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• A customer was affected by an Amazon bug that froze his bank account, causing him to be evicted from his apartment. |
• Amazon's response to the customer's problem was to send a team to help resolve the issue, even going so far as to get him back into his apartment. |
• The company's approach to customer service was to be overly apologetic and conciliatory, even to the point of being seen as insincere or manipulative. |
• The conversation turns to leadership and the idea that certain successful leaders, such as Jeff Bezos and Bill Gates, may have developed sociopathic tendencies in order to be effective at their level. |
• The speakers discuss the challenges of being a leader and the need to balance being effective with being a "nice" person. |
• They also discuss the idea that there may not be a clear example of a successful leader who is also a "nice" person, and that leadership often requires making tough decisions and taking risks. |
• Sociopathic behavior in leadership |
• Importance of diversity and representation in companies |
• Google's innovation challenges and reliance on search ad revenue |
• Amazon's history of innovation due to competitive pressure |
• Threats to Google's monopoly on the ads ecosystem, including EU regulation and the rise of LLMs |
• The future of advertising and the need for targeted, effective ads |
• The dominance of Google in ads is being challenged by Amazon and TikTok's new shop feature. |
• Google is being disrupted by its own inventions, specifically Large Language Models (LLMs). |
• The company has pivoted to AI, but is struggling to implement it effectively. |
• Open source is not necessarily a solution, as the quality of a model depends on the data used to train it. |
• Google will likely remain relevant in the next five years, but may be surpassed by others in the long term. |
• The company's history of innovation and open sourcing, particularly with TensorFlow, is being revisited in light of current challenges. |
• Microsoft and other large companies are struggling to innovate and be bold due to their need for curation and polish. |
• Bezos' persistence and Amazon's relatively small number of failed projects |
• Amazon's Fire Phone as a notable failure |
• Alexa and Echo's monetization struggles |
• Potential replacement of Alexa with more advanced AI |
• Apple's lack of innovation in Siri |
• Google's cultural significance and potential shift in language usage |
• Google's future direction and potential changes to search experience |
• Comparison of ChatGPT and Google's search capabilities |
• Google's reliance on AI and search infrastructure |
• Importance of relevance and quality in ads |
• Balance between relevance and user privacy |
• Opt-in relevance as a potential solution |
• Steve Yegge's experience leaving and returning to work after retirement |
• Discussion of purpose and fulfillment in work vs. other activities |
• Steve Yegge discusses his decision to retire at 52, but returned to work after 10 months due to feeling like a "video game drooling zombie" |
• He was inspired by Anthony Bourdain's concept of needing a purpose and challenge to avoid stagnation |
• Steve mentions a conversation with his friend Mark Porter, who predicted he would retire for only two years |
• The group discusses the importance of having a purpose and challenge in life, using the analogy of a car needing friction to function |
• Steve talks about being wooed back to the game by Sourcegraph, where he is now working as a leader |
• He shares his experience of interviewing with 21 companies, looking for a role that would be fulfilling and not feel like work |
• Steve discusses the alignment of his goals and interests with Sourcegraph, and how he was able to make a meaningful contribution to the company, particularly in the area of code intelligence and AI |
• The founders of Sourcegraph, Quinn and Beyang, are relatable and down-to-earth, making them a good fit for the project. |
• Cody, a coding assistant, has just been launched and is still in its early days, with room for improvement. |
• The goal is to make Cody a valuable tool for developers, freeing them up to focus on coding and eliminating mundane tasks. |
• The team is working to improve Cody's quality, using a combination of AI and code graph technology. |
• The conversation turns to the inevitability of AI's impact on the future of coding, with a focus on the LLM (large language model) invasion. |
• The guests discuss the challenge of getting people to believe in and accept AI's potential, framing it as a sci-fi concept that's now becoming reality. |
• Current state of Sourcegraph and its ecosystem |
• Disparities in developer experience depending on language and ecosystem |
• Low-hanging fruit and potential for innovation |
• Magical innovation loops and the challenges of sustaining them |
• Amazon stories and experiences, including Jeff Bezos' reaction to a joke |
• The potential for a podcast on post-mortems and lessons learned from mistakes |
• Discussion of cultural differences in tech between Western and Asian companies, with Steve Yegge mentioning Amazon's value of not being vocally self-critical. |
• Explanation of Sourcegraph's knowledge graph and how it provides a defensible moat in the market. |
• Analysis of why big companies like Google are stuck in their approach and cannot be as aggressive as smaller companies like Sourcegraph. |
• Discussion of the "Innovator's Dilemma" and how it affects large companies. |
• Steve Yegge's prediction that Sourcegraph will remain a leader in the market due to its ability to iterate quickly and its existing code graph. |
• A hypothetical scenario in which Steve Yegge is asked to write a prescription for all developers to ensure they are prepared for the future of coding. |
• The importance of learning AI for software developers to stay ahead in their careers |
• Steve Yegge's prescription: "Learn AI" and the need to familiarize oneself with foundational concepts |
• The ease of accessing resources for learning AI, including YouTube tutorials and visualizations |
• The process of applying AI to products, including establishing benchmarks and iterating through experiments |
• The use of tools like Hugging Face and leaderboards to evaluate and improve AI models |
• The need for continuous learning and experimentation in AI development |
• The potential for AI to become integrated into everyday engineering tasks and workflows |
• The importance of sharing stories and experiences in learning and innovation |
• The need for companies to be more open and transparent |
• The value of pushing back against established norms and seeking change |
• The host's enthusiasm for Sourcegraph and their sponsorship of the show |
**Adam Stacoviak:** So we're joined by Steve Yegge. Steve, you've had such a career... You're a ranter, a blogger, you upset people, you move along when it gets conservative and not innovative... Where is the best place to begin for you? Should we just go back as far as we can? What's the fun part for you? |
**Steve Yegge:** Sure, sure, we could start anywhere. Go back to Amazon, or my early days in the '90s at GeoWorks, in the assembly language, or wherever you like. |
**Adam Stacoviak:** Where do you think -- I'm sure that your entire history informs today for you, but where do you think things began for you in learning as far back in your history that sort of informs most of what's happening today? |
**Steve Yegge:** Well, so I've gone through a couple of phases in my career where the learning was accelerated for one reason or another... You know, sometimes you go and you're just getting stuff done, but you're not really learning anything. You're just executing. And then you go through these periods where you're ju... |
**Jerod Santo:** \[06:13\] "I'm learning!" \[laughter\] |
**Steve Yegge:** Right?! I mean, seriously, you can feel it when you're learning. And one of the early -- I mean, it's embarrassing to call it an early one, but it was almost 30 years ago... I was writing a computer game, and I was trying to make it massively multiplayer, I had a big vision for it... And I was trying t... |
**Adam Stacoviak:** Uncle Jeff... How was Dread Pirate Bezos? |
**Steve Yegge:** Dread Pirate Bezos, yeah... He was -- he is... |
**Adam Stacoviak:** \[laughs\] That's hilarious.. |
**Steve Yegge:** It kind of defies description. You know how they say Jobs had a reality distortion field? I never liked Steve Jobs, but everybody said that he'd just come into the room and bend reality, right? And Bezos would do that, too. He would just sort of bend everything to his vision. And his vision was just in... |
**Jerod Santo:** So did he have the vision for AWS? It seems like he did. The services. And it seems like he kind of dictated "Everything's gonna be a service", and this turned into AWS. Is that how it worked, or am I reading it wrong? |
**Steve Yegge:** So I had an insider telling me after I wrote my platform rant - because it got a lot of attention at Amazon. And there was a lot of truth to what I said. Certainly, Jeff -- we did have extra compute power, and off-cycles, and there were other reasons to do it... But the insider told me that one of the ... |
**Jerod Santo:** Okay... |
**Steve Yegge:** And so he designed Amazon to be choppable into pieces. And the way you do that is you make everybody basically an autonomous business unit; every team is completely sort of self-contained, and they have their own API boundaries, and they're almost -- they're basically replaceable. And that led to AWS, ... |
**Jerod Santo:** Yeah. One thing that you wrote recently for Sourcegraph on the "Cheating is all you need", is you wrote "Did I ever tell you about the time AWS was just a demo on some engineer's laptop?" No, you haven't told me about that time. I mean, you tell it in a paragraph there, but do you want to tell that sto... |
**Steve Yegge:** We thought it was weird. \[laughter\] |
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