, you know, what you see, and advice, help people move forward better, faster. And I find that very fulfilling. And so that was that. And the culture there is very vibrant. I mean, it reminds me of our early days Uber, when everybody is gung ho, hard charging the founders. Hard charging everybody is. When I visit there, usually during board meetings once a year, we kind of go down to Brazil, and we would have all hands with the entire company. And sometimes I also did all hands with the engineering team and do AMA style the way we all did Uber. And so it's just very energetic. Right. And there are many factors to their phenomenal success. One is, like, very much like Uber, they actually solve the right problem at the right time. There's a whole bunch of unbanked population before nubank came along, and they deliver leapfrog of traditional banking just online on the app. And the experience is beautiful. The NPS score is through the roof. And ultimately it add a lot of value to people live. And that's why the adoption rate is crazy high. Right. And so, yeah, well executed, amazing product vision, phenomenal cultures and energy. And all those factors are very common and like, great companies. And we experienced one of those in a Uber too, in the early days. So it's really re energizing being a part of that.

[Travis Kalnick]

And they're doing great. And now you're the CTO at fair. What made you join Fair?

[Tuan Pham]

I took a couple years off when my daughter was finishing high school because I'd figured that time would not ever come back when she's gone and she's gone.

[Travis Kalnick]

Now, was it the right choice?

[Tuan Pham]

Oh, absolutely. I would not take that time back. So that was.

[Travis Kalnick]

I'm so glad.

[Tuan Pham]

Yeah. 10th, 11th grade and 12th grade, I get to stay home, drop her off, pick her up, cook, you know, hang out together, help with college application, all of that stuff. And so the bond we had was really cool. And as I was thinking about her going to college, I was thinking, wow, I'm gonna have a lot of time on my hand, so what should I do?

[Travis Kalnick]

Here we go again.

[Tuan Pham]

Exactly right. And so should I join another board? Which I was about to and then at the last minute some partner, sequoyah asked me to meet, meet Max, the CEO of Fair and really liked him. Very smart. Again, all the same characteristics, very smart, very hard charging, want to do all the right thing. The businesses empower, you know, local, you know, businesses.

[Travis Kalnick]

Can we talk a little bit about that? Because from the outside, you know, when you Google fare and you and I look at it, it doesn't tell you exactly too much, feels a little abstract.

[Tuan Pham]

From the outside it is a B2B marketplace, right. Between big brand wholesalers and retailers. So people buy that and then stock their storefront. And so all this traditional two sided marketplace dynamic apply. And the mission is very similar to Amazon Ruby, even though we are B2C. Right. This is B2B. But it's all about what can we do to empower local businesses to flourish. Right? So to buy the right thing, to sell through, make a profit, grow that business.

[Travis Kalnick]

So basically this can help small and also large businesses to actually just like grow their business. May that be like more inventory, more

[Tuan Pham]

successful, demand, more demand, more supply, all of that stuff. Right. So yeah, it's like a really marketplace. This is like really fun and very complex. And so I really like that. And I really, when I dig in through the interview process and everything else. And again, this company moved really fast. Within a week everything was finished, including my homework assignment. Right. You have to go and present and everything else. And so I really. The company moved really fast. It's energizing and the culture is super nice and super kind, you know, like no politics. Everybody's just focused on doing the right thing and working with each other, taking care of one another. So it's a trifecta. It doesn't matter if the company is really big or really small. Right. But it's got all the ingredients. So I said, well, maybe that's a good place to jump in and help out.

[Travis Kalnick]

And can you give us a little context on Fair in terms of the size of the company, the size of the engineering team, where the hubs are, what the work is like, is it in person, is it hybrid and so on?

[Tuan Pham]

Yeah, the company is about a thousand person. The engineering team, including the data science team combined is about 300 people. The work, we are in the office three days a week. Yeah, three days on the week. The other two are working remotely online for. Yeah. And some people throw up more if they live close to the office. Yeah, the engineering team, there's a portion here in SF just down the street from here and a large part is In Canada. Then we have a big office in Waterloo and we have a big office in Toronto. So I make the trip there quite often every five, six weeks or so I'm over there.

[Travis Kalnick]

And what are some interesting engineering challenges that you're excited about right now that you're solving?

[Tuan Pham]

Oh, right now, clearly the most exciting thing is AI. And how is AI changing everything so quickly?

[Travis Kalnick]

Tell me, what are you seeing, what's working, what's not on your teams?

[Tuan Pham]

In my team as well as in the company, we're using AI to boost everyone effectiveness and productivities and output. Right. And so that's one within the engineering specifically, we use AI to make, you know, search and recognition better. Right. Because the whole job is to help people discover things that would sell really well for their business and et cetera. And imagine AI as a shopping consultant. Right. And all that stuff. And then coding wise, you know, AI is doing a lot more of the coding now, but we also used different technique to actually boost entering productivity. Have you heard of like swarm coding?

[Travis Kalnick]

So swarm coding as in the agents?

[Tuan Pham]

Yeah, a whole bunch of agents. A swarm of agents.

[Travis Kalnick]

It's pretty new. So you're already using it.

[Tuan Pham]

So we are already using it. And we building Orchestrator to orchestrate the action of all this agent. And we measure first the early adopters and then the bulk of the engineer follow through after we build the more robust tooling. And we see dramatic lift in engineering output among the early adopter. The ones are really efficient at thinking this way. Right. Because it's very different from a linear kind of thinking. When I write this piece of code right now it's almost like multi threaded programming with single threaded. Right. You have to think about all these other things. You have to prompt all the actions and then you have all this code get coming back at you and you have to review it. You have to sit together. Yeah. And it required a different way of thinking and the cognitive load might be a little higher, but the output is dramatic. We have seen our best engineer double their output.

[Travis Kalnick]

But I know we're talking about that. But just to make clear, we're talking about not the code out, but the actual business out, but the impact of their work, right?

[Tuan Pham]

Yeah. The impact now depend on the evolution of AI. Right. So right now the state of the art right now is very easy to make large scale changes. Right. Cleanup and everything else. So massive productivity increase. Now we're trying to crack the next frontier which is how we get that level of productivity increase and output. Building new features on top of a Code base that are older, Right. It's not like, oh, you and I can just go build something brand new, not entangled with anything. It's really fast. The whole thing will generate for you, right? Yeah, but we got millions of lines of code and how do you deal with that and build feature on top with all those dependencies and all that stuff. Right. Can AI good enough now to help us untangle some of those things along the way of building new things? And so we actually continue to work on that and figure out how we can actually continue to boost more and more productivity out even building new feature

[Travis Kalnick]

with AI, how do you think AI will change software engineering and what a software engineer does or in what skills we value?

[Tuan Pham]

Yeah, it's already changing. I mean very rapidly, fast. These changes are faster than anything I've ever seen, including the Internet. Right. Back then I remember when we first learned how to do programming, we have to know a lot about the machine architecture, we have to know about virtual memory and then we have to learn how to write syntax and coding. All of that stuff been abstracted away now, right. Social AI used like I want X, Y and Z, blah. And it should be this way and whole thing get constructed. Right. So it elevated the level of the playing field where people who don't even know how to program can now create good, you know, good decent code and app or whatever it is that look on the surface are really good. So it is game changing. Right. It elevates the playing field. Now then, in that level of abstraction, how do you tell the great engineer from the good engineer?

[Host]

Great question.

[Travis Kalnick]

How do you.

[Tuan Pham]

Well, from what we see so far, the great engineer are still finding way to leverage this and accelerate the output even more then we see the difference between the great engineer and an average Engineer is still 2,3x in terms of their capability. They're more inquisitive, they're at the bleeding edge more, they're more innovative. Right. And there are people who like, okay, well here's the tool that you give me. I'm going to be two times more productive, right. Because I'm using this tool. It's great. But the great engine continues to break new boundaries. And so I think that is still a very. You can still, you can look at people and you can see who are the high performer versus who are average.

[Travis Kalnick]

So do I hear correctly that the traits that you're seeing in great engineers is. We didn't mention, but it's kind of given the foundations plus curiosity plus innovation,

[Tuan Pham]

fearlessness, willing to innovate. Willing to stretch, willing to try new things and break new ground. All of those traits still exist.

[Travis Kalnick]

Interesting. If I think back to like just the Uber days or your startup days,

[Host]

that those traits were kind of the traits of the standout.

[Tuan Pham]

That's right. Those are things that make someone outstanding versus someone average.

[Travis Kalnick]

So I guess maybe an advice is like, well I mean try not like if, if you were a great engineer before, just don't be complacent and keep using. That's right. Approaching the same way, Right, Correct.

[Tuan Pham]

Yeah. Complacency is death. I mean the world will move faster and faster and the moment we stand still, we are falling behind.

[Travis Kalnick]

It sounds like if you worked at a fast paced startup before, which is this is how it works. AI should be familiar. Welcome to how it was before.

[Tuan Pham]

To me it is a incredibly powerful tool. But in the end it's still a tool and you can wield the tool properly. You can do extraordinary things versus you just merely use a tool in a mundane way. You're not going to be a great stuff.

[Travis Kalnick]

So we talked about standout engineers in this age. I'd like to talk about something that I cannot talk with. Too many things. Standout ctos. You have now been CTO at multiple companies. I lost for VP of engineering. You've been at some of those highest engineering leadership and at Uber at fair, you've done an outstanding job as a cto. What is the most important job of cto?

[Tuan Pham]

Yeah, there are a couple of angle to this. One is build a high performance team. Right. Talent, culture, all of that, you know, whatever it is that you got to do. Put the org structure, put the, you know, develop the talent, prune, you know, bad folks out or whatever. Everything that you need to do to make sure that you have really high talent density. Because when you have team A, team A would just want to hire more A level players and yeah, they just intolerant of anybody who's not performing. Right. So when you get to, but you got to get to that concentration and then it's kind of just self protecting if you will. Right. And then of course you have to create an environment where people really trust each other and align and work really well together. Right. Because you put an all star team together doesn't mean they work really well if you don't have like the cultural alignment. Right. So that organizational side of things I've always deeply believed in, if you do that one well, then good outcome would just happen. It doesn't matter what you want to do. Right. They will just be able to come out with great result because we have great talent with great motivation. The other side is you have to look in the future and see around that corner. For example, I always think about two years out. What does great need to look like? Okay, do we have the key, you know, ingredient, if you will, talents and otherwise to actually get there, Whether it's architects, leadership, whatever. Right. And what problem are we trying to solve? What would the business look like? So, you know, the famous Wayne Gretzky quote is get to where the puck would be. So. Yes. And envision that future. And I would share this with everyone at every management level that when you're in any level, your job is to see a little bit further out than your folks. Right. Because your folks are busy working on the near term things. Right. And then you have to see, because if you don't do that, then no one, it's your job to actually do that.

[Travis Kalnick]

Right. Well, let's put this to the test because right. Right now is the most. So many people, including me. See, it's an unprecedented time with growth. How do you look around the corner? What do you see around your corner right now? Like, what will be coming? Maybe not if in two years, but even in six months.

[Tuan Pham]

Well, in six months, you know, we know what we need to do. In fact, it's too short, right? It's like these are the things about two years.

[Travis Kalnick]

I recently asked OpenAI on what they see in two years and they're like, oh, that's too long. Let's talk six months.

[Tuan Pham]

Yeah, but in context with everything, right? For them, they're trying to reinvent that future. And sometimes things are changing too fast there from that context. But from fair the business, yes. We know what business result we want to drive. We know what project we need to execute. Right. To me, that's pretty much lock and load. It just require good execution. Right. Good adjustment along the way. To me, 18 to 24 months out is my job to look at while my team is worrying about the six month problem. Right. And so, for example, there are many areas that we need to clean up. Right. There's the data ecosystem that's been old and same problem we saw at Uber too. You know, something changed upstream, break things downstream. And how do you really clean it up with all this, you know, older, you know, code base? Then you know, what is the next generation of search and discovery that are AI driven? Right. You know, consulting to look like productivity. Right. How can we leverage AI to like double output on, you know, future development? Right. So all of these things, what does that future need to look like? And do we have the horsepower to get there, right, in terms of expertise, management and planning, all that stuff. And so, and then if the answer is no, then it begs the next question, how do we actually position ourselves there? Who do we recruit? And so that's the job of the CEO on the sort of the non management side.

[Travis Kalnick]

And then finally, what advice would you give to a young engineer, someone, let's say 25 years old or a new grad who is entering the industry right now?

[Tuan Pham]

Lots of changes for folks who are entering the workforce right now. I have to acknowledge it's a very scary time because it's very bumpy. Even at our company right now, we still bring in new grad, but it comes through our intern co op channel, right? We're not in the world where we just hire massive number of new college grad like the old days anymore, right? But if great people are still finding opportunity, right? We have a healthy cohort of co op every single four months that come through, right? And the best of the best still get offered from us. Because if we don't hire those folks today, what senior engineer will we have for years from now? Right? You have to feed the talent pipeline. And great people are great people, they will learn and grow and yeah, and so that will always, the opposite will always be there for great talent. So invest in yourself. When a student volunteer doing interest, solve hard problem early on. The earlier and harder you work early on, the better you have in the future. If you take it too easy right now, then the road in the future might be a little harder. So I think that's the key. And then when you enter the industry, it depends on, I think career phases. I would say the first five, ten years or so, find opportunity where you learn the most that push you the most. Because those are the times that you have the most energy to develop your skill and ramp up really fast. And when you get to senior engineer, staff engineer range, then you know enough to be very dangerous in terms of making a big impact. Then seek opportunity where you can make a big impact. Maybe a smaller company will allow you like a bigger stage to actually make a huge impact, right? Take some of that risk and do that. And that phase should be about using what you know and make this big impact as you can. And you will learn along the way too. And then when you get to the next phase where hopefully if you're really good, you're already at this, you know, principal, engineer, senior staff, or on the management side, senior director, vp, whatever it is. And then that point, you learn to give back, right? You learn to coach and develop people. Along the way, you'll be leading and responsible for very big things. You know, apply that knowledge to do a really great job, but also teach and bring other people along. So different phases, you should change the priority a little bit.

[Travis Kalnick]

Tuan, thank you so much. This was a great conversation, so I

[Tuan Pham]

hope that everyone will find this useful.

[Host]

What a conversation. So many of these stories have not been told before, and I hope you enjoyed them as much as I did. The microservices story is such a good one. Nobody at Uber planned to have thousands of microservices. It happened because every time they tried to decompose the monolith, the business was growing so fast that other teams were adding to it faster than the Decomposition team could pull things out. It took two years to do something that in isolation would have taken three to six months. Uber had unusually violent business growth that resulted in unusually fast code growth, and microservices helped Uber tame its growth. But unless you're growing at the speed of Uber, you probably will not need thousands of microservices. Oh, and fun fact, in 2026, Uber has fewer microservices than they had in 2016. I also found it fascinating how Tuan's entire career was shaped by relationships he built by simply doing great work. Bill Gurley reached out about Uber because he remembered Twan from NetGravity, a company from a decade earlier that didn't even win its market. The engineers Twan pulled from VMware into Uber came because they genuinely enjoyed working with him. There was no networking strategy, just years of being good to people, compounding quietly in the background. Finally, Tuan's point about AI was an interesting one. Complacency is death. The traits that made someone a great engineer before these AI tools curiosity, fearlessness, willingness to try new things are exactly the same traits that make someone great with AI tools. The tools changed. What makes people exceptional has not do check out the show notes below for more deep dives on Uber and Uber's enduring culture as covered in the Pragmatic Enduring newsletter and podcast. If you've enjoyed this podcast, please do subscribe on your favorite podcast platform and on YouTube. A special thank you. If you also leave a rating on the show. Thanks and see you in the next one.