[00:00:00]

intro: Welcome to Chitchat Stocks on this show host Ryan Henderson and Brett Schaefer analyze businesses and riff on the world of investing. As a quick reminder, Chitchat Stocks is a CCM media group podcast. Anything discussed on Chitchat Stocks by Ryan, Brett, or any other podcast guest is not formal advice or recommendation.

intro: Now, please enjoy this episode.

Brett: Welcome in. We have another episode of the Chitchat Stocks podcast for you this week. We have a fantastic interview coming up with Shawn Wang from LatentSpace. It is a, I'll say covering anything AI. A lot of the stuff, you know, for me and Ryan, it might be going over our heads and it might be a little too hard technically for us, but that's what we brought on Shawn to the show today.

Brett: For a lot of public market investors, this new [00:01:00] AI stuff, it's hard to You know, see what is, what is working, what's just a narrative, what all the stuff that's getting thrown at us during this boom times. So Shawn, we wanted to bring you back on the show. You came on, I think almost exactly two years ago now to talk more cloud stuff.

Brett: Now we're really going to talk about cloud AI and how it is impacting the startup ecosystem. So Shawn, as we kick off the show. What is your relevant expertise in this booming AI field? 

swyx: Oh God, that's the million dollar question here. So I am so for, for listeners who haven't heard back the previous episode that I was on I was finance and public markets guy.

swyx: And I was, I was in a hedge fund for my first career. And then I changed careers to tech where I worked at AWS and three unicorn Sort of developer tooling cloud startups. My relevant expertise is you know, on, on some [00:02:00] level, I, I'm just a software engineer that is building with AI now. And then on another level, I had, I actually, when I was an options trader back in the sales side, I actually did a lot of natural language processing of the Bloomberg chats.

swyx: So I fed all of the Bloomberg chats into a pricing mechanism. Then built our global pricer. So our entire options desk was running off of that thing. This was about 13 years ago. So so you know, I, I've always had some involvement with like AI, but like, you know, it was never a big part of my identity and I think.

swyx: The more foundation models came into focus, and foundation models is a very special term as opposed to traditional, maybe machine learning finance that a lot of your listeners might be familiar with then you start to build differently, and there the traditional software engineering skills become a lot more relevant.

swyx: So relevant expertise now is that I, I guess I've sort of popularized and created the term of AI engineer, which you can talk about and created the industry such that Gartner now considers, considers [00:03:00] it like the peak of its hype right now. And I, I consider that both a point of success and also a challenge because I have to prove Gartner wrong that it has not peaked, but you know, they put us at the top of the hype cycle, which is kind of funny.

swyx: Because I started it, so. 

Ryan: Yeah, it's it's a unique challenge but yeah, funny anecdote. Okay, so a lot has changed since we last spoke. Yeah. Pretty much this whole world of AI that everyone's talking about now or at least has become mainstream has, I believe that kind of kicked off right after the discussion or our last discussion.

Ryan: So I guess the last discussion was really focused on the cloud computing industry broadly. And that was actually right around the time when AWS. Azure, GCP all the revenue growth rates were coming down and actually now with the hindsight bottoming. So my question for you is what has, I guess, [00:04:00] what has changed over the last two years and why has revenue growth at the big cloud providers re accelerated?

swyx: Yeah, again, like, revenue growth at big cloud providers is due to factors that, you know, probably I don't have a full appreciation of. I also challenge the fact, the idea that everything has changed. You know, I think in some ways, this is just like the next wave of something that was just a broader, maybe like 20, 30 year long trend anyway.

swyx: You know, we, we needed more cloud compute. Now we need even more cloud compute. Now we need more GPUs in the cloud instead of CPUs, right? Like, what's really changed? I don't know. Like, you know, people still want serverless everything. People still want orchestration. People still want you know, unlimited storage and bandwidth and all the sort of core components of cloud.

swyx: In that sense, it hasn't really changed. I do think that if you see there are plots over time of the amount of money and flops invested in machine learning models, that actually used to follow a pretty log linear Moore's law type growth chart for the last like 40 years. [00:05:00] And then, You had 2022 happen and now everyone's like, oh, you can train foundation models now.

swyx: And actually you've seen a big inflection upwards in the amounts that people are throwing in throwing the money in there just because they see the money now. So like every, it's like obvious to everyone, including us, including me in a way that it wasn't obvious to basically everyone, but Sam Altman and Satya Nadella circa 2019.

swyx: Like they knew this. Four years five years ahead of everyone else. And that's why they went big on OpenAI. But now that we see this, obviously everyone's throwing money into NVIDIA, basically. 

Brett: I had, why, why are, and this is maybe a question I think I know, but I'd like the answer again, and it feels like it's maybe a basic question, but a lot of, I think listeners are going to want to kind of understand this connection.

Brett: Why do these new AI companies require so much upfront spending? On NVIDIA chips, cloud computing costs. All that stuff. 

swyx: Yeah. I mean, so [00:06:00] you have to split it by whether you're a foundation model lab or you're basically everyone else that consumes foundation models. So the rough estimate for, let's say GPT 3 was like 50 million to a hundred million in compute for one run.

swyx: And for every one successful final training run, maybe you have between a hundred to a thousand. Prior runs before that, right? So just pure R& D. The estimate for GPT 4 was 500 million. We've actually had two generations of frontier models since then, just for OpenAI. So that would be GPT 4. 0 and GPT those are the models that, those are only, only the models they've released.

swyx: And also not, those are only the text models, we haven't counted the video models and all the other stuff. So it's just a lot of upfront investment, right? Like, I think it's, it's like the classic capital fixed costs upfront thing, where, you know, you have a pre training phase where you're just consuming all of the internet.

swyx: [00:07:00] Data that's, you know, there's nuances to that, but we won't go into that. And, and, Alka, Alka comes the other end, you know, 3 to 6 months later, Alka comes a model that you then spend another 6 months fine tuning and red teaming, and post training, and then it's ready for release. So, like, so there...

Plus, Shawn started the AI Engineer movement with his essay Rise of the AI Engineer and organized two incredible AI engineer conferences in the past twelve months - AI Engineer World's Fair and AI Engineer Summit

And Shawn has angel invested in DevTools like Airbyte, Railway, Supabase, Replay.io, Stackblitz, Flutterflow, Fireworks.ai while running the DevTools angels community.

Besides this, Shawn curates DX.tips (DevTools magazine) and in a past life wrote the Coding Career handbook, championed learn in public, cofounded Svelte Society and was previously Head of Developer Experience at Temporal, and a Developer Advocate at AWS and Netlify.

Also, before this, Shawn had a very successful career in investment banking, trading, building data pipelines and performing quantitate portfolio management. I think this brings him a very unique perspective - I've always admired his ability to zoom out and see the big picture and the trends.

Even though Shawn is now all-in on AI, he's still one of the go-to authorities on DevTools go-to-market.

As you can tell, Shawn is someone I deeply admire. So I'm glad he came back.

What we discuss:

• Organizing the AI Engineer Conferences
• Rise of the AI Engineer
• Intentionality and principles (yes we even talk about Alcoholics Anonymous)
• The AI CEO
• Invisible deadlines
• Ilya believing in AGI more than most people at OpenAI
• Are developers going to be obsolete? 
• Thor convinced swyx to invest in Supabase
• Building DevTools that work well with LLMs
• Angel investing in DevTools - why and how
• Is DevRel dead?
• How to hire DevRel
• Why DX.tips exists

Links:

• Rise of the AI Engineer https://www.latent.space/p/ai-engineer
• Latent Space Podcast https://www.latent.space/
• swyx's Twitter https://x.com/swyx
• swyx's website https://www.swyx.io/
• swyx's LinkedIn https://www.linkedin.com/in/shawnswyxwang/
• smol.ai https://smol.ai/
• DevTools Angels https://github.com/sw-yx/devtools-angels
• DX.tips https://dx.tips/
• DevRel's Death as Zero Interest Rate Phenomenon https://dx.tips/zirp 
• AI Engineer Summit https://www.ai.engineer/summit/2023
• AI Engineer World's Fair https://www.ai.engineer/worldsfair
• Coding Career Handbook https://www.learninpublic.org/
• Shawn's previous appearance on Scaling DevTools https://podcast.scalingdevtools.com/episodes/swyx 
• Eisenhower Matrix https://asana.com/resources/eisenhower-matrix
• Thor from Supabase https://x.com/thorwebdev
• Solaris AI coworking space in SF https://www.solarissf.com/
• Browserbase https://www.browserbase.com/
• Indent https://indent.com/ and Fouad https://x.com/fouadmatin
• How to do hackathons https://dx.tips/hackathons
• How to do conferences https://dx.tips/conf-guide
• How to hire DevRel https://dx.tips/mailbox-first-devrel-hiring
• Climbing the ladder of abstraction with Amelia Wattenberger https://www.youtube.com/watch?v=PAy_GHUAICw...for the job. And they should not be doing that job and they should try something else to do. People pay for it because they need the job title to be filled more than they need that person. Those good people are very hard to reach.

  That's one thing there. I also mentioned some other things that I've found in the different roles in the category: 

  Bottoms-up and open source have been very challenging in the growing a company success criteria. That's what different roles focus on: bottoms-up and open source, and particularly open source. You don't have to be open source. 

https://www.heavybit.com/library/podcasts/generationship/ep-18-intelligence-on-tap-with-shawn-swyx-wang?utm_campaign=coschedule&utm_source=twitter&utm_medium=heavybit&utm_content=Ep.%20%2318,%20Intelligence%20on%20Tap%20with%20Shawn%20%22swyx%22%20Wang

https://open.spotify.com/episode/45dTtNCiIxqySG1lU5addY?si=SeMrk4FBR_yGc4NtG8Ll5Q

In this episode, I chatted with Shawn Wang about his upcoming AI engineering conference and what an AI engineer really is. It's been a year since he penned the viral essay "Rise of the AI Engineer' and we discuss if this new role will be enduring, the make up of the optimal AI team and trends in machine learning.

Timestamps

00:00 - Introduction and background on Shawn Wang (Swyx)
03:45 - Reflecting on the "Rise of the AI Engineer" essay
07:30 - Skills and characteristics of AI Engineers
12:15 - Team composition for AI products
16:30 - Vertical vs. horizontal AI startups
23:00 - Advice for AI product creators and leaders
28:15 - Tools and buying vs. building for AI products
33:30 - Key trends in AI research and development
41:00 - Closing thoughts and information on the AI Engineer World Fair Summit

This is one of my favorite episodes of their NPR podcast parody of Serial.

https://www.listennotes.com/podcasts/a-very-fatal-murder/episode-5-part-1-did-my-tJbSp9yP2wU/

• [00:02:05] Elements of Intentionality - Taste and Standards
• [00:05:17] Elements of Intentionality - Intentionality is All or Nothing
• [00:06:50] Serena's path to Intentionality
• [00:10:24] Elements of Intentionality - Fantasy
• [00:10:55] Elements of Intentionality - Tenacity & Resilience
• [00:14:13] Where to be Intentional - Relationships
• [00:17:48] Where to be Intentional - Art
• [00:19:50] Where to be Intentional - Work
• [00:24:30] Elements of Intentionality - Stubbornness
• [00:26:03] Journaling?
• [00:28:28] Listing Intentions?
• [00:30:52] Applying Intentionality - on a medium priority
• [00:37:32] Dropping Intentions
• [00:42:18] Serena asks: Why do you want to live your life with intentionality? 
• [00:43:21] Serena asks: What is Intentionality for you?
• [00:47:06] Serena asks: What has kept you from Intentionality?
• [00:50:52] Intetionality is Lonely 
• [00:52:38] PSA: Serena's eggs are amazing
• [00:53:08] Back to Health
• [00:57:24] Intentionality Inspirations - Ramit Sethi and Ira Glass
• [01:03:02] I should write more
• [01:06:45] Closing - Intentionality and Fulfilment

1. here are the recommended resources for others who listened 
   • latent space university: https://www.latent.space/p/lsu-beta
   • AI engineering 101+201 https://www.latent.space/p/aie-2023-workshops
   • Andrej Karpathy's software 2.0: https://karpathy.medium.com/software-2-0-a64152b37c35
   • Voyager paper: https://arxiv.org/abs/2305.16291
2. 
   
3. 
   
4. 
   

January 10, 2024

https://realworldserverless.com/episode/92i

https://www.cognitiverevolution.ai/ai-engineers-pendants-and-tensions-between-openai-and-developers-with-swyx-of-latent-space/

https://freecodecamp.libsyn.com/90-shawn-swyx-wang-from-dev-to-ai-founder

https://twitter.com/swyx/status/1674895620870651909?s=20

I felt like the space wasn't info dense enough for the main Latent Space pod but you get the full show as loyal swyx mixtape subscribers.

https://www.se-radio.net/2023/05/se-radio-563-david-cramer-on-error-tracking/ 1hr in

https://softwareengineeringdaily.com/2019/12/19/no-code-with-shawn-wang/

The software category known as “no-code” describes a set of tools that can be used to build software without writing large amounts of code in a programming language.

No-code tools use visual interfaces such as spreadsheets and web based drag-and-drop systems. In previous shows, we have covered some of the prominent no-code products such as Airtable, Webflow, and Bubble. It is clear that no-code tools can be used to build core software infrastructure in a manner that is more abstract than the typical software engineering model of writing code.

No-code tools do not solve everything. You can’t use a no-code tool to build a high performance distributed database, or a real-time multiplayer video game. But they are certainly useful for building internal tools and basic CRUD applications.

We know that no-code tools can create value. But how do they fit into the overall workflow of a software company? How should teams be arranged now that knowledge workers can build certain kinds of software without writing code? And how should no-code systems interface with the monoliths, microservices, and APIs that we have building for years?

Shawn Wang is an engineer with Netlify, a cloud provider that is focused on delivering high-quality development and deployment experience. Netlify is not a no-code platform, but Shawn has explored and written about the potential of no-code systems. Since he comes from a code-heavy background, he is well-positioned to give a realistic perspective on how no-code systems might evolve to play a role in the typical software development lifecycle.

further reading

• https://www.theverge.com/22309962/timnit-gebru-google-harassment-campaign-jeff-dean
• https://docs.google.com/document/d/1f2kYWDXwhzYnq8ebVtuk9CqQqz7ScqxhSIxeYGrWjK0/edit

to read: https://overcast.fm/+HaNPbG9CU/24:00

6:55 - Product versus Platform
9:05 - Durable Functions
13:49 - Coding Career Handbook for Junior to Senior Developers What Inspired You To Write It
16:02 - What Most Developers Should Know after They Get Their First Job
21:36 - How Did You Survive during the Pandemic and no Flight Policy
23:34 - Jsconf Asia 2018 Talk
25:20 - The Third Age of Javascript
27:28 - Perspective On on the React Ecosystem
27:51 - What Do You Think about React Ecosystem Right Now
35:04 - Do You Learn English at a Very Early Age

My article on Google vs OpenAI: https://lspace.swyx.io/p/google-vs-openai

Transcript

Michael Lynn: Welcome to the show. My name is Michael Lynn and this is the MongoDB Podcast. Thanks for joining us. Today on the show, Lena Smart, Chief Security Officer of MongoDB, and I team up to interview Dwight Merriman, co- founder and key contributor to MongoDB. Dwight Merriman is a true tech legend. In addition to co- founding and co- creating the MongoDB database and 10gen now called MongoDB, the company. He also co- founded and led several other well known successful companies including Business Insider, DoubleClick and Gilt Groupe. In today's interview, Dwight shares openly and honestly about the motivations behind creating the database, which now actually claims nearly half of the entire NoSQL market. He talks about the decision to build the database rather than use something that existed at the time. Dwight's friendly, easy to talk to, knowledgeable, and probably one of the smartest individuals that I've had the pleasure of chatting with. Without further ado, let's get to the interview. If you enjoy the content, please consider visiting Apple Podcasts or Spotify. Leave a rating and a comment if you're able, let us know what you think. Stay tuned. Hey, did you know that MongoDB University has been completely redesigned? That's right. Hands- on labs, quizzes, study guides and materials, bite- sized video lectures, programming language specific courses. You can learn MongoDB in the programming language of your choice, Node. js, Python, C#, Java, so many more. You can earn that MongoDB certification by validating your skills and leveling up your career. Visit learn. mongodb. com today.

Lena Smart: So it is my absolute pleasure, and I'm so glad that you could make it in person today, to introduce Dwight Merriman. He is the first CEO of MongoDB, and you were still coding, I understand. You're also co- founder and director of MongoDB as of today. Are you still coding?

Dwight Merriman: I'm still coding or tinkering a bit myself, but not on the database anymore. I think there's, to really dive in and work on it, there's a certain minimum number of hours a week you have to work on it, just to keep up with the code base and the state of everything, because it's not short, it's not a small program anymore.

Lena Smart: Amazing. And also in the room we have Mike Lynn, who's our developer advocate, and I know that you'll likely have some questions.

Michael Lynn: Yeah, for sure.

Lena Smart: And just fire ahead, because probably this will be the most interesting person I'll speak to in a inaudible too.

Michael Lynn: Well I'm fascinated already and I've got so many questions for Dwight, but I'm going to let you go ahead and ask away.

Lena Smart: Cool. So the first question I have, and this has been a burning question of mine since I joined three and a half years ago, is how did you start the company? How did you start MongoDB?

Dwight Merriman: Right, so when we started, actually the name of the company was 10gen, and this was around 2008, or I forget the date, maybe two months before that, I can't remember. The original, what we were really looking at, at the time, is as myself and our other co- founders like Elliot and Kevin, we've been working on various entrepreneurial projects, and we were seeing this repeated pattern where over and over. New product idea, you start building the system. At this point, I've been doing that for quite a long time. So knew what the best practices were at the time. But it was always around that timeframe, January, 2008, whenever it was, it just seemed like it was always a bit awkward. There was awkward and un- anesthetic, and it just seemed like there was a lot of duct tape and rubber bands. And even though those were best practices. You would talk to CTOs at the time, and they would say things like, " Putting memcached in front of databases is okay, and roll your own sharding in front of my MySQL sequel or Postgres is okay, but it isn't. It was because there wasn't a better way at the time. And everything, that was really when the cloud computing EC2 was really taking off. So it was very clear to us that cloud computing was the future, and a lot of the traditional products weren't very cloud- friendly. So if you have a database that scales vertically, so I can make it bigger, but then it's a mainframe, or a Sun 6500 or something like that, that's the opposite of a cloud principle, which is horizontal scalability and elasticity. And then if you tried to do it the other way, horizontally, it was usually rolling your own when it came to operational databases. And a lot of other things, but also just agile development was the way to go then, all iterative development. But a lot of the old tools, and this isn't just databases, but languages, everything, weren't really designed for that, because they were invented earlier. So it's not their fault. So we were just saying, " Gee, there's got to be a better way to develop applications," and this is both on the how to develop them, how to code them, and also on how to scale them, and how to run them in the cloud painlessly. So our first concept was just we were going to do platform as a service. So we were going to try to do a fresh take on the developer stack, versus LAMP and whatever else was common then. And see what we could come up with. So we started building a platform as a service system. It was open source and this was very early. So I think when we went to beta, it was almost exactly the same time that Google's, was it Google App Engine?

Lena Smart: Yeah.

Dwight Merriman: It's the same time it came out to beta. So our timing was, it was like when they came out with it. And I was like, "Oh, okay, somebody there's thinking similar thoughts." And so that was fine. But a few months later, as we got a little further into it, I was thinking about it and I was like, I'm looking at things like AWS, where they have all these microservices. And they're like, " I'm not going to give you a full cloud platform. I'm going to give you some building box for your toolbox, and over time I'll give you more." Because the scope is large, so today they have a lot of services, but this, we're 15 years later- ish. So if I give you a platform though, to give you everything you need really, it's a big scope, and it's going to take quite a while to build it. So I think platform as a service makes sense, but we got further into it, and we had something working analogous to Google App Engine, or I guess, Heroku was around back then. It just felt like, " Boy, to get this true maturity, there's so many pieces that you would want in it. It's going to take a long time. This is, it's going to take a decade or something." And for a startup you only have so much runway. And it's now even today platform as a service, I think, is a valid notion and concept, but it's certainly not mature yet. The more AWS style or microservices- style approach, which you could do on all the big cloud platforms today, I just, I say AWS because I'm just contrasting it with the PaaS vendors back in the day, approach is still the dominant approach. So we've been building this, and really what were we building? So we're trying to build something where you'd write some code, you put it in inaudible, then you would just click Deploy. And it would deploy your app into our system in the cloud, try to handle scaling for you, including things like app server layer, app tier, how many app servers should there be, and low balancing for that....

https://en.wikipedia.org/wiki/Markdown

https://twitter.com/swyx/status/1241578667916042240

Shawn just posted this new essay drawing on what we discussed here:

Every Google vs OpenAI Argument, Dissected

full episode: https://www.listennotes.com/podcasts/techmeme-ride-home/twtr-spc-the-big-ai-discussion-vb0hd4qmEHA/

Featuring

• Shawn Wang – Twitter, GitHub, Website
• Adam Stacoviak – Mastodon, Twitter, GitHub, LinkedIn, Website
• Jerod Santo – Mastodon, Twitter, GitHub, LinkedIn

Notes and Links

• AI Notes
• Why “Prompt Engineering” and “Generative AI” are overhyped
• Multiverse, not Metaverse
• The Particle/Wave Duality Theory of Knowledge
• OpenRAIL: Towards open and responsible AI licensing frameworks
• Open-ish from Luis Villa
• ChatGPT for Google
• The Myth of The Infrastructure Phase

ChatGPT examples in the wild

• Debugging code
• TypeScript answer is wrong
• Fix code and explain fix
• dynamic programming
• Translating/refactoring Wasplang DSL
• AWS IAM policies
• Code that combines multiple cloud services
• Solving a code problem
• Explain computer networks homework
• Rewriting code from elixir to PHP
• Turning ChatGPT into an interpreter for a custom language, and then generating code and executing it, and solving Advent of Code correctly
• Including getting #1 place
• “I haven’t done a single google search or consulted any external documentation to do it and I was able to progress faster than I have ever did before when learning a new thing.”
• Build holy grail website and followup with framework, copy, repsonsiveness

For ++ subscribers

• Getting Senpai To Notice You
• Moving to Obsidian as a Public Second Brain

Transcript

**Jerod Santo:** Alright, well we have Sean Wang here again. Swyx, welcome back to the show.

**Shawn Wang:** Thanks for having me back on. I have lost count of how many times, but I need to track my annual appearance on the Changelog.

**Adam Stacoviak:** Is that twice this year on this show, and then once on JS Party at least, right?

**Shawn Wang:** Something like that, yeah. I don't know, it's a dream come true, because, I changed careers into tech listening to the Changelog, so every time I'm asked on, I'm always super-grateful. So yeah, here to chat about all the hottest, latest things, right?

**Adam Stacoviak:** Yeah.

**Jerod Santo:** That's right, there's so much going on right now. It seems like things just exploded this fall. So we had Stable Diffusion back in late August; it really blew up at the end of August. And then in September is when we had Simon Willison on the show to talk about Stable Diffusion breaking the internet. You've been tracking this stuff really closely. You even have a Substack, and you've got Obsidian notes out there in the wild, and then of course, you're learning in public, so whenever Swyx is learning something, we're all kind of learning along with you... Which is why we brought you back on. I actually included your Stable Diffusion 2.0 summary stuff in our Changelog News episode a couple of weeks back, and a really interesting part of that post that you have, that I didn't talk about much, but I touched on and I want you to expand upon here is this idea of prompt engineering, not as a cool thing, but really as a product smell. And when I first saw it, I was like, "No, man, it's cool." And then I read your explainer and I'm like, "No, he's right. This is kind of a smell."

**Adam Stacoviak:** "Dang it, he's right again."

**Jerod Santo:** Yeah. We just learned about prompt engineering back in September, with Simon, and talking about casting spells and all this, and now it's like, well, you think it's overhyped. I'll stop prompting you, and I'll just let you engineer an answer.

**Jerod Santo:** Well, so I don't know if you know, but the Substack itself got its start because I listened to the Simon episode, and I was like, "No, no, no. Spellcasting is not the way to view this thing. It's not something we glorify." And that's why I wrote "Multiverse, not Metaverse", because the argument was that prompting is -- you can view prompting as a window into a different universe, with a different seed, and every seed is a different universe. And funny enough, there's a finite number of seeds, because basically, Stable Diffusion has a 512x512 space that determines the total number of seeds.

So yeah, prompt engineering \[unintelligible 00:04:23.23\] is not my opinion. I'm just reporting on what the AI thought leaders are already saying, and I just happen to agree with it, which is that it's very, very brittle. The most interesting finding in the academic arena about prompt engineering is that default GPT-3, they ran it against some benchmarks and it came up with like a score of 17 out of 100. So that's a pretty low benchmark of like just some logical, deductive reasoning type intelligence tests. But then you add the prompt "Let's think step by step" to it, and that increases the score from 17 to 83... Which is extremely -- like, that sounds great. Like I said, it's a magic spell that I can just kind of throw onto any problems and make it think better... But if you think about it a little bit more, like, would you actually use this in a real work environment, if you said the wrong thing and it suddenly deteriorates in quality - that's not good, and that's not something that you want to have in any stable, robust product; you want robustness, you want natural language understanding, to understand what you want, not to react to random artifacts and keywords that you give.

Since then, we actually now know why "Let's think step by step" is a magic keyword, by the way, because -- and this is part of transformer architecture, which is that the neural network has a very limited working memory, and if you ask a question that requires too many steps to calculate the end result, it do...

https://twitter.com/i/spaces/1dRJZMpoMArGB 2hrs 43mins in

https://twitter.com/i/spaces/1dRJZMpoMArGB

https://twitter.com/i/spaces/1dRJZMpoMArGB

Selected listener survey responses

if you missed the survey in July, you can still fill it in here: https://forms.gle/gmVYak98azGi28it8

What other podcasts do Swyx Mixtape listeners enjoy?

• Conan O‘Brian needs a friend; alphalist cto podcast;remote ruby
• ShopTalk Show, WTF with Marc Maron, Hardcore History
• Corecursive, Working Code, Soft Skills Engineering
• Software unscripted, your undivided attention, startups for the rest of us
• I like software sessions by Jeremy Jung and I have listened to quite a bit of Zero Knowledge podcast which is crypto related.
• Switched on Pop, Stratechery, Radio Derb
• cppcast, hanselmines, go time
• Swyx Mixtape, Ezra Klein Show, Acquired

What are your favorite episode(s) of the Mixtape so far? 

• Star Wars Lofi because I loved it. Career+Luck as it is a great tooic
• Behind the scenes of the business world. I’m not interested enough to listen to full podcasts about business, but I really appreciate the small nuggets of insight.
• All of them not about cryptocurrency
• The levels one (because I’m a diabetic dev)
• I started extensively listening starting in June. I really enjoye the episodes covering snowflake databricks. You introduced the idea of betting on technology to me and I trust your judgement. So the podcast gives me a list of interesting tech I should at least know about without too much effort on my end.
• This one! I like it! And I can’t remember some of the very good earlier ones. I don’t listen to that many podcasts. I dunno how you do it! Kudos
• latest deep work series was great, I love to work or at least think about and how to improve. the learning in public thing was what made you follow for quite a while now/ the episode about the drowned singer/actor from glee touched me and I researched the topic and learned how to hopefully act correctly if I ever got in rip current
• One about Xbox losing all it's market share after the Xbox One launch (I love tech war stories--this field moves so fast. I find I know a lot about the preset but so little about the past)

Opening song https://www.youtube.com/watch?v=1ouIqZJ1elE

What sphinx of cement and aluminum bashed open their skulls and ate up their brains and imagination?

Moloch! Solitude! Filth! Ugliness! Ashcans and unobtainable dollars! Children screaming under the stairways! Boys sobbing in armies! Old men weeping in the parks!

Moloch! Moloch! Nightmare of Moloch! Moloch the loveless! Mental Moloch! Moloch the heavy judger of men!

Moloch the incomprehensible prison! Moloch the crossbone soulless jailhouse and Congress of sorrows! Moloch whose buildings are judgment! Moloch the vast stone of war! Moloch the stunned governments!

Moloch whose mind is pure machinery! Moloch whose blood is running money! Moloch whose fingers are ten armies! Moloch whose breast is a cannibal dynamo! Moloch whose ear is a smoking tomb!

Moloch whose eyes are a thousand blind windows! Moloch whose skyscrapers stand in the long streets like endless Jehovahs! Moloch whose factories dream and croak in the fog! Moloch whose smoke-stacks and antennae crown the cities!

Moloch whose love is endless oil and stone! Moloch whose soul is electricity and banks! Moloch whose poverty is the specter of genius! Moloch whose fate is a cloud of sexless hydrogen! Moloch whose name is the Mind!

Moloch in whom I sit lonely! Moloch in whom I dream Angels! Crazy in Moloch! Cocksucker in Moloch! Lacklove and manless in Moloch!

Moloch who entered my soul early! Moloch in whom I am a consciousness without a body! Moloch who frightened me out of my natural ecstasy! Moloch whom I abandon! Wake up in Moloch! Light streaming out of the sky!

Moloch! Moloch! Robot apartments! invisible suburbs! skeleton treasuries! blind capitals! demonic industries! spectral nations! invincible madhouses! granite cocks! monstrous bombs!

They broke their backs lifting Moloch to Heaven! Pavements, trees, radios, tons! lifting the city to Heaven which exists and is everywhere about us!

Visions! omens! hallucinations! miracles! ecstasies! gone down the American river!

Dreams! adorations! illuminations! religions! the whole boatload of sensitive bullshit!

Breakthroughs! over the river! flips and crucifixions! gone down the flood! Highs! Epiphanies! Despairs! Ten years’ animal screams and suicides! Minds! New loves! Mad generation! down on the rocks of Time!

Real holy laughter in the river! They saw it all! the wild eyes! the holy yells! They bade farewell! They jumped off the roof! to solitude! waving! carrying flowers! Down to the river! into the street!

Tim's article: https://www.timstodz.com/coping-with-imposter-syndrome/

special! the making of this mixtape was livestreamed today if you're interested in the behind the scenes process

Also recommend listening to the Dropbox talk that he mentions: https://www.youtube.com/watch?v=J8UwcyYT3z0

Transcripts

Courtland Allen
19:43
What about in the early days? Because I know for a lot of founders, those first few months where you're not sure that this is something that's going to work out or be worthwhile can be pretty nerve racking. I know you started off with CoderPad as a side project, but you eventually decided to make it full time, so where there any bumps in the road, or challenges, or any insights that you had growing from zero dollars to, what was it, $4,000/month?

Vincent Woo
20:3
Yeah, I quit it when I hit $4,000 MRR.

Courtland Allen
20:6
What was that decision like?

Vincent Woo
20:8
This is going to sound really stupid, and I had to explain this in the YC interview as well, they were like why $4,000, you haven't quit yet? I was like, I'm quitting at exactly $4,000 MRR, and they were like, why? I was like, okay, here's a reason... it's stupid. It's because when I hit $40 MRR, I posted on Facebook as a joke, haha my business makes $40/month guys, isn't that funny? Then when I hit $400 I was like haha, guess what, I made 10x what I made the last time I posted, that's crazy bro. Then I thought, oh shit, if I do this again at $4,000 that's actually kind of real stakes money, so I might as well quit then. Also $4,000 kind of pays for rent and stuff, so that's why. There's no reason to it, I just did it because I felt like it. I could've quit at any number, I mean if I quit at the beginning it would have been fine too, it didn't really matter.

Courtland Allen
20:57
In San Francisco $4,000 pays for literally just rent, haha.

Vincent Woo
21:1
I had a roommate, we were splitting a one bedroom you know, I had the converted living room kind of situation, one of the shitty old Victorian's in a basement.

Courtland Allen
21:11
Was it a hard transition going from your developer salary to just $4,000/month...

Vincent Woo
21:17
No.

Courtland Allen
21:17
Would you say that you were motivated to... what was pushing you the most, just to increase your revenue or to...?

Vincent Woo
21:21
These motivational questions are hard for me, I don't think I'm like most people. Why was I doing what I did? The truth is, I don't know. I don't actually believe that most people know why they do what they do. I was doing a thing because it seemed like the right thing to do but... okay, I'm going to take a moment to explain. I'm what you might call an optimistic nihilist, like I don't think anything's really real, up to and including money. Money is like a dead person's face painted on a green piece of paper... that it signifies material wealth to me is almost amazing. That, that system actually works to me is terrifying and awesome at the same time. So yeah, I thought it would be fun to make more money, but I knew abstractly that if I failed at CoderPad, literally the worst possible thing that could happen to me... is I would just get a job. Which I had proven that I had been able to do at least a couple times before that, so I wasn't worried about it. There was no anxiety for, because to me this is all a big game.

Courtland Allen
22:22
Yeah, it's almost like a role playing game. Where you're essentially leveling up and acquiring skills, and to what end... I don't know haha.

Vincent Woo
22:31
I think of it more like an open world exploration game, like GTA or whatever. Like just seeing how much you can get away with before everyone figures out that you have no idea what you're doing, and you're just making everything up as you go along.

Courtland Allen
22:41
So one of the reasons I asked you about your motivation was because one of the earlier things that I saw you in was actually a video where you gave a talk at Dropbox.

Courtland Allen
23m 9s
Well that's what I wanted to ask, why give a talk like that?

Vincent Woo
23m 12s
It was to provoke the audience.

Courtland Allen
23m 14s
Did you want to tell them that...

Vincent Woo
23m 17s
That they were doing their lives wrong? Yes.

Courtland Allen
23m 18s
How did they take that? They seemed pretty supportive.

Vincent Woo
23m 21s
They liked it. I mean it was tongue in cheek, obviously. It was in this building, probably on this floor, just a different room, it's Stripe now. We could do the same thing if you want... could come back and do the same talk again, in the same room. Why did I do that? I mean...

Courtland Allen
23m 40s
The impression that I got watching it was that it seems like it was a core principle of yours that people should do this, or that it's better for the world if more people do that.

Vincent Woo
23m 51s
There's more of the premise for the talk than necessarily a core belief of my personality. I mean I was invited to do a talk and they even payed me, it was crazy. This was a best topic I could come up with, so I tried to make it compelling, but I also gave reasons to not start a business. I actually think there are tons of reasons to not do it. Many people I think are unsuited for it, and also it's not terribly pleasant in a lot of ways, so I don't know necessarily that I actually recommend everybody who's listening to start a business. I know that's sort of the premise of Indie Hackers, and also it's acquisition by Stripe is sort of, how do you put it? Grow the GDP of the internet.

Courtland Allen
24m 27s
Exactly, nailed it.

Vincent Woo
24m 28s
Right, so readers at home, if you can start a business, do that, but also maybe don't. It's not easy, it's a lot of work and there are a lot of things that valuable in life that have nothing to do with money, that's how I'd put that.

Courtland Allen
24m 44s
I think one of the cooler things that you touched on, that I've also found to be true is that a lot of people who would love to start a business don't, just because they've never even considered it as an option. Especially being the smaller, Indie Hacker type business where you're just making money and you're not trying to be a unicorn, especially if you're a developer, that doesn't get advertised as much. Do you think that's changing now-a-days?

Vincent Woo
25m 7s
I think it must be changing. If there exists people like you, who's sole job is to promote this lifestyle, I would take as some indication that things are changing a bit. On the other hand, I touched on this in the talk, I think this is kind of cyclical. It used to be a cultural norm that everybody kind of wheeled and dealed, at least that's my impression. If you go in other countries that's way more true too. We probably hit peak corporatism and are trying to dial that back a little bit, I think is natural, it was probably inevitable in some respect that people would get upset with... we've had cultural satire and lampooning of corporate life for decades now. I remember my entire life I would watch stuff like Office Space, or cartoons...

Courtland Allen
25m 55s
Dilbert.

Vincent Woo
25m 56s
Yeah, no one paints a favorable light of corporate life anymore. There is no work that makes the work of an office seem noble. In some ways that's tragic because I don't think that's necessarily true, but on the other hand it reflects reality. I think the majority of of...

Transcript:

So one of the big differences between linear and other product products is that it has a local first approach where, uh, it does a lot of things locally in the app before, like communicating with the backend. Uh, why was this such an important baseline feature for you guys to get in? And how, how did you do it? If you can, uh, comment on that. So yeah, optimistic updates. I don't like, that's that, that's the story. first and offline readiness, or someone, they're almost like, like local first, like for sure. But like offline readiness for example is like a byproduct of like how, just how we build linear and we're able to like plug that in afterwards. So the goal is like build something that's really, really snappy and if you see a spinner or like a loader after your every interaction, um, you know, like, it's like if that's your foundation, like it's extremely hard to like change. So we select, build out the foundation from the get go to, uh, do, do updates locally first and then like likes us, communicate them, uh, distribute them like behind the scenes Um, of course some might fail, but like most of them, uh, they don't, uh, often the question is like, okay, like how do you do conflict resolution? Well, the short answer, like simple answer, like, we kind of like don't have to that often. Uh, so In a tool like Linear, most changes are addition on something that's like already happened. We're we're not a, we're not a Notion or Google Docs. You don't edit the same text block. Uh, of course you can edit like the same, uh, issue description at the same time. But reality is that that rarely, rarely ever happens. So hopefully we can like, solve that at some point. But right now the last update, like last update wins. Uh, so how it like technically happens is a little bit like similar to, for example, like how Dropbox builds their desktop, uh, application. Is that when you first, uh, log into linear, you get a larger dump, what we call a bootstrap, um, of kinda like all of your issues and like, like teams and users and that information. Uh, we load that first in memory, then persist in an index db in the background. Um, if you use the product that's the caching, uh, indicator that like pops up one after you're logged in. And after that, uh, we just do delta, delta syncs or like delta packages distributed through web sockets and those get up, uh, applied on the local, uh, copy of the store that you use. Uh, so we, we maintain a copy of the. Connect the whole, like the database, uh, in memory and then persisted in index db. We first update everything into that, uh, show everything in the client, then send those over. If you get something like those, like Delta packages over the wire, they select it applied like the UI react to those. Um, we use a little bit like, like it's a React application, react with type script. We use mobx under the hood, uh, to do all the updating. But, and like the developer experience for this is, uh, It is, uh, it is, it is different from a lot of like applications where you have to, like, we do all the heavy lifting for you. We do like the mutations and queries and uh, like we don't do queries, but like we do mutations. So whenever you like mutate something, we auto generate mutational mutations out of those and send those to the server. The server, uh, which then again, then creates the Delta packages for other clients. But all of that, uh, is abstracted from US engineers at Linear. So we basically only interact with the, with the store. That's the application state and you reach from it, UI updates, you change things to it. Uh, mutations are created in your background. So while it was like it's an engineering geat, uh, Tomas actually has a YouTube video about it. Uh, I can share it after the fact, but, um, It allows us to move faster while putting this upfront investment in place. Uh, it's, it's not like easy system . That's why we have and couple of other engineers working on it, uh, nowadays more, more or less full-time. Full-time as well. Like scaling this, uh, is, um, you know, like we knew like at first, like our customers were relatively small. They don't have that much data, so we can just read every, all of their information into the client. As we grow, like we know that, like, that's not gonna work out anymore. So then we started like chipping off on doing other more unique things, uh, on top of it to help it scale. Um, so that's a, it's an ongoing, ongoing thing as well. But it's kind like at first, you know, we served like the small startups, now we serve companies like cross stage companies of, you know, Brazil, retool like several hundred, uh, engineers. And then Cash App is also using us and they're, I don't remember like how big they are, but it's a sizeable, sizeable engineering organization. So we've been able to like, Scale, linear asset product? Uh, both like on from the product perspective, but also from the, kinda like the technical foundation perspective. And that's, that's in the end, like our goal, like we want linear to be the, the one tool that you use. Like if you're a small startup, like pick up using it, like don't think about it and it should, uh, get you throughout your, your like, scale IPO and beyond . So Really, I really love this. So it's like this really. Complex technical architecture that's required, but the, the thing that you're going for, the thing that you're pushing for is optimistic updates. You know, I want to do an action and feel like it instantly completed. And it's like, it's a difference between a performance first company and a company who thinks about performance after the fact. Because architecting a system or introducing that type of architecture, post shipping a product is a non-trivial endeavor. And, and it would've taken y'all a long time to get to that point. So it's like, uh, I don't know. That's, that's really cool to, to hear about. And yeah, it's, it's hard. Luckily nowadays there are starting to be some technical solutions for this. For example, repliCash, and I'm sure you you know, like bunch of like and, yeah, bunch of others. When we started four years ago, there's nothing Couch db, which, and Coach DB and Fire Base, but they only really, they didn't work for a, uh, kinda like multi-tenant team tool. It, they work really well. If you're like one user who switches between like different applications and your, your state follows you, your settings follow you. But for, for a tool like linear, like nothing existed, so we kinda like have to. Do the investment. And Tomas really went, went to town with it and I'm, I'm glad he did. Uh, I, I don't personally like have the engineering like capabilities like pull that off, but I'm really fortunate to be working with him and yeah, it's now, it's like one of the, like the defining things of, of linear. It's like the speed and the snappiness. We basically don't have, like, there's a couple of, there's a couple of spinner and like loading states in the application, but, uh, you, you, you can use the product and like try to find them yourself. I won't tell where they are. 

Transcript

So elastic compute makes sense, and scaling down because you have like ephemeral on-demand resource usage, right? Like, all of a sudden, I have to answer a bunch of HTTP requests, and so my server has to do stuff, and then everybody leaves, and my website doesn’t get any hits, and I could scale that down. With databases, if I’ve got a one-gigabyte database, it’s just like, it’s always there. I mean, all that data is there, and I could access any part of it at any time, or I need to… And we don’t know which parts. So I have a hard time with database scaling to zero, unless you’re – I don’t know, just like stomaching the cost… Or tell us how that works with Neon. Are you just stomaching the costs of keeping that online, or are you actually scaling it down?

NIKITA SHAMGUNOV

We’re actually scaling that down. Let me explain how this works, and it may get quite technical. The first thing is what should be the enabling technology of scaling that down? If you’re just kind of thinking, “How would I build serverless Postgres?” and if you ask a person that is not familiar with database internals, they would say something like, “Well, I would put it in the VM maybe, or I would put it in the container, I would put that stuff into Kubernetes… Maybe I can change the size of the containers…” The issue with all that, as you start moving those containers around, it will start breaking connections, because databases like to have a persistent connection to them. And then you will be impacting your cache. Databases like to have a working set in memory, and if you don’t have a working set of memory, you’re paying the performance hit by bringing that data from cold storage to memory.

The third thing that you will find out, that if the database is large enough, it’s really, really hard to move database from host to host, because that involves data transfer, and data transfers are just long and expensive. And now you need to do it live, while the application is running and hitting the system. And so naively, you would arrive with something that you kind of proposed, like just stomach the costs. There is a better approach, though… And the better approach starts with an architectural change of separating of storage and compute.

If you look at how databases, storage works at the high level, it’s what is called a page-based storage; all the data in the database is split into 9-kilobyte pages. And the storage subsystem basically reads and writes those pages from disk, and caches those pages in memory. And then, kind of the upper-level system in the database lays out data on pages.

So now you can separate that storage subsystem, and move that storage subsystem away from Compute into a cloud service. And because that storage subsystem operates is relatively simple from the API standpoint - the API is “read a page, write into a page”, then you can make that part multi-tenant. And so now you start amortizing costs across all your clients. So if you make that multi-tenant, and you make that distributed, and distribute key-value stores - you know, we’ve been building them forever, so it’s not rocket science anymore - then you can make that key-value store very, very efficient, including being cost efficient. And cost efficiency comes from taking some of that data that’s stored there and offloading cold data into S3.

[20:13] Now, then it leaves out compute. And compute is the SQL query processor, and caching. So that, you can put in a VM. We actually started with containers, but we quickly realized that micro VMs such as Firecracker or Cloud-hypervisor is the right answer here. And those micro VMs have very, very nice properties to them. First of all, we can scale them to zero, and preserve the state. And they come back up really, really quickly. And so that allows to us to even preserve caches, if we shut that down.

The second thing that allows us to do is live-changing the amount of CPU and RAM we’re allocating to the VM. That’s where it gets really tricky, because we need to modify Postgres as well, to be able to adjust to suddenly you have more memory, or shrink down to “Oh, all of a sudden, I have less memory now.” And so if you all of a sudden have less memory, you need to release some of the caches, and release this memory into the operating system, and then we change the amount of memory available to the VM. And there’s a lot of cool technology there, with live-changing the amount of CPU, and there’s another one that’s called memory ballooning, that allows you to, at the end of the day, adjust the amount of memory available to Postgres.

And then you can live-migrate VMs from host to host. Obviously, if you put multiple VMs on a host, they all started growing, at some point, you don’t have enough space on the host. Now you do make a decision - which ones do you want to remove from the host? Maybe you have a brand new hosts available for them, with the space… But there is an application running, with a TCP connection, hitting that system> Storage is separate, so you only need to move the compute. And so now you’re not moving terabytes of data with moving Postgres, you’re just moving the compute part, which is really the caches, and caches only. But you need to perform a live migration here. So that’s what we’re doing with this technology that’s called Cloud Hypervisor, that supports live migrations. And the coolest part is, as you’re performing the live migration, you’re not even terminating the TCP connection. So you can have the workload keep hitting the system as you change the size of the VM for the computer up and down, as well as you can change the host for that VM, and the application just keeps running… So yeah, that’s kind of super-exciting technology.

JEROD SANTO

So do you have your own infrastructure that this is running on, or are you on top of a public cloud, or how does that all work?

NIKITA SHAMGUNOV

So we are on top of AWS. We know that we need to be on every public cl...

Transcript

so let me tell you about service meshes
kind of like the terminology just to get
everybody up to speed because i know
some of you haven't looked at this space
or haven't looked at it recently
you're going to hear two terms control
plane and data plane bandied about a lot
and it's very confusing at first okay
because first of all they are sort of
poorly named and second of all there is
actually a fair amount of overlap
between the two in the in the service
offerings that we have today all right
and in the tech stacks that we have
available so let me walk you through
them all right
so starting at the uh at the service
level so you have a bunch of services
maybe they're on vms maybe they're in
kubernetes maybe they're in nomad or
fargate or whatever right but you've got
services vms or containers and you want
to have them communicate with each other
all right
well having rather than having them all
communicate with each other
which obviously means you're going to
have to build like service discovery
logic into the service itself
so if i have a player service
let's say i have a game server and it
wants to go call the player service and
say is this player real okay if so give
me their give me their information give
me their credentials okay typical
service to service uh you know function
call rpc
all right well you could have the game
server say well i'm going to call the
service registry service to see uh where
the player service lives and then i'll
make a call to the player service right
but now you're building that i'm going
to call the service registry service
which is this other service right that
you would have to build or whatever or
use ncd like grab did or whatever
and then it has to call and get the
address of the player service and then
and then it makes the call and it's like
you've built
routing logic
and discovery logic into your actual
application logic which you do not want
you do not want that okay
so
almost immediately people started moving
to proxies
you have a proxy that's your local proxy
they call it a sidecar proxy in
kubernetes land because it actually runs
in your little cluster as another
service along alongside all of your
other services
and it handles all
network uh ingress and egress for you
so you the idea is that your application
only knows about the sidecar proxy right
so to your application the proxy is the
outside world if if you you know it
knows about the service locations and it
also knows about circuit breakers and
traffic splitting and load balancing and
scaling and everything else that we'll
talk about in a bit
and that proxy becomes the thing that
other people use to talk to your service
as well because your service may be a
cluster right and so people if people
want to send something to the player
service and there's a bunch of instances
of it your proxy is the one to choose
which one maybe maybe it interacts with
an external load balancer or maybe it
does the load balancing itself the proxy
does okay by doing the health checks on
its local service instances yeah
does this model make sense so as soon as
you get this basic model of the of the
sidecar proxy you've got a helper
service that goes along with every
cluster
and it knows about the services in that
cluster and it knows about the outside
world
and your cluster talks to the outside
world through the proxy and the outside
world talks to your cluster through the
proxy okay you can use nginx for that
and that's what dropbox is doing right
but these days people always almost
always use envoy or link or d there are
a couple of other options in addition to
those in nginx but i mean those are the
really popular ones okay
envoy is the the super industrial
strength
does everything swiss army knife amazing
data plane okay by the way those sidecar
proxies i'm going to introduce you now
to the to the second term you hear data
plane the other one being control plane
data planes is just all of your sidecar
proxies in aggregate because if you if
you've got a whole bunch of clusters
right uh or even a whole bunch of
services and you want proxies for each
of them then
that mesh of proxies
that are all talking to each other
to work out the service discovery and
the routing and everything on behalf of
the application services now you've
extracted all of that you know who who's
talking to who what where and how much
and all that you've extracted it into
your
sidecar proxies
that's your data plane
it's because the network data is going
through that and i think it's a terrible
name it should have been called the
network plane or the proxy point proxy
plane would have been an absolute great
name for it right
proxy plane but no they call it data
plane so it's completely confusing
because you'd think the data plane would
be either your application logic or it
would be the data layer behind your
application logic but no
so stupid name really stupid shame on
whoever chose that name really you just
you did a huge disservice to the
industry so if you patent yourself on
the back because you came up with a name
data plane like seriously like punch
yourself in the mouth okay it just it
was a bad name
naming you know naming stuff matters man
you don't want to confuse everybody for
the rest of their lives
whatever but the name is stuck and the
name is the name now and in fact there
are well we've been ahead of ourselves
here but they're even becoming universal
standards now for data plane uh
interfaces
so the data plane i mean like you're
just going to have to learn what data
plane means it means it's the proxy
layer okay the proxies that can uh could
load balance and they can they they
handle the network for you it's software
load balancing they actually in envoy
they actually communicate through a
protocol called a gossip protocol which
is a family protocols where they're sort
of like udp multicast where
everybody just kind of like spits out
the state and consumes the state and it
sort of floods the network
and it's eventually consistent
so that's one thing to know about envoy
is they chose an eventually consistent
model
if you'll recall
i said that etcd and technologies like
it like google's chubby or uh
zookeeper or uh even hashicorp console
they're all they're all key value stores
that are
um transactional highly available and
strongly consistent okay
uh and that actually makes them uh sort
of a pain to operate
uh in practice
all of the ones that i just mentioned
chubby is an interesting one google's
chubby it was probably the first uh mike
burrows i think uh did chubby and if you
haven't heard the name mike burrows
uh you really should know his name
because you know he's easily one of the
the people who had 10 people who've had
the most impact of google right
uh he's you know i don't know he's a de
or whatever
and uh and he he came up with chubby as
far as you know among other things and
chubby is um
chubby is distinguished as
having something like seven nines of
availability it was down for 30 seconds
in 10 years something like that
so um
so yeah and it's because google has a
core competency of operating chubby at
scale
right because it's the it's the central
you know key value service for service
uh discovery and information ...

On this episode, we talk with Shawn “swyx” Wang all about developer relations aka devrels, and what their critical role at a tech-based company entails.

Is it just marketing for developers? Are they YouTube creators who like tech? Programmers who like teaching? Super fans who want to get paid to work on the product they already love?

We answer all of these questions, and also delve into the duality of the devrel role, where they benefit the company and also the developers in the community.

Don’t miss this real talk with Shawn about important but often misunderstood role in the tech business!

• About Devrel
• Manscaped
• Airbyte
• Netlify’s Jason Lengstorf
• AWS Amplify
• Webflow
• Developer Marketing: Engage and convert
• Developer marketing is the inverse of traditional marketing
• Measuring Developer Relations
• What is Developer Relations?
• Dealing with Honne and Tatemae in Japan
• Fireship on YouTube
• CraftQuest

full episode https://www.listennotes.com/podcasts/software/mental-health-with-kelsey-qraH318AdcV/

And also read: A Chemical Hunger

Shazam turns 20: https://news.ycombinator.com/item?id=32520593

Transcript

So turn to the century, the phonograph, brand

new innovation, the very first record player, consider how completely insanely

revolutionary this was, for all of human history, before the phonograph. If you wanted

to listen to music, there was only one way to do it. And that was to be in front of a

human being who was playing an instrument. There's no other way. How are you going

to listen to music? And then this machine comes along and can do it for you, can play

music. Unbelievable. Consumers didn't believe it at first. Like they literally, they had to

be shown like, no, there is not a person behind the wall playing music. Like they had to

be shown. And then once they believed it, they loved it. They brought it home. You

 know who hated this?

[00:43:45] Jordan Harbinger: Yeah. I don't know. Musicians?

[00:43:46] Jason Feifer: Yeah. Musicians hated it.

[00:43:48] Jordan Harbinger: Yeah.

[00:43:49] Jason Feifer: Hated it because they saw themselves being replaced here.

That, you know, they see this new technology doing the thing that they do and they see

change and they equate change with loss and they say, "We got to stop this," right?

They pull a margarine. And the leader of the resistance was this guy named John Philip

Sousa. John Philip Sousa, you may not know his name, but you know his music because

it's still around today. All the military marches, [Dah-dah-dah-dah] John Philip Sousa.

[00:44:12] Jordan Harbinger: You know why we know who he is? Because we have

recordings of the music.

[00:44:15] Jason Feifer: Bingo! That's exactly right. So John Philip Sousa, he at the

time was the leader of the resistance against recorded music. He wrote this amazing

piece, like Google it because it is hilarious. It's called The Menace of Mechanical Music.

It ran in Appleton's Magazine in 1906 and it contains all of these wonderful arguments

against recorded music. And my favorite goes like this. He says, "When you bring

recorded music into the home, it will be the end of all forms of live performance in the

home because why would anybody perform music in the home when now there's a

machine that can do it for them." So now, because we're going to extrapolate loss,

remember I talked about that earlier, right? Like you see changes loss and you

extrapolate the loss. So what's next? Well, he says, "Because people are no longer

performing music at home, mothers will no longer sing to their children."

[00:45:00] Jordan Harbinger: It's quite the jump.

[00:45:01] Jason Feifer: Yeah. Quite the jump. Why would they do that? When a

machine could do it. Here's another jump, "Because children grow up imitating their

mothers, the children will grow up to imitate the machines, and thus, we'll raise a

generation of machine babies." That was his argument, like a real thing that—

[00:45:16] Jordan Harbinger: Okay.

[00:45:16] Jason Feifer: —people took it seriously. I feel like it's fun to like laugh at

John Philip Sousa for this, but also—

[00:45:20] Jordan Harbinger: Sure.

[00:45:20] Jason Feifer: —I feel like what he's doing is pretty relatable.

[00:45:23] Jordan Harbinger: It is relatable. It's very human.

[00:45:24] Jason Feifer: It's very human. You have something and it works for you.

And then you see some change come along and you feel like this change is existential.

It is going to outmode you. So he tried to stop it.

[00:45:36] And it's worth asking ourselves in this moment, three simple questions.

 Number one, what is this new thing that's happening? Number two, what new habit or

skill are we learning as a result? And then number three, how can that be put to good

use? Because if you do that, it just helps you reframe any moment of change as let's

focus on the gain. Is there some kind of gain that we can extrapolate? Maybe it's not as

easy to see as the loss, but is it there and what would it look like?

[00:46:06] Because if you ran that scenario with John Philip Sousa, what you would see

is, well, okay, what new thing are people doing? Well, what they're doing is they're now

listening to music on these machines whenever they want. What new habit or skill are

we learning as a result? We're learning that we have control or consumers have a lot

more control over the music that they listen to. And therefore, also have access to a lot

more music because before the only music that they could get was whoever happened

to be able to travel to their town and perform for them. How could that be put to good

use? Well, come on guys. Come on, John Philip Sousa. Like this means that you could

record something yourself. And you could sell it and now people can listen to and enjoy

your music. And you can monetize that in ways that are much more scalable than what

you're doing now. Because you're coming from a world in which the only thing that you

do is perform for people that you can get in front of. And that means that you have a

limited number of people that you can get in front of. But if you can change that

dynamic, then man, oh man, suddenly your economic ability skyrockets.

[00:47:02] As it turns out, John Philip Sousa was protecting a system that limited his

own economic ability. And the reason he was doing that was because he was panicking

because of change. And once he figured it out, he changed his tune. That is not meant

to be a pun, but there it is.

[00:47:15] Jordan Harbinger: Yeah. I see what you did there. You are a dad, indeed.

[00:47:17] Jason Feifer: There it is. I'm nailing it. I got all the dad jokes. And he started

to record himself and he started to perform on radio and he changed. And this is

something that we all need to be mindful of. There is gain in change and we need to run

ourselves through these things that can just help us focus on it.

In this episode, Shawn Wang (swyx), head of developer experience at Airbyte, sat down with InfoQ podcast co-host Daniel Bryant and discussed the rise of remote development environments. Topics covered included, whether remote development experiences are good enough to see the death of local(host) development, what a wishlist might look like for the ultimate developer experience, and how cloud native organizations are currently developing software.

Read a transcript of this interview: bit.ly/3R3OEcD

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DX

SWYX

LocalHost

Remote

development

Transcript

eric schmidt is a business leader and

software engineer that served as

google's chief executive officer from

2001 to 2011.

under his leadership google grew from an

early silicon valley startup to arguably

the most important technology company on

the planet

schmidt is currently co-founder of

schmidt futures and sits on the board of

many public and private institutions

he is still involved with technology

consults with the us department of

defense

also talks about ai in his latest book

the age of ai and our human future

written alongside former u.s secretary

of state henry kissinger and computer

scientist daniel huddenlocker

schmidt was a guest at the milken global

conference and here he anticipates some

of the ai innovations that we will

certainly see in five years

he also predicts what we might see in 20

years

here are the details

recently in the last couple of years

there have been

extraordinary gains so for example a

team at google and at the baker lab

separately

figured out a way to actually understand

if you take dna what proteins are

generated and what their structure is

that's an extraordinary achievement in

my opinion worth a nobel prize

there are drugs being designed now that

could not be possibly

designed by humans

in any way because of their complexity

there's evidence that ai can be used in

biology ai is mapped to biology the way

math is to physics in other words

biology is so complicated that ai will

be used to interpret biology and predict

its outcome

over and over again ai will arrive in

your life

another example is the hottest area in

my industry right now are large language

models uh recently a set of startups

have been funded between 100 and a

billion 100 million and a billion

dollars

they have no current product or revenue

plans um

the the belief of the power of this

technology these large language models

are interesting because you suck all the

information in

like you read all the web which

computers can do but we can't and then

they discover things they appear to

discover a structure of language and an

example of recent google product last

week can actually translate from one

computer language to another and we

didn't give it any examples of one to

translate to the other it discovered a

structure and it can predict it

these are the beginning of general

intelligence

the the current um excitement stems from

a technology called transformers that

was invented three or four years ago and

what transformers do is it can predict

the next word after a set of words so if

you give it a sentence it can predict

what the word will be and it's done

using a complicated mathematical

technique it turns out predicting the

next word is mathematically the same

thing as predicting the next sound the

next video the next image

all of that and so you have a

unification a multi multi-modal

unification of video text and speech so

these systems sound and look like

they're intelligent

a good example is gpt3 which came out

last year

which kicked the current revolution off

you asked it

do you think like a human and it says no

i do not

because i am a large language model and

you are a i think a human who has been

taught to think in this way

now is that

it thinking about you or is it pattern

matching we can't tell and the truth is

and i'm as part of philanthropic work

i'm funding projects to try to

understand this we don't actually

understand why this works we don't

mathematically understand why it works

and we also don't understand its failure

modes

so you wouldn't want to use this as a

replacement for something that's live

critical because we can't say when it

fails when does it just crash

the current large language models for

example have trouble with the notion of

gravity so if you say to them i moved it

i moved the object from here to here and

then i put it up here and i put it down

there and so forth now everyone just

followed what i did the large language

model gets confused because it doesn't

understand gravity so the computer

scientists say we're going to now add

concepts

right

so with concepts and then with planning

maybe you get to the point where it

looks like a human-like intelligence

which has all sorts of issues

if i were 24 today this is exactly what

i'd be working on this is where the

hardest and most challenging computer

science systems problems are with the

greatest payoff

now remember that the system can predict

patterns

and if you can predict a pattern you can

also generate an artifact there's a

duality in these systems where they can

generate things

so part of the issues that we face now

is that these systems can generate

speech i'll give you an example

within five years

the following will be true

you'll be able to take a system

um take one of these language models

which would be infinitely expensive to

make but you didn't pay for it

it shows up in your doorstep and it fine

tunes the technical term is literally

fine-tuning it you fine-tune it to you

who are you what do you care about it

sort of watches you and learns from you

it learns your voice

right all of a sudden it can generate

videos with you in it

now you could think of this as a second

ai right

now the interesting thing is imagine

five years from now i install this thing

and i use it for a few years and

eventually we all die unfortunately well

it lives on

right

as a pretty good impersonation of me

and what happens when i'm dead and it's

still learning is that me

is that an artifact of me or is it just

a stupid artifact of history that you'll

keep in a box and some future will say

oh eric was so stupid back then but it's

entertaining to watch him right because

he didn't keep learning we don't know we

have no way of discussing these things

this stuff is incredibly powerful it

will be the basis of enormous gains in

human health

language translation communication

summary and education

all the things that milken represents

will be affected in an almost always

positive way having said that there's

terrifying consequences as well so the

first question has to do with jobs

does this fundamentally mean there are

more jobs or less jobs i spent my whole

life people saying computers will

replace humans humans won't have

anything to do so far that narrative has

been false notice that there's a huge

surplus of jobs and not people to fill

it certainly in the united states the

second one has to do with national

security something i've worked on for

almost a decade now

and in our in the kissinger book we talk

a lot about this

what happens when the...

more with Heidi: https://www.youtube.com/watch?v=oMbeCKh-9v4

• Nov 9 https://www.listennotes.com/podcasts/unchained/the-chopping-block-ftx-the-3ki-p42chnb/
• Nov 16 https://www.listennotes.com/podcasts/unchained/the-chopping-block-why-rlhFySZAtMB/

Gitlab data guide: https://about.gitlab.com/handbook/business-technology/data-team/platform/dbt-guide/ and https://about.gitlab.com/handbook/business-technology/data-team/

Our previous episode on dbt: https://mixtape.swyx.io/episodes/wtf-is-dbt-drew-banin

Transcript

Stefania: I wanted to maybe shift a little bit in terms of how the industry is changing before we move on to how you have seen data cultures being built and data trusts being undermined and all those things.

Can you talk a little bit about how you see the industry has changed in the past few years?

Laurie: Yeah. I wrote a blog post about this recently.

I think it's probably the thing that spurred you to invite me to this podcast in the first place.

Stefania: Correct.

Laurie: Which is about nine months ago, I was introduced to DBT. DBT has been around for awhile now, I think five or six years, but it was new to me nine months ago.

And it definitely seems to be exponentially gaining in momentum at the moment.

I hear more and more people are using it and see more and more stuff built on top of it.

And the analogy that I made in the blog post is as a web developer, it felt kind of like Rails in 2006.

Ruby on Rails was you hire someone and you say, "Well, it's a Rails app."

And on day one, they're productive.

They know how to change Rails apps.

They know how to configure them.

They know how to write the HTML and CSS and every other thing.

And that taking the time to productivity for a new hire from three months to one month times a million developers is a gigantic amount of productivity that you have unlocked.

The economic impact of that is huge. And DBT feels very similar.

It's not doing anything that we weren't doing before.

It's not doing anything that you couldn't do if you were rolling your own, but it is a standard and it works very well and it handles the edge cases and it's got all of the complexities accounted for.

So you can start with DBT and be pretty confident that you're not going to run into something that DBT can do.

And it also means that you can hire people who already know DBT.

We've done it at Netlify. We've hired people with experience in DBT and they were productive on day one.

They were like, "Cool. I see that you've got this model. It's got a bug. I've committed a change. I've added some tests. We have fixed this data model."

What happens on day two? It's great.

The value of a framework is that a framework exists more than like any specific technical advantage of that framework.

Stefania: Yeah. I love that positioning of DBT.

Do you have any thoughts on why this has not happened in the data space before?

We have a lot of open source tools already built.

We had like a huge rise in people using Spark and Hadoop and all those things for their data infrastructure awhile ago, maybe 10 years ago, and that's still happening in some of the companies.

What are your thoughts on why this is happening now?

Laurie: I think it was inevitable.

I mean, the big data craze was 10 years ago.

I recently was reminded by somebody that I wrote a blog post.

It was literally 10 years ago. It was like July 15th 2011.

I was like, statisticians are going to be the growth career for the next 10 years, because all I see is people collecting data blindly.

They're just creating data warehouses and just pouring logs into them and then doing the most simple analyses on them.

They're just like counting them up.

They're not doing anything more complicated than counting them up.

A lot of companies in 2010 made these huge investments and then were like, "What now?"

And they were like, "Well, we've sort of figured we'd be able to do some kind of analysis, but we don't know how. This data is enormous. It's very difficult to do."

It was inevitable that people would be trying to solve this problem.

And lots of people rolled their own over and over.

Programmers are programmers, so when they find themselves rolling their own at the third job in a row, that's usually when they start writing a framework.

And that seems to be what DBT emerged from.

I think it's natural that it emerged now. I think this is how long it takes.

This is how much iteration the industry needed to land at this.

Stefania: Yeah. That's a good insight.

I maybe want to touch on then also another thing that a lot of people talk about.

And ultimately, I mean, I think what most companies want to strive for, although it remains to be defined what it literally means, are self-serve analytics.

What does that mean to you and how does that fit into the DBT world?

Laurie: I have what might be a controversial opinion about self-serve analytics, which is that I don't think it's really going to work.

There are a couple of problems that make self-serve analytics difficult.

What people are focusing on right now are like just the pure technical problems.

One of the problems with self-serve analytics is that it's just hard to do.

You have to have enormous amounts of data.

If people are going to be exploratory about the data, then the database needs to be extremely fast.

If queries take 10 minutes, then you can't do ad hoc data exploration.

Nobody but a data scientist is going to hang around for 10 minutes waiting for a query to finish.

Stefania: Finishing your query is the new-- It's compiling.

Laurie: But even when you solve that problem, and I feel like a lot of companies now solve that problem, you run into the next problem, which is, what question do I ask?

What is the sensible way to ask?

And also, where is it?

Discovery is another thing.

If you've instrumented properly, you're going to have enormous numbers of data sources, even if you're using DBT.

And they're all neatly arrayed in very nicely named tables and the tables of documentation, you're going to have 100, 200, 300 tables, right?

You have all sorts of forms of data.

And unless somebody goes through every table by name and tries to figure out what's in that table.

And does it answer my question?

The data team knows where the data is and it's very hard to make that data automatically discoverable.

I don't think people have solved that problem.

Even if you solved that...

Episode Summary

Today Corey sits down with swyx, head of developer experience at Airbyte, and so much more! They begin by chatting about swyx’s career history, professional motivation, and an industry taboo: following the money. Then Corey and swyx move into a discussion about the surprisingly challenging nature of developer experience and what it means to “learn in public.” swyx talks about expertise and how to quantify and demonstrate learning. Corey and swyx discuss swyx’s book “The Coding Career Handbook” and career coaching. swyx shares about his most recent foray into management in the era of zoom meetings, and conclude the conversation by talking about data integration and swyx’s latest job at Airbyte.

Links Referenced:

• “Learning Gears” blog post: https://www.swyx.io/learning-gears
• The Coding Career Handbook: https://learninpublic.org
• Personal Website: https://swyx.io
• Twitter: https://twitter.com/swyx

Transcript

Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. Some folks are really easy to introduce when I have them on the show because, “My name is, insert name here. I built thing X, and my job is Y at company Z.” Then we have people like today’s guest.

swyx is currently—and recently—the head of developer experience at Airbyte, but he’s also been so much more than that in so many different capacities that you’re very difficult to describe. First off, thank you for joining me. And secondly, what’s the deal with you?

swyx: [laugh]. I have professional ADD, just like you. Thanks for having me, Corey. I’m a—

Corey: It works out.

swyx: a big fan. Longtime listener, first time caller. Love saying that. [laugh].

Corey: You have done a lot of stuff. You have a business and finance background, which… okay, guilty; it’s probably why I feel some sense of affinity for a lot of your work. And then you went into some interesting directions. You were working on React and serverless YahvehScript—which is, of course, how I insist on pronouncing it—at Two Sigma, Netlify, AWS—a subject near and dear to my heart—and most recently temporal.io.

And now you’re at Airbyte. So, you’ve been focusing on a lot of, I won’t say the same things, but your area of emphasis has definitely consistently rhymed with itself. What is it that drives you?

swyx: So, I have been recently asking myself a lot of this question because I had to interview to get my new role. And when you have multiple offers—because the job market is very hot for DevRel managers—you have to really think about it. And so, what I like to say is: number one, working with great people; number two, working on great products; number three, making a lot of money.

Corey: There’s entire school of thought that, “Oh, that’s gauche. You shouldn’t mention trying to make money.” Like, “Why do you want to work here because I want to make money.” It’s always true—

swyx: [crosstalk 00:03:46]—

Corey: —and for some reason, we’re supposed to pretend otherwise. I have a lot of respect for people who can cut to the chase on that. It’s always been something that has driven me nuts about the advice that we give a new folks to the industry and peop—and even students figuring out their career path of, “Oh, do something you love and the money will follow.” Well, that’s not necessarily true. There are ways to pivot something you’d love into something lucrative and there are ways to wind up more or less borderline starving to death. And again, I’m not saying money is everything, but for a number of us, it’s hard to get to where we want to be without it.

swyx: Yeah, yeah. I think I’ve been cast with the kind of judgmental label of being very financially motivated—that’s what people have called me—for simply talking about it. And I’m like, “No. You know, it’s number three on my priority list.” Like, I will leave positions where I have a lot of money on the table because I don’t enjoy the people or the products, but having it up there and talking openly about it somehow makes you [laugh] makes you sort of greedy or something. And I don’t think that’s right. I tried to set an example for the people that I talk to or people who follow me.

Corey: One of the things I’ve always appreciated about, I guess, your online presence, which has remained remarkably consistent as you’ve been working through a bunch of different, I guess, stages of life and your career, is you have always talked in significant depth about an area of tech that I am relatively… well, relatively crap at, let’s be perfectly honest. And that is the wide world of most things front-end. Every time I see a take about someone saying, “Oh, front-end is junior or front-end is somehow less than,” I’d like to know what the hell it is they know because every time I try and work with it, I wind up more confused than I was when I started. And what I really appreciate is that you have always normalized the fact that this stuff is hard. As of the time that we’re recording this a day or so ago, you had a fantastic tweet thread about a friend of yours spun up a Create React App and imported the library to fetch from an endpoint and immediately got stuck. And then you pasted this ridiculous error message.

He’s a senior staff engineer, ex-Google, ex-Twitter; he can solve complex distributed systems problems and unable to fetch from a REST endpoint without JavaScript specialist help. And I talk about this a lot in other contexts, where the reason I care so much about developer experience is that a bad developer experience does not lead people to the conclusion of, “Oh, this is a bad interface.” It leads people to the conclusion, “Oh, I’m bad at this and I didn’t realize it.” No. I still fall into that trap myself.

I was under the impression that there was just this magic stuff that JS people know. And your tweet did so much to help normalize from my perspective, the fact that no, no, this is very challenging. I recently went on a Go exploration. Now, I’m starting to get into JavaScript slash TypeScript, which I think are the same thing but I’m not entirely certain of that. Like, oh, well, one of them is statically typed, or strongly typed. It’s like, “Well, I have a loud mechanical keyboard. Everything I do is typing strongly, so what’s your point?”

And even then we’re talking past each other in these things. I don’t understand a lot of the ecosystem that you live your career in, but I have always had a tremendous and abiding respect for your ability to make it accessible, understandable, and I guess for lack of a better term, to send the elevator back down.

swyx: Oh, I definitely think about that strongly, especially that last bit. I think it’s a form of personal growth. So, I think a lot of people, when they talk about this sending the elevator back down, they do it as a form of charity, like I’m giving back to the community. But honestly, you actually learn a lot by trying to explain it to others because that’s the only way that you truly know if you’ve learned something. And if you ever get anything wrong, you’ll—people will nev...

the austin powers store page screenshot mentioned: https://inventlikeanowner.com/podcast/alex-edelman-building-the-amazon-website-in-the-late-90s/

Reddit has Two Tables (2012): https://news.ycombinator.com/item?id=32407873

https://share.transistor.fm/s/6877d1db

This little podcast/newsletter started as a little experiment last year. I never thought I would make it to episode number 50, but here we are! Thank you to the few of you out there who listen/read my ramblings about spreadsheets.

I decided to give you all a break and invite my first guest to the podcast: Shawn Wang (aka @swyx). Shawn currently works in developer experience at AWS, but has a really diverse background (check out his site to learn more). I’ve mentioned Shawn in previous episodes (25 and 49) and was honored he agreed to be the first guest on Dear Analyst. We dig into a variety of topics including negotiating your salary, Javascript frameworks, creating, and whatever else tickled my fancy.

Becoming a Jedi

I was particularly interested in a 4,000-line Excel VBA script he wrote while working as a trader in a previous job. You can learn a lot about someone from looking at their code, and that’s exactly what we did during this episode. Shawn was kind enough to share a VBA script he built back in 2012 for his team to price billions dollars worth of derivatives. I honestly don’t understand 90% of this script, but Shawn walked through a lot of the derivative concepts he had to translate into this VBA script. You can see some of his thoughts about this script in the Tweet thread below:

https://twitter.com/swyx/status/1327041894853922816?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1327041894853922816%7Ctwgr%5Ef93cc6228794ba7b8cdb0018993df1a13c16d4e9%7Ctwcon%5Es1_&ref_url=https%3A%2F%2Fwww.thekeycuts.com%2Fdear-analyst-50-walking-through-a-vba-script-for-trading-billions-of-dollars-worth-of-derivatives-with-shawn-wang%2F

I think it’s amazing that his bank relied on traders using this homegrown script to price everything from interest rates to mortgages.

One of the main takeaways from our walkthrough of this script is that the code isn’t pretty. Shawn had a problem that he needed to solve, picked up the tool that could solve that problem, and started hacking away at the solution. Shawn shared a story from his senior trader at the time on building tools for yourself:

—Shawn Wang

For the benefit of other traders out there, Shawn also believes in learning in public. Releasing this script is just one example of that. By producing content and acknowledging gaps in your knowledge, you’ll learn faster than being a “lurker,” as Shawn puts it.

No-code is a lie

We talked a bit about an article he wrote called No code is a lie, and how programmers sometimes need to get over themselves. Programmers may get caught up in the style of their code, but the end-user just cares about whether the thing works and solves their problem.

After finance, Shawn moved from Excel and VBA scripts to Haskell, Python, and Javascript. He still has a soft spot for Excel, however. With Excel, you have your database and user interface right in front of you. This not only gives people an easy way to create, but makes creation more inclusive.

—Shawn Wang

Taming the Javascript community

Shawn got really involved with the ReactJS community and eventually became one of the moderators of the subreddit after Dan Abramov asked him to help with the community.

Shawn recently stepped down from moderating the community as he started coding with Svelte, another Javascript framework. In terms of moving from community to community, Shawn made an interesting point on encouraging renewal in communities. Mods, leaders, managers, and political figures should have limited terms to encourage innovation and different perspectives. Plus, I think when you are new to a community, you get a chance to learn from the ground up from others who are more experienced. Once you’re at the top, it’s time to find a new place and rinse, lather, and repeat.

Getting $50,000 added to his salary

We both talked about our interests in Haseeb Qureshi’s blog posts on salary negotiation. If you were a developer 4-5 years ago, you most likely came across Haseeb’s posts because it shows step-by-step how Haseeb went from finishing a coding bootcamp to getting a 6-figure salary at Airbnb.

Shawn also cited Patrick McKenzie’s post and Josh Doody’s guide on salary negotiation as good resources. I remember when I was interviewing, I relied on Haseeb’s concepts to get me through the negotiation process. Long story short? You should always negotiate.

The fallacy of measuring developer advocacy programs

I’ve read various blog posts and listened to podcasts about this subject, so figured I’d ask Shawn what he thinks about measuring developer advocacy efforts since he works at one of the largest companies on the planet. Rest assured! His team has not come up with the perfect formula either. Guess where they keep track of all their speaking engagements and content? You guessed it: in a spreadsheet.

Shawn mentioned one startup called Orbit that is trying to crack this nut. They dub themselves as the “operating system of vibrant developer communities.” Their orbit model is a bit cheesy but does attempt to quantify someone’s engagement in a community:

• Love is a member’s level of engagement and activity in the community.
• Reach is a measure of a community member’s sphere of influence.
• Gravity is the attractive force of a community that acts to retain existing members and attract new ones.
• Orbit levels are a practical tool for member segmentation and used to design different programs for each level of the community.

I’m currently working on a similar program and commend them on tackling this problem :).

Other projects

Shawn finally shared what he’s working on these days:

• Wrote a book called Coding Career Handbook and maintaining a community for that
• Growing the Svelte society on Twitter
• Angel investing
• Scouting for a VC fund
• Writing on

Oege de Moor: https://www.linkedin.com/in/oegedemoor/

Codex paper: https://overcast.fm/+xs-qU9hPo/05:09

my unpublished research on Emad: https://lspace.swyx.io/p/3060cbd8-2c17-4fbf-a41e-3a9b23f5fe18

ambient discomfort on LLM size: https://www.reddit.com/r/MachineLearning/comments/wiqjxv/d_the_current_and_future_state_of_aiml_is/  https://twitter.com/swyxio/status/1576685740825579520

link |
00:37:16.960 
that I think is another angle at which you can start

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00:37:20.200 
to understand the human mind, the human body,

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00:37:22.280 
which is quite fascinating,

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00:37:23.400 
which is from the basic building blocks,

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00:37:26.640 
start to simulate, start to model

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00:37:28.960 
how from those building blocks,

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00:37:30.480 
you can construct bigger and bigger, more complex systems,

link |
00:37:33.080 
maybe one day the entirety of the human biology.

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00:37:35.820 
So here's another problem that thought

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00:37:39.680 
to be impossible to solve, which is protein folding.

link |
00:37:42.720 
And Alpha Fold or specifically Alpha Fold 2 did just that.

link |
00:37:48.840 
It solved protein folding.

link |
00:37:50.320 
I think it's one of the biggest breakthroughs,

link |
00:37:53.400 
certainly in the history of structural biology,

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00:37:55.140 
but in general in science,

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00:38:00.240 
maybe from a high level, what is it and how does it work?

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00:38:04.840 
And then we can ask some fascinating questions after.

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00:38:08.700 
Sure.

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00:38:09.980 
So maybe to explain it to people not familiar

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00:38:12.880 
with protein folding is, you know,

link |
00:38:14.400 
first of all, explain proteins, which is, you know,

link |
00:38:16.980 
proteins are essential to all life.

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00:38:18.840 
Every function in your body depends on proteins.

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00:38:21.520 
Sometimes they're called the workhorses of biology.

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00:38:23.920 
And if you look into them and I've, you know,

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00:38:25.340 
obviously as part of Alpha Fold,

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00:38:26.660 
I've been researching proteins and structural biology

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00:38:30.200 
for the last few years, you know,

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00:38:31.760 
they're amazing little bio nano machines proteins.

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00:38:34.760 
They're incredible if you actually watch little videos

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00:38:36.460 
of how they work, animations of how they work.

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00:38:39.000 
And proteins are specified by their genetic sequence

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00:38:42.600 
called the amino acid sequence.

link |

Steve's post about Sourcegraph: 

• https://about.sourcegraph.com/blog/introducing-steve-yegge
• https://www.youtube.com/watch?v=viNB7v3bgx8

5 hour walks: https://www.youtube.com/watch?v=mp_MKrnSdaM&list=PLbsKh5N-eR063R9VopWCM_SZ5ccxhNGLm&index=26

PG's essay http://paulgraham.com/fn.html

HN response: https://news.ycombinator.com/item?id=27194284

SHOW NOTES:

• Shawn’s homepage
• Temporal.io (homepage) - open source microservice orchestration
• Learning in Public - The Coding Career Handbook
• The Coding Career (community)

Topic 1 - Welcome to the show. You seem to be at the center of (or around) so many developer-centric conversations. Tell us a little bit about your background, and some of the areas you’ve been focused on. 

Topic 2 - You’re well known for The Coding Career Handbook. With so many options out there for developers, how do you frame conversations about where people should focus? 

Topic 3 - At some point, developers (like many engineers) get bored of working on the same things. Right now it seems like we’re in the middle of big changes. What should they think about the transition process? 

• Cloud distros https://www.swyx.io/cloud-distros/
• Self provisioning runtimes https://www.swyx.io/self-provisioning-runtime/ 
• Video in DevRel https://sacra.com/research/lenny-bogdanoff-milk-video-infrastructure/?highlight=ecommerce 

Topic 4 - As a developer, what are some of the best ways to get visibility of your projects? How do you find the right balance of public projects, side projects, and whatever you’re currently getting paid for (main company job)?

Topic 5 - Any tips or tricks that you’ve learned to accelerate your learning process? 

Topic 6 - How is WFH changing the developer work-life-balance?

2020 Hadoop Death Roundtable: https://www.listennotes.com/podcasts/the-on-premise-it/hadoop-is-dead-the-on-PuYEm57yaqZ/

The post that I enjoyed from Lillian: https://twitter.com/swyx/status/1395562957434544128?s=20&t=tcHfqZ4WQ1Toq7I6n6xvag

Those posts are paid, so just browse the free ones: https://lillianli.substack.com/

Her threads are pretty good too: https://twitter.com/lillianmli/status/1350857550791491591

and https://twitter.com/lillianmli/status/1372554923552964608

Previous Devrel Real Talks:

• https://mixtape.swyx.io/episodes/weekend-drop-devrel-real-talk-ep-1-ft-justin-garrison-micheal-benedict-zack-hoherchak
• https://mixtape.swyx.io/episodes/devrel-real-talk-making-2m-yr-in-devrel-ft-rebecca-marshburn-and-nader-dabit
• https://mixtape.swyx.io/episodes/devrel-real-talk-q-a-and-all-things-video-from-shorts-to-streams-ft-hassan-vercel-theo-ping-nairobi-suborbital-justin-aws

Our guests:

• Justin https://twitter.com/rothgar

Our hosts:

• https://twitter.com/Chau_codes
• https://twitter.com/RealChrisSean
• https://twitter.com/swyx

the magazine’s reporter encountered Steve manning the Apple Computer booth at a computer fair. 

People have been hearing all sorts of things about computers during the past ten years through the media. Supposedly computers have been controlling various aspects of their lives.

Yet, in spite of that, most adults have no idea what a computer really is, or what it can or can’t do.

Now, for the first time, people can actually buy a computer for the price of a good stereo, interact with it, and find out all about it. It’s analogous to taking apart 1955 Chevys.

Or consider the camera. There are thousands of people across the country taking photography courses. They’ll never be professional photographers. They just want to understand what the photographic process is all about. Same with computers.

We started a little personal-computer manufacturing company in a garage in Los Altos in 1976. Now we’re the largest personal-computer company in the world. We make what we think of as the Rolls-Royce of personal computers. It’s a domesticated computer.

People expect blinking lights, but what they find is that it looks like a portable typewriter, which, connected to a suitable readout screen, is able to display in color. There’s a feedback it gives to people who use it, and the enthusiasm of the users is tremendous. We’re always asked what it can do, and it can do a lot of things, but in my opinion the real thing it is doing right now is to teach people how to program the computer.”

Before moving on to a booth where a bunch of kids were playing a computer game called Space Voyager, the reporter asks if Steve “would mind telling us his age. ‘Twenty-two,’ Mr. Jobs said.” Speaking off-the-cuff to a passing journalist from a decidedly nontechie publication, Steve finds so many ways to demystify for the average person the insanely geeky device that he and Woz had created.”

Shawn joins Adam to discuss Amplify and its place in the developer ecosystem, whether we should care about Cloudflare, yet, and how to cope with the anxiety that can come with being extremely online. Also, it sounds like Adam is a tech bro and he's NOT happy about it.

Transcript

Adam Elmore: Hey, everyone. Welcome to AWS FM, a podcast with guests from around the AWS community. I'm your host, Adam Elmore. And today, I'm joined by Shawn Swyx Wang. Hi, Shawn.

Shawn Wang: Hey, Adam. How's it going?

Adam Elmore: It's going well. I've been extremely excited. I've said this on a ton of podcasts, that I'm excited to get on with a guest, but this has been a long time because before I took my break, I was going to get on with you. Took a big, long break, and I've finally got you on. You're somebody, and I'm going to say a lot of things, I'm very dramatic, but you're somebody that I really admire in the online space. You have this ability to think about things, and distill them, and put them out there in a way that I admire greatly. I'm so excited to have you on here. It's going to be hard for me to stay on any one topic because I have just a list of questions I want to ask you, basically.

Shawn Wang: [inaudible 00:00:52].

Adam Elmore: First, could you tell everyone on this show who you are, just the short version of Shawn?

Shawn Wang: Yeah. So I'm Shawn, born and raised in Singapore, went to The States for college and then spent my first career in finance where I did investment banking and hedge funds. Loved the coding part because every junior finance person starts to learn to code, and didn't like the stress of the finance part, so I pivoted to tech where I was a software engineer at Two Sigma and then I was in developer relations at Netlify, AWS, Temporal, and I've just joined Airbyte as head of developer experience.

Adam Elmore: Oh, I did not know you weren't still at Temporal. So Airbyte, what is Airbyte?

Shawn Wang: Airbyte is a data integration company, it basically has the largest community of open-source connectors for connecting to any SaaS API source into your data warehouse. So for anyone doing data engineering, the first task that you have to do is to get data from all the different silos of data in your business. Let's say you have a Salesforce being the source of truth for customers, Stripe being the source of truth for transactions, get all of them into a single data warehouse for you to do operations on. So the goal is to have the largest community of open-source developers for connecting all the data and liberating your data from all the silos that you have in your business.

Adam Elmore: And how long ago did you start? How did I miss this?

Shawn Wang: A couple weeks ago. I actually have not announced it on Twitter, which is why.

Adam Elmore: Oh, there you go.

Shawn Wang: I like to slow play it. So when I joined Temporal, I actually waited for six months to really understand Temporal and to practice my pitch before announcing it on Twitter. And that's how I like to do things because, well, partially I want to be fully up to speed before I represent something publicly.

Adam Elmore: Yeah. So I want to talk about that. You get very up to speed in a way that I don't see a lot of people on Twitter. I don't see them understand things in the way that you do. So you obviously write, your blog is a huge source of information for me, and I've enjoyed it quite a lot, but it's not just that you write, it's the way you think about things. Does that come from your finance, your analytical background in finance, or were you like that before, your ability to see the whole forest, take in the way things are trending and the way things are moving, put it all together and distill it into these wonderful articles? Where does that come from?

Shawn Wang: Oh, so first of all, thanks for the very kind words. I don't hear back from my readers that often, so it's really nice when I get to talk to someone like this. So yeah, I would say a lot of this stuff is actually from my finance days. This is the kind of analysis that you would have to do when you do an investment report or investment research on any stock or any industry. You want to get a perspective of what's going on, what the trends are, who the major players are, and form an opinion on where things are going. And I think taking that finance mindset into the bets I have, in terms of technologies, whether or not it's for using them personally in my personal stack or for joining them as a startup employee, I think is extremely underrated. And it's something I'm trying to model and hopefully teach people someday.

Shawn Wang: Although I'm not sure about the teaching part, because if I say like, "Get rich by doing investment analysis stock on early stage startups," I would feel like a hustler. So maybe not that, but I just do like engaging in that. And probably it's an exercise for me to think things through clearly by writing it down. And I also get a lot of feedback from that, so I actually improve and learn a lot by learning in public. And that's the other thing that I am pretty well known for, so this is the application of the general purpose learning in public principle.

Adam Elmore: Yeah. No, and I love your learning in public article. I hope more people see how you break down systems and the world around us and distill it. I hope more people do that because I'd love to have more sources of that kind of information. It's really fascinating and that's a lot of what I want to talk about today is your opinions on the future and where certain things are headed. First, I want to talk, you did work at AWS. How long were you at AWS?

Shawn Wang: A year. AWS Amplify.

Adam Elmore: Yeah. So I'd love to know, I guess what it was like working at AWS, what you took from that, but also more broadly, I want to get into Amplify and where it fits. You sort of live in that intersection. I feel like web, and cloud, and infrastructure, where things are trending, and I want to talk Amplify's place in that, but first, what was your role there like at AWS, at Amplify?

Shawn Wang: Yeah, I was a senior dev advocate at Amplify, basically doing demos and talks for Amplify. And the fun thing about working at Amplify is that you are essentially also a developer advocate for all the underlying services. So amplify is essentially a roll up of DynamoDB, API Gateway, AWS AppSync, even file storage like S3. You could do some demos with that. And I did, I made like a DIY Dropbox clone. But it's focus on front-end engineers. And I think that was the first time that AWS had ever made a dedicated arm or products for front-end engineers. And it turned out to be a really good bet because AWS Amplify was one of the fastest growing AWS services, at least during the time that I was there. So I thought it was just really compelling to try it out and obviously everyone has very high regard for AWS. There's a bunch of services that I only experienced on the inside and I only learned about once I got on the inside, and I thought that was really interesting as well.

Shawn Wang: A few things I'll point out. I really loved the AWS interview process, actually. I felt like it was very rigorous and I definitely haven't had as rigorous a process anywhere else. And they really got a good look at every single part of me before they made the decision. And for...

---

SaaS API founders should not miss this week's Cartoon Avatars interview with William Hockey, former Plaid cofounder/CTO and now founder of Column.

He does not do interviews often and rarely do you get this level of insight into a $13 billion, fintech category-defining behemoth. What follows is a TL;DR for those who, well, TL;DW.

The $12 Billion UI Decision - Owning the UI

Many SaaS API providers take pride in being "behind the scenes", or being "whitelabel" to appeal to as many enterprise customers as possible. Jeff Lawson often proudly talks about how many people use Twilio without realizing it.

TLDR: Hockey bet the company on going against that received wisdom - forcing 100% of his customers to migrate to a Plaid hosted UI with Plaid's logo and branding - over a period of 2 years, with a lot of pushback.

He estimates this decision alone was worth 90% of the company value today (!)

From the 22-26 minute mark:

When we first started, we were this transparent infrastructure provider and so the consumer had no idea who we were...

...and so what happened is you didn't know, as a consumer, that Plaid existed in that flow. We realized that this was kind of problematic because, as a consumer, you were not getting the same experience hooking up your bank account to Venmo as you were when you hooked up your account to Square Cash, or Chime or, Coinbase..

and that had a lot of security issues but also had conversion issues because every application thought that their design was best or whatnot...

so what we decided to do is we made them display a Plaid designed UI to the consumer...

We made the application insert our branding, our logo and our experience into the application. That was extraordinarily controversial, as you can imagine, because these applications want to control the experience.

One way to view this move is concluding "Plaid customers were so bad at their jobs of optimizing UI that just providing the APIs wasn't enough."

The motivations were two fold: self protection (Plaid oriented) and conversion optimization (customer oriented):

It actually started converting a lot better... the consumer actually started to feel comfortable, like hey I know this screen, I've seen this before, and it also allowed us to do a lot of micro optimizations around messaging certain banks and just allowed us to kind of have a platform that we could actually deliver content and software directly to the consumer...

Where my eyes really popped is how far they took this - forcing ALL their users to adopt this flow - near impossible for most API companies to do especially if customers threaten to leave over this decision.

but it was a very very challenging rollout - it took almost 18 to 24 months, there was a lot of pushback to it - but i think if we didn't do that, A) consumers wouldn't have as good of an experience, B) we also would have got commoditized and it would have been really easy for these applications to switch it out. It would just been a worse experience for everybody

But in the end, it was worth it:

You can try the full UX of the $12 Billion UI right here: plaid.com/demo without connecting a bank account.

You can see Stripe, a Plaid competitor that stayed relatively behind the scenes, increasingly start to own the experience with Billing in 2018, Checkout in 2020, and lots more I am unaware of. In fact, Stripe Checkout's marketing sounds eerily similar to what Hockey just said for Plaid:

Alvar Lagerlof also reports that Swedish fintech Klarna also inserts a branded UI:

This is a product direction you can expect more SaaS APIs taking going forward as they seek both to build their own customer relationships and to serve their B2B customers better (by doing their jobs better than they can).

Sidenote: Founder Intuition Over Data

What is perhaps most interesting is that this decision was made without data - Hockey felt like he would not have had support from consumers, banks, or employees - which is why these kind of high conviction bets require founder-led companies.

Also noteworthy - it took "three or four years" before it became obvious that forcing their UI was the right decision.

At 27 minutes:

We just felt like there was a bit of an arbitrage where we knew where the industry was going to play out we knew what the banks were going to react and so we just made the gut call.

This isn't something he encourages at all scales - and the transition from being a product visionary at 10 employees to a delegating leader at 1000 employees is a difficult but necessary transition.

Column: The Bank with Developer Experience

For his next act (as a billionaire, post Plaid), William

Hour 1 was Q&A - comparing notes on Vercel vs Airbyte, going deep/leveling up in DevRel (Building your Lightsaber) and on content creation (Dev.to vs Hashnode vs Substack)
Hour 2 was Video/YouTube/Twitch focused since Theo joined!

Previous Devrel Real Talks:

• https://mixtape.swyx.io/episodes/weekend-drop-devrel-real-talk-ep-1-ft-justin-garrison-micheal-benedict-zack-hoherchak
• https://mixtape.swyx.io/episodes/devrel-real-talk-making-2m-yr-in-devrel-ft-rebecca-marshburn-and-nader-dabit

Our guests:

• Hassan https://twitter.com/nutlope
• Alex https://twitter.com/alexandereardon
• Nairobi https://twitter.com/Tech4Abolition
• Theo https://twitter.com/t3dotgg
• Justin https://twitter.com/rothgar

Our hosts:

• https://twitter.com/Chau_codes
• https://twitter.com/RealChrisSean
• https://twitter.com/swyx

• https://mixtape.swyx.io/episodes/weekend-drop-coding-career-chat-the-operating-system-of-you
• https://mixtape.swyx.io/episodes/weekend-drop-coding-career-chat-finance-for-developers

Show notes and referenced links:

• Reading: https://learninpublic.org/v1-strategy-intro-tech.pdf
• Replies: https://twitter.com/Chad_R_Stewart/status/1558529083079856128

Join the Coding Career Community: https://learninpublic.org/

Follow for future spaces: https://twitter.com/Coding_Career

Comp Report: https://www.commonroom.io/blog/2022-developer-relations-compensation-report/
Slido: https://app.sli.do/event/bxvrMv1yBfycLUh7bL3aaG

Previous episodes:

• https://mixtape.swyx.io/episodes/weekend-drop-devrel-real-talk-ep-1-ft-justin-garrison-micheal-benedict-zack-hoherchak

Our guests:

• Rebecca https://twitter.com/beccaodelay
• Nader https://twitter.com/dabit3

Our hosts:

• https://twitter.com/Chau_codes
• https://twitter.com/RealChrisSean
• https://twitter.com/swyx

• https://www.youtube.com/watch?v=lklTPY4Zj7Q
• https://soundcloud.com/clublifebytiesto/clublife-by-tiesto-podcast-801
• https://en.wikipedia.org/wiki/Ti%C3%ABsto

Tracklist:

• [00:00] Intro
• [00:42] 1 John Summit & GUZ feat. Stevie Appleton - What A Life
• [03:50] 2 Fancy Inc – Circles (feat. Jack Dawson)
• [06:16] 3 Piero Pirupa - Put Your Hands Up
• [08:00] 4 Oliver Heldens - I Was Made For Lovin' You (feat. Nile Rodgers & House Gospel Choir) (James Hype Remix)
• [10:11] 5 Tiësto & Charli XCX - Hot In It (VIP Remix) 
• [13:44] 6 The Weeknd - How Do I Make You Love Me (Sebastian Ingrosso & Salvatore Ganacci Remix)
• [16:33] 7 David Guetta vs. Benny Benassi - Satisfaction
• [17:56] 8 Cat Dealers & Lukas Vane feat. Elise LeGrow - Hey Hey (Heard You Say)
• [20:13] 9 Sebastián Yatra - Tacones Rojos (Tiësto Remix)
• [23:44] 10 Axel Rulay vs. Tiësto - Si Es Trucho Es Trucho (feat. El Alfa & Farruko)
• [26:09] 11 DubVision, Otto Knows & Alex Aris - Electricity
• [28:10] 12 HÄWK & The Shooters - We Make It Pop
• [29:08] 13 Tujamo - Drop That Low (Tujamo's Secret Weapon 2022)
• [31:09] 14 Imanbek & BYOR – Belly Dancer (LUM!X Remix)
• [32:40] 15 MORTEN - No Good
• [35:39] 16 Tiësto - Baila Conmigo
• [37:12] 17 KVSH & Carola - Welcome To The Future
• [38:42] 18 Martin Garrix & Breathe Carolina - Something
• [40:21] 19 Martin Ikin - Future
• [41:38] 20 Odd Mob - LEFT TO RIGHT
• [43:08] 21 Fred Again.. - see yourself in my eyes (Sonickraft Remix)
• [45:31] 22 Binary Finary - 1998 (Whitesquare Remix)
• [48:31] 23 Mind Against & Dyzen - Freedom (Club Mix)
• [50:12] 24 Gheist - Only
• [52:24] 25 ARTBAT & Shall Ocin, feat. Braev - Origin
• [56:57] 26 CamelPhat & Mathame - Believe

• Introduction https://www.youtube.com/watch?v=mJv-QBdxSaU
• Interrogation
  • https://www.youtube.com/watch?v=q5osSNZ1jyk
  • https://www.youtube.com/watch?v=DSDLNjwIjbM
• LATE ADDITION: Tony Dalton and Vince Gilligan on BCS Insider: https://www.listennotes.com/podcasts/better-call-saul/608-better-call-saul-insider-GKShJeCHRkE/ 

Watch the Better Call Saul Season 1 Recap: https://www.youtube.com/watch?v=3Jr33FcB9lA
Watch "A Sick Joke" - Chuck's scene in Chicanery: https://www.youtube.com/watch?v=rreFXFnlKO4

Show notes and referenced links:

• Tweet out the Twitter space: https://twitter.com/Coding_Career/status/1554567966125088769
• Finance for Devs Youtube Workshop: https://www.youtube.com/watch?v=Lelq40jILA4
• Accounting for Devs https://news.ycombinator.com/item?id=23947818
• Google Doc: https://docs.google.com/document/d/1imIgNckZ_kM564fpGgTBtsqiGwRAIOcmA_hzuwRH4bo/edit?usp=sharing

  Join the Coding Career Community: https://learninpublic.org/

  Follow for future spaces: https://twitter.com/Coding_Career

Discuss this episode: https://twitter.com/swyx/status/1557220705237962755

We want to hear from you! The Swyx Mixtape Listener Survey

• Fill out our 2022 Survey! https://forms.gle/g2s1Np9wS5qmrKSRA!
• Survey context: https://mixtape.swyx.io/episodes/swyx-mixtape-survey-refactor-and-deadpool-swyx
• Results will be summed up in a future episode

Her videos:

• Low Budget Filmmaking (87m views)
• Girl Learns to Dance in a Year (12m views)

Discuss this episode: https://twitter.com/swyx/status/1556793526800842752

We want to hear from you! The Swyx Mixtape Listener Survey

• Fill out our 2022 Survey! https://forms.gle/g2s1Np9wS5qmrKSRA!
• Survey context: https://mixtape.swyx.io/episodes/swyx-mixtape-survey-refactor-and-deadpool-swyx
• Results will be summed up in a future episode

Old talk version: https://www.youtube.com/watch?v=IzK4IxHv3W0

Join the Coding Career Community: https://learninpublic.org/

Follow for future spaces: https://twitter.com/Coding_Career

Transcript

[00:00:00] Chad Stewart: I think we should set up the whole thing first in case, people might be coming off the street and they don't necessarily know exactly about the chapter of the book. I definitely think you should talk a little bit about that first. 

[00:00:10] swyx: I do opinion introduce it. Yeah. Yeah.

[00:00:13] That'd be great. Do you wanna give it a shot? I wanna see what what your take on it is. Oh, okay. Yeah, sure. I'll give it a shot. So, 

[00:00:20] Chad Stewart: So pretty much the idea. Well, so first of all the, currently the chapter actually is at the end of the book. And a lot of you get a lot of, the, you get a lot of other information before you get to this chapter.

[00:00:32] And the kind of idea is that, all that other information is important. It's great. But if you don't necessarily know how to implement. Then, yeah, it's not particularly useful. And so my understanding, you of took the idea of hairs, things that that you could use to start implementing some of these things.

[00:00:53] And then one of the things that actually really enjoyed really liked I read over the chapter again, just to to refresh myself, was the idea of not everything to use all the time. You have tactics which you use whenever they come up, then you have strategy. Which you use, like you use a little bit more often.

[00:01:13] I don't remember what the third one is, but it is like levels of when you use them principles. Yes. Principles. Thank you. When you use them often. So the chapter resonated with me mostly because of a lot of the things that you were talking about is like habits and like laying the foundation for success.

[00:01:30] Part we talked about it in the Mito last week in terms of keeping yourself physically healthy, but just also, it's just generally your habits, both your physical habits, like learning, expanding your knowledge, networking, interacting with people it's just having that foundation laid out so that, leveraging the other topics of the book was is what you call.

[00:01:53] It was easier. I know we had that, this kind of discussion about about maybe putting it earlier in the book, but that's the reason why I decided, Hey, maybe this would be the first thing to talk about because this is something that, we talk up in the industry, but not really, yeah. So just wanted to talk about 

[00:02:11] swyx: anyways. Yeah. That's a great recap. Yeah, that's fantastic recap. Okay. Job done. Thank you everyone. Yeah. Wow. And you didn't even I didn't even tell you I was gonna ask you anyway. I just love hearing about it from other point of view.

[00:02:23] But yeah, you can see how it's weird to put it at the front of the buzz. I have to go through and set up all the context first, which is like 39 chapters of random shit. And then but, and then I come in at the end with a really strong chapter. Right. But I think my reflection is like, Imagine you would hand it the golden book of advice.

[00:02:42] Like maybe my book is like not the golden book of advice, but maybe someone else's book in book of advice. Can you convert that advice into results and the chances are, is it's no, because it's not really, you're not really lacking for advice. You're really lacking for systems to implement that effectively in your career, in your life.

[00:03:03] Right? To actually put things in action and follow through on them. It's not ideas, it's execution, it's not motivation, it's discipline. And so like it's really boring blocking and tackling stuff. But then I felt like if I did not talk then everything I, everything else I talk about is a complete waste because like this that's the real sustainable advantage.

[00:03:24] I think for sure, I was very influenced by atomic habits. Like you can have all the fancy trading strategies that you want, but ultimately, your net worth is a trailing indicator of your financial habits. Did you save enough? and, did you did you did you put did you pay down the interest rate on the things that you're supposed to pay down first before chasing the investment in other categories?

[00:03:48] And I definitely feel like, when people give high level career advice, they tend to overstep in terms of the high stakes, the very dramatic, the very flashy, the very sexy, or very smart sounding ideas. And there's just the boring, like eat of vegetables, versions of the ideas. Isn't talked about enough when actually it is the predominant.

[00:04:08] Thing to get right. So, yeah. Oh, go ahead. Go ahead. Sorry. I cut you off. Oh, no, I see you also join on your personal, so, I'm talking to two CHADS. Oh 

[00:04:15] Chad Stewart: yeah. One that's a duck and one that's an actual person. Yeah. No, so I would, I, so I do agree with you. But, and I guess it's I try not to say too much about the, on, on like you're delivering the chapter as opposed to the chapter's contents itself.

[00:04:30] But like I do agree that, like the thing that everybody's interested in, like you said, the gold as you put it is definitely. The, what you call it the flashy advice, the, this is how you negotiate your salary. These are the technologies that you choose, as opposed to the eat, your vegetables as you call it version is, get up every day and code, get up every day and read tech, tech news, or get up every day and network, specifically the phrase network, where network is just this bland, instruction that you're, that 

[00:05:02] swyx: everybody gives, know, which network what you supposed to do when people say I'm gonna get up to date end network.

[00:05:06] What is that? I 

[00:05:08] Chad Stewart: have no clue. I just, I say it all the time. And then I sit down and okay, what am I supposed to do? Ha 

[00:05:15] swyx: oh, but so my version of that right. Is to learn in public. Right? And I know, this, so, like it's weird to come to, to reach out, to let's, here's an unenlightened version of networking, which is.

[00:05:26] You're just, you're gonna go out there and you're gonna look for some industry mentor and you're gonna cold email them and say, please, can you be my mentor? Which is an unspecified job of indeterminate length for no money. So good luck. But if you learn the public you're putting your interests out there, you're you progress out there and people can help you with specific dimensions and you can build your network that way by building up assets of value that you exchange for something else.

[00:05:50] And I think that's a really positive some way to network and I highly encourage people 

[00:05:54] Chad Stewart: to do that. Yeah, no, I definitely agree. I definitely agree. And I guess like that's like the going back to the operating system of you is like the more kind of boring part, because that is something that you have to do all the time, it's the grind, right?

[00:06:11] Like everybody is trying to tell you to grind, but they don't necessarily tell you. You know why it's important and they don't tell you that it gets boring. Well, I gue...

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Show Notes

• CMU Database lecture from Robert Hodges at Altinity