ConTejas Code

Tejas Kumar
  • 5.0(7개의 평가)
  • 과학 기술
  • 매주 업데이트
ConTejas Code

ConTejas Code is a podcast in the web engineering space that has deep dives on various topics between frontend engineering with React, TypeScript, Next.js, and backend engineering with Kafka, Postgres, and more. The series is a mix of long-form content and guest episodes with industry leaders in the web engineering space. From the podcast, listeners will take away actionable best practices that you can integrate into your workflows as well as valuable insights from prominent people in the industry. Hosted on Acast. See acast.com/privacy for more information.

  1. 1일 전

    TC39: How signals work, adding signals to the JavaScript programming language

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - TC39 Signals Proposal: https://github.com/tc39/proposal-signals Summary In this conversation, Kristen Maevyn, and Daniel Ehrenberg discuss reactivity and its importance in JavaScript. They explore the concept of reactivity, its role in keeping applications deterministic, and the challenges of achieving consistency in modern rendering frameworks. They also compare signals to observables and explain why signals are being considered as a language-level feature. The conversation touches on the API for signals, the use of classes in JavaScript, and the benefits of functional programming. Signals are an evolution of the long-standing problem of managing state in JavaScript applications. They provide a solution to the issues with classes and functions by combining the benefits of both. Signals allow for encapsulation, testing in isolation, and pure functions while still being able to handle state. Chapters 00:00:00 Intro 00:09:57 What are signals? 00:26:37 Classes and the `new` keyword 00:41:31 State Management and Signals 00:49:25 Push-based vs. Pull-based Reactivity 01:04:43 Language-level vs. Framework-level Signals 01:14:27 Server-side Signals 01:25:06 Self-referencing Signals 01:36:29 Audience Q&A 01:47:07 Conclusion Hosted on Acast. See acast.com/privacy for more information.

    1시간 48분
  2. Paul Klein IV: How to Build Browsers for AI Agents

    11월 4일

    Paul Klein IV: How to Build Browsers for AI Agents

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - React Africa (partner): https://react-africa.com/ - Browserbase: https://browserbase.com/ - Browserbase Series A Announcement: https://www.kleinerperkins.com/perspectives/browserbase-AI-seriesa/ - Paul on X: https://x.com/pk_iv Summary In this conversation, we talk to Paul Klein IV, the founder of BrowserBase. We discuss the concept of browser-based software and its potential to automate tasks on the web. Paul explains that the future of software is one where it does the work for us, and Browserbase is designed to power this future by providing a programmable web browser for AI applications.  We also touch on the challenges of running browser automation frameworks in production and how Browserbase solves these challenges. Paul introduces Stagehand, an open-source SDK that helps developers automate web workflows, and emphasizes the importance of ethical use of browser automation tools. Customers are building various applications on Browserbase, including web scraping, testing, AI agents, B2B software, and professional services.  The company has experienced rapid growth, with thousands of hours of browser sessions per week. To handle the scale, Browserbase had to make architectural changes, such as moving from Postgres to ClickHouse for better performance. They also had to address challenges like connection management, resource allocation, and debugging customer issues. The founder believes they have achieved product-market fit based on strong customer retention and repeatable growth strategies.  Browserbase is a technical product, so the number one priority for hiring is that candidates are technical and understand what Browserbase does. The team is currently focused on growing the top of the funnel and the sales edge side. They have specific roles for growth engineers and customer-focused engineers. The company recently raised a Series A round of $27M, with the goal of becoming a category-defining infrastructure company. The pricing model for Browserbase includes a hobby plan, a startup plan, and a scale plan. The company offers 10 free sessions for users to try out the product. Chapters 00:00:00 Paul Klein IV 00:04:41 Why Browserbase? 00:11:57 What is Browserbase? 00:19:09 Stagehand: the open source SDK 00:35:30 How People are Using Browserbase 00:49:17 Creating web APIs where there are none 00:59:40 Product-Market Fit 01:06:16 AI Engineering at Browserbase 01:08:42 Remote Work vs. Onsite 01:13:36 Browserbase's Series A Round 01:20:02 AI Fatigue 01:28:11 Advice for Founders 01:32:10 Conclusion Hosted on Acast. See acast.com/privacy for more information.

    1시간 33분
  3. Kelly Vaughn: How to Navigate Career Transitions and Build Meaningful Relationships

    10월 28일

    Kelly Vaughn: How to Navigate Career Transitions and Build Meaningful Relationships

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - React Brussels: https://react.brussels - React Africa: https://react-africa.com - Kelly on X: https://x.com/kvlly - Spot AI: https://spot.ai - Tejas on X: https://x.com/tejaskumar Summary Kelly Vaughn, Director of Engineering at Spot AI, shares her unique career journey from self-taught coder to entrepreneur and now corporate leader. She discusses running a Shopify agency, co-founding a venture-backed startup, and transitioning to her current role. Key points include: - The challenges of running an agency and managing employee livelihoods - Insights on bootstrapping vs. venture funding for startups - The importance of genuine relationships and networking in career growth - Adapting to different company stages and cultures - Navigating the transition from entrepreneur to corporate employee - The value of diverse backgrounds in tech leadership roles Kelly emphasizes the importance of self-reflection, embracing change, and learning from failures throughout one's career journey. Chapters 00:00:00 Intro 00:05:08 Spot AI: Video Intelligence 00:12:46 Dealing with Rapid Growth 00:17:05 Getting into Tech 00:22:25 TapRoom Consultancy/Shopify 00:32:35 Running a Consultancy 00:39:09 Venture Capital or no? 00:40:08 Shutting Down Consultancy 00:41:11 Attention, Effort, Mistakes as a Path to Growth 00:47:26 The Pressure of Running a Business 00:52:05 How to find a job: networking 01:01:02 Being taken advantage of 01:04:59 How Kelly got her audience 01:08:31 Big audience problems 01:12:01 Therapist and Engineering Leadership 01:18:18 Boundaries 01:26:06 Advice for Founders Hosted on Acast. See acast.com/privacy for more information.

    1시간 38분
  4. Aya Bochman, co-founder Fashn.ai: How to build a lean AI startup (that makes money)

    10월 21일

    Aya Bochman, co-founder Fashn.ai: How to build a lean AI startup (that makes money)

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - Upvote Fashn on ProductHunt: https://www.producthunt.com/posts/fashn-virtual-try-on - Fashn: https://fashn.ai - Aya on 𝕏: https://x.com/ayaboch - React Africa (partner): https://react-africa.com Summary Aya Bochman, co-founder of Fashion AI, discusses her journey in creating a generative AI platform for virtual try-on in the fashion industry. She shares insights on building a self-funded startup, the challenges of developing AI models, and the importance of work-life balance for founders. Chapters 00:00:00 Introduction to Fashion AI 00:07:42 Demo and product description 00:11:10 Technical challenges in virtual try-on 00:17:48 Data collection and labeling process 00:26:51 API development and pricing model 00:34:45 Collaboration with other services (RunPod, Fal.ai) 00:43:02 Dealing with content moderation 00:46:46 Business model and pricing structure 00:52:12 Incident with Meta and open-source code 00:59:10 Future plans and potential competition 01:03:13 Advice for technical founders 01:20:12 Work-life balance and avoiding burnout 01:29:51 Working with a spouse as a co-founder Hosted on Acast. See acast.com/privacy for more information.

    1시간 33분
  5. Peer Richelsen, founder Cal.com: How to build an open startup

    10월 14일

    Peer Richelsen, founder Cal.com: How to build an open startup

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - React Brussels: https://react.brussels - React Africa: https://react-africa.com  - Cal.com: https://cal.com - Peer on X: https://x.com/peer_rich - Tejas on X: https://x.com/tejaskumar_ Summary In this discussion, Peer Richelsen, co-founder of Cal.com, shared insights into the company's open-source scheduling infrastructure. Cal.com offers customizable scheduling solutions for individuals and enterprises across various industries, with its open-source approach driving rapid development and community engagement. Richelsen highlighted key features like "instant meetings" for customer support and discussed the platform's technical architecture, primarily based on Next.js with plans to partially migrate to Nest.js. The conversation also touched on Cal.com's cautious approach to AI integration, its structure as a U.S. entity despite European roots, and commitment to transparency in operations. Richelsen expressed satisfaction with Cal.com's current trajectory, outlining plans to enhance offerings in healthcare scheduling, improve sales team routing, and expand capabilities across different sectors. Throughout the discussion, Richelsen's passion for open-source development and innovative scheduling solutions was evident. Chapters 00:00:00 Intro 00:03:52 Supabase hate 00:04:41 What is Cal.com? 00:09:12 Balancing Open Source Maintenance and New Features 00:14:34 Prioritizing Customer Feedback 00:18:33 Cal.com's Product-Market fit 00:22:12 Cal.com's Transparency (Open Startup) 00:25:02 Cal.com's Hiring Process 00:29:10 Location based pay nuance 00:35:55 Cal.com stats: active users and recurring revenue 00:42:51 Cal.com technical deep dive 00:54:06 Cal.com API Platform 00:58:01 Cal.com Atoms 01:06:15 Cal.ai AI-enabled scheduling agent 01:18:16 What founders should know about running a startup 01:27:24 Future experimental Cal.com features 01:30:36 Germany's Startup Reputation (bad) 01:33:57 Positioning and Marketing for Cal.com Hosted on Acast. See acast.com/privacy for more information.

    1시간 35분
  6. Harper Carroll: How Machine Learning Works, What AI Engineering is, the Future of AI

    10월 7일

    Harper Carroll: How Machine Learning Works, What AI Engineering is, the Future of AI

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - React Africa (partner): https://react-africa.com/ - Harper Carroll: https://harpercarrollai.com/ - 10 Days of AI Basics Course: https://www.youtube.com/watch?v=Ie7qxG9os1U&list=PL-ocKywdn6lE9l4LIPL4gMY4nNRfjEswG&pp=iAQB - Harper on X: https://x.com/harperscarroll - Isabelle Boemeke on X: https://x.com/isabelleboemeke - Tejas on X: https://x.com/tejaskumar_ Summary In this enlightening conversation with Harper Carroll, we dove deep into the world of AI, covering everything from the basics of neural networks to the cutting-edge concepts of AI agents. Harper's expertise, stemming from her 10 years of Stanford education, provided invaluable insights into the inner workings of machine learning models. We explored the environmental impact of AI and the potential role of nuclear energy in sustaining AI development. Harper's balanced view on AI's future was refreshing, emphasizing its potential for optimization rather than doom-and-gloom scenarios. The discussion concluded with thought-provoking reflections on AI's potential to free humanity for more creative pursuits and its possible connection to fundamental universal principles of peace and love. Chapters 00:00:00 Intro 00:06:09 What is AI? 00:11:34 Machine Learning Deep Dive 00:17:08 Impostor Syndrome 00:22:11 Machine Learning Deep Dive Continued 00:28:04 What are Hidden Layers? 00:34:29 Model Architectures 00:37:04 How do embeddings models work? 00:40:23 AI Engineering Deep Dive 00:48:06 Smaller specialized models vs. LLMs (Large Language Models) 00:49:57 Hallucinations and RAG 00:52:16 Fine-tuning a model and blends 00:55:24 RAG vs. Fine-tuning 01:00:31 RAG Explained 01:04:15 Machine Learning Evals 01:10:28 Backpropagation 01:12:44 AI Agents 01:16:25 Agentic RAG 01:17:51 AI and Energy: The rise of nuclear power 01:25:06 AI Optimism vs. Doomerism 01:31:27 AGI and Superintelligence 01:36:22 Hope for the future with AI 01:41:03 Conclusion Hosted on Acast. See acast.com/privacy for more information.

    1시간 43분
  7. ChatGPT: How to Train an LLM, Ethics, and the future of AI

    9월 30일

    ChatGPT: How to Train an LLM, Ethics, and the future of AI

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - SquiggleConf: https://squiggleconf.com/ - ChatGPT: https://chatgpt.com Summary In this groundbreaking episode of the ConTejas Code Podcast, we engage in a deep conversation with ChatGPT, exploring the intricacies of AI, its ethical implications, and the future of human-computer interaction. The discussion covers the training process of AI models, the importance of ethical data sourcing, and the challenges of transparency in AI development. The episode also dives into philosophical dilemmas like the trolley problem, the potential for AI to replace human jobs, and the unique qualities that make us human. Throughout the conversation, the complexities of latent space and voice modeling are examined, culminating in a reflection on the irreplaceable aspects of human experience. Chapters 00:00:00 Intro 00:07:39 How to Build an LLM 00:10:04 Copyrights and Ethics 00:17:13 Is OpenAI Actually Open? 00:37:10 An Open AI Supervision Committee 00:45:21 Training an LLM 00:51:11 Optimizing Hyperparameters for Machine Learning 00:59:44 What did Ilya see? 01:00:14 Superintelligence Threats to Humanity 01:07:25 The Trolley Problem 01:13:24 AI on Trump vs. Kamala 01:19:47 What Questions Would ChatGPT Like to Answer? 01:22:04 The Future of AI: Dystopian or Hopeful? 01:28:15 Latent Space Explained 01:41:28 AI Consciousness 01:46:03 Conclusion Hosted on Acast. See acast.com/privacy for more information.

    1시간 49분
  8. Tracy Lee, CEO This Dot: How to be successful in DevRel with AI

    9월 23일

    Tracy Lee, CEO This Dot: How to be successful in DevRel with AI

    Links - Codecrafters (sponsor): https://tej.as/codecrafters - Wix (sponsor): https://tej.as/wix - SquiggleConf: https://squiggleconf.com/ - Tracy Lee on X: https://twitter.com/ladyleet - This Dot Labs: https://www.thisdot.co/ - RxJS: https://rxjs.dev/ - GitHub Copilot: https://github.com/features/copilot - CascadiaJS Conference: https://2023.cascadiajs.com/ - Render: https://render.com/ - Vercel: https://vercel.com/ - Netlify: https://www.netlify.com/ - AWS Amplify: https://aws.amazon.com/amplify/ - Michael Terrell Coaching: https://www.michaelwterrell.com/ - Cal Newport's "Deep Work": https://www.calnewport.com/books/deep-work/ - O'Reilly Media: https://www.oreilly.com/ Summary In this episode, Tracy Lee, CEO and co-founder of [This Dot Labs](https://www.thisdot.co/) shares her inspiring journey from hosting JavaScript meetups to becoming a prominent figure in the tech industry. She explores the evolution of This Dot Labs, highlighting the crucial role of open source contributions and community building in its success. Tracy emphasizes the significance of Developer Relations (DevRel) in fostering long-term relationships and brand awareness. The discussion touches on current industry trends, including the increasing integration of AI technologies like GitHub Copilot in development workflows, and how This Dot Labs navigates client policies regarding AI usage. We also explore the challenges of scaling a consultancy, the importance of hiring autonomous and entrepreneurial-minded individuals, and strategies for effective team building. Tracy sheds light on the need for leaders to be coachable and receptive to feedback, sharing personal anecdotes about growth and learning. The conversation wraps up with insights into This Dot Labs' future directions, including expanding services in AI consulting and backend technologies. Chapters 00:00:00 Introduction 00:06:25 Building This Dot Labs 00:10:40 The Role of Open Source 00:14:15 Importance of DevRel 00:22:45 Challenges in Consultancy 00:27:00 AI Integration in Client Projects 00:31:35 Hiring Autonomous Individuals 00:36:20 DevRel's Value in the Current Economy 00:40:55 Emotional Intelligence and Leadership 00:45:15 Balancing Business and Personal Connections 00:50:30 Expanding Services at This Dot Labs 00:55:45 Future Directions and Vision 01:00:00 Impact of AI on the Industry 01:15:00 The Importance of Being Coachable 01:20:30 Overcoming Personal Challenges 01:25:40 Advice for Aspiring Tech CEOs and Founders 01:35:15 Looking Ahead: This Dot's Next Steps 01:40:00 Final Reflections and Closing Thoughts Hosted on Acast. See acast.com/privacy for more information.

    1시간 50분
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예고편

5
최고 5점
7개의 평가

소개

ConTejas Code is a podcast in the web engineering space that has deep dives on various topics between frontend engineering with React, TypeScript, Next.js, and backend engineering with Kafka, Postgres, and more. The series is a mix of long-form content and guest episodes with industry leaders in the web engineering space. From the podcast, listeners will take away actionable best practices that you can integrate into your workflows as well as valuable insights from prominent people in the industry. Hosted on Acast. See acast.com/privacy for more information.

정보

  • 제작진
    Tejas Kumar
  • 방송 연도
    2024년
  • 에피소드
    56
  • 등급
    무삭제판
  • 저작권
    © Tejas Kumar
  • 웹사이트 보기
    ConTejas Code

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