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[6170.58 --> 6172.48] I mean, I don't think we will, but I don't know.
[6173.20 --> 6173.94] I don't know.
[6174.32 --> 6174.56] Okay.
[6174.68 --> 6175.56] So it's free for now.
[6175.78 --> 6176.10] Let's say.
[6176.34 --> 6177.20] No, just say it's free.
[6177.30 --> 6179.06] You don't have to like, you don't have to put times on it.
[6179.44 --> 6180.80] It has been free.
[6181.50 --> 6181.86] Forever.
[6182.12 --> 6184.08] Since the beginning of it until this moment.
[6184.26 --> 6186.58] So it's a good chance that it will remain free, let's say.
[6186.64 --> 6187.02] Oh yeah.
[6187.14 --> 6187.54] I mean, it's like.
[6187.56 --> 6189.74] Based upon past trend, future trend suggests.
[6189.82 --> 6194.14] It's like a 99% chance, but we just don't want to like go out making promises to people,
[6194.24 --> 6194.48] you know?
[6194.80 --> 6195.32] I know.
[6195.56 --> 6196.16] Well, you know.
[6196.18 --> 6196.92] Unless we keep them.
[6196.92 --> 6197.36] Okay.
[6197.50 --> 6200.44] Well, for now, everybody come in Slack.
[6200.60 --> 6201.86] It is free for now.
[6202.30 --> 6202.70] I'm just kidding.
[6203.04 --> 6203.86] That sounds like, yeah.
[6204.18 --> 6206.44] You better get in here quick before we change our mind.
[6207.56 --> 6210.42] No, just again, I love to see people in there.
[6210.56 --> 6211.96] I love to see people connecting.
[6212.12 --> 6215.40] I think it's a place that, that is safe to hang out in.
[6215.50 --> 6216.78] There's nobody arguing in there.
[6216.86 --> 6220.98] There's obviously opposing sides sometimes to different conversations, but it's never been
[6220.98 --> 6224.16] anything we've had to personally moderate by any means whatsoever.
[6224.16 --> 6228.28] So if you're looking for a place to just hang out with people like you, that's a good spot.
[6228.64 --> 6230.78] So if you want that, do that.
[6231.20 --> 6232.06] It's free for now.
[6232.48 --> 6232.96] There you go.
[6233.44 --> 6235.76] Otherwise, plus plus is better.
[6236.26 --> 6238.52] And we'll talk to you again in 2024.
[6239.30 --> 6239.86] Bye y'all.
[6242.66 --> 6243.62] All right.
[6243.98 --> 6245.22] That is it.
[6245.64 --> 6247.92] 2023 is in the bag.
[6248.18 --> 6248.98] Can you believe it?
[6248.98 --> 6255.14] If you have ideas, requests, or anything at all you'd like to say, leave us a comment.
[6255.64 --> 6256.80] We love hearing from you.
[6257.14 --> 6261.10] There's a link in your show notes to the discussion thread for this episode.
[6262.04 --> 6266.18] Thanks again to each and every one of you who left us a voicemail.
[6266.60 --> 6267.22] So cool.
[6267.38 --> 6267.78] So cool.
[6267.84 --> 6270.22] I hope you enjoy your BMC remix.
[6270.64 --> 6272.72] The podcast wouldn't be the same without you.
[6272.72 --> 6278.24] And thanks one last time to you, our listener, for listening to our shows this year.
[6278.56 --> 6282.62] We literally wouldn't be able to keep putting out new stuff if y'all weren't listening.
[6282.84 --> 6283.38] So thank you.
[6283.92 --> 6288.94] And a huge thanks to everyone on our team and in the Changelog community for everything you do.
[6289.14 --> 6290.06] You know who you are.
[6290.38 --> 6291.96] But still, I'll name a few names.
[6292.26 --> 6293.24] BMC, of course.
[6293.46 --> 6296.16] Our editors, Jason and Brian, of course.
[6296.54 --> 6298.46] Alexandru on transcripts.
[6298.66 --> 6299.60] Gerard, of course.
[6299.60 --> 6305.68] Our friends and panelists on JS Party, GoTime, Practical AI, all our pods.
[6305.98 --> 6306.66] Y'all are awesome.
[6307.00 --> 6310.72] To our longtime partners, Fastly, Fly, and TypeSense.
[6311.08 --> 6312.94] There are many more people we could thank.
[6313.02 --> 6316.26] But hey, we're already an hour and 45 minutes in.
[6316.46 --> 6317.28] So I'll let you go.
[6317.72 --> 6318.84] That's all for now.
[6319.00 --> 6322.24] But let's get back together and talk a lot more next year.
[6329.60 --> 6359.58] We'll be right back.
[6359.60 --> 6389.58] We'll be right back.
• Steve Yegge's early career and learning experiences
• Writing a computer game and learning about dev tools and languages
• Working at Amazon and learning from Jeff Bezos
• The development of AWS and its design as a service
• The early days of AWS and its initial demo on an engineer's laptop
• The transition from SOAP to REST and the design of AWS's text protocol
• Steve Yegge's opinions on innovation and trying new approaches
• Jeff Bezos's leadership style and vision for Amazon and AWS
• The importance of text over binary formats
• Performance vs. flexibility and debugability
• Two schools of thought at Amazon: one prioritizing performance, the other flexibility
• The legacy of AWS and its adoption within Amazon
• Reactions to large language models (LLMs) and their potential impact
• Comparison to past shifts in technology, such as Kubernetes and SOAP/REST
• Personal anecdotes about working at Amazon and meeting with Jeff Bezos
• Jeff Bezos' reaction to a simple fitness function for reducing customer contacts, which he found to be too simplistic.
• A story about how Steve Yegge's team pitched their project to Bezos, and how Bezos asked a seemingly simple question that threw them off.
• The concept of yin and yang, and how it relates to the two-pizza team's objective function, with the yin being the simple function and the yang being the underlying problem that needs to be addressed.
• A discussion about how Bezos can be intimidating, but also insightful, and how he can freeze even the most seasoned leaders with a simple question.
• A humorous moment where Adam Stacoviak references the TV show Silicon Valley and uses a joke to explain the concept of yin and yang.
• The concept of yin and yang and its application to the Jobs and Wozniak dynamic
• Steve Yegge's experience working with Jeff Bezos, including a story about a presentation he gave to Bezos' lieutenants
• The unique way Bezos likes to receive presentations, including the removal of random paragraphs
• The importance of thinking on one's feet and responding quickly in high-pressure situations, particularly when working with Bezos
• Steve Yegge's analogy for thinking on one's feet, comparing it to putting one's feet in the fire (i.e. being able to adapt and move quickly)
• The concept of "The Closer" at Amazon, where Steve Yegge would convince top talent to join the company despite better offers from other companies
• Steve Yegge's record of successfully convincing 50-70 people to join Amazon, but ultimately losing one person to Facebook
• The importance of storytelling at Amazon, where Jeff Bezos would encourage employees to focus on telling a compelling story rather than just presenting data
• The difference in approach between Amazon and Google, where Amazon would continue to try new ideas even if they failed initially, while Google would quickly kill failed projects
• The value of experiencing the customer's pain firsthand, as exemplified by Bezos' practice of reviewing customer contact data and sending employees on field trips to interact with customers