ConTejas Code

Links - CodeCrafters (partner): https://tej.as/codecrafters - WebAssembly on Kubernetes: https://www.cncf.io/blog/2024/03/12/webassembly-on-kubernetes-from-containers-to-wasm-part-01/ - Shivay on X: https://x.com/howdevelop - Tejas on X: https://x.com/tejaskumar_ Summary In this podcast episode, Shivay Lamba and I discuss the integration of WebAssembly with AI and machine learning, exploring its implications for developers. We dive into the benefits of running machine learning models in the browser, the significance of edge computing, and the performance advantages of WebAssembly over traditional serverless architectures. The conversation also touches on emerging hardware solutions for AI inference and the importance of accessibility in software development. Shivay shares insights on how developers can leverage these technologies to build efficient and privacy-focused applications. Chapters 00:00 Shivay Lamba 03:02 Introduction and Background 06:02 WebAssembly and AI Integration 08:47 Machine Learning on the Edge 11:43 Privacy and Data Security in AI 15:00 Quantization and Model Optimization 17:52 Tools for Running AI Models in the Browser 32:13 Understanding TensorFlow.js and Its Architecture 37:58 Custom Operations and Model Compatibility 41:56 Overcoming Limitations in JavaScript ML Workloads 46:00 Demos and Practical Applications of TensorFlow.js 54:22 Server-Side AI Inference with WebAssembly 01:02:42 Building AI Inference APIs with WebAssembly 01:04:39 WebAssembly and Machine Learning Inference 01:10:56 Summarizing the Benefits of WebAssembly for Developers 01:15:43 Learning Curve for Developers in Machine Learning 01:21:10 Hardware Considerations for WebAssembly and AI 01:27:35 Comparing Inference Speeds of AI Models ---------------------------------------- Hosted on Acast. See acast.com/privacy [https://acast.com/privacy] for more information.

Links - Codecrafters (Partner): https://tej.as/codecrafters - Tejas on X: https://x.com/tejaskumar_ - Mary Thengvall, The Business Value of Developer Relations: https://develocity.io/measuring-devrel-success-effective-metrics-for-impact/#:~:text=In%20a%20talk%20given%20at,5 - Matthew Revell, “What is Developer Relations?”: https://developerrelations.com/guides/what-is-developer-relations/#:~:text=Most%20companies%20invest%20in%20DevRel,because%20they%20want%20to%20affect - Quinton Wall, Does Developer Relations Belong Under Marketing or Engineering?: https://www.linkedin.com/pulse/does-developer-relations-belong-under-marketing-engineering-wall-z9gic#:~:text=For%20early%20stage%20companies%2C%20Developer,the%20detriment%20of%20developer%20experience - Mike Stowe, A Brief History Of Developer Relations Programs: https://influitive.com/blog/brief-history-developer-relations-programs-developer-communities/#:~:text=When%20I%20joined%20Constant%20Contact,across%20one%20of%20these%20companies - R. Scott, Developer Relations: A Growth Engine from Day One: https://www.delltechnologiescapital.com/resources/devrel-day-one#:~:text=%E2%80%8DDeveloper%20Relations%20is%20at%20its,%E2%80%9D - Matt Bernier, The intersection of DevRel and Product Management: https://developerrelations.com/talks/intersection-dev-rel-product-management/#:~:text=The%20Barbican%2C%20London%2C%20UK - Develocity.io, Measuring DevRel Success: Effective Metrics for Impact: https://develocity.io/measuring-devrel-success-effective-metrics-for-impact/#:~:text=impact%20on%20user%20engagement%20and,2 - Jake Prins, 10 Ways to Build a Developer Community: https://www.apideck.com/blog/ten-ways-to-build-a-developer-community#:~:text=in,seminar%2C%20or%20webinar - Francine Hardaway, DevRel: Marketing, Product Management, or Neither?: https://medium.com/influence-marketing-council/devrel-marketing-product-management-or-neither-77d6c4666f7f#:~:text=Most%20developer%20relations%20programs%20wrestle,sourced%20by%20DevRel%20are%20invaluable Chapters 00:00:00 Introduction 00:02:28 The Core Thesis of DevRel 00:12:41 History of DevRel: From Apple in the 80s to Today 00:19:08 The Value of DevRel & Success Stories (Stripe, MongoDB) 00:25:08 The Critical Role of the Feedback Loop 00:27:03 The Danger of Ignoring DevRel Feedback 00:34:33 Where DevRel Sits: Marketing vs. Product & Engineering 00:37:22 The Gold Standard: A Product Engineer with a Megaphone 00:49:37 Measuring DevRel Success: Beyond Vanity Metrics 00:52:00 Key Metrics: Community, Satisfaction, & Monthly Active Developers (MAD) 01:01:31 Practical DevRel: How to Build Community 01:03:37 Practical DevRel: Content Strategy & "Carving the Turkey" 01:06:50 Practical DevRel: Improving the Onboarding Experience 01:11:00 Practical DevRel: Events, Public Speaking & Internal Advocacy 01:17:20 Start of Q&A with Africa's DevRel Community 01:18:02 Defining AI Engineering vs. Machine Learning 01:20:01 Defining DevRel: It's High-Quality Customer Relations 01:26:32 Q&A: Is Developer Experience (DX) the same as User Experience (UX)? 01:29:14 Q&A: How AI is Changing UX/DX with Model Context Protocol (MCP) 01:35:32 Q&A: Biggest Opportunities for DevRel in AI 01:38:25 Q&A: Necessary Skills for AI DevRel (Communication is #1) 01:44:22 Q&A: Where to Find Developers for New Niche Tools 01:48:08 Q&A: What's Most Exciting in Tech Right Now? 01:53:22 Q&A: Advice for New Developers in the AI Era (Build and Ship!) 01:58:00 Q&A: How to Balance Technical Work with Community Management 02:00:57 Q&A: How to Form Meaningful Professional Relationships 02:05:56 Conclusion ---------------------------------------- Hosted on Acast. See acast.com/privacy [https://acast.com/privacy] for more information.

Links - CodeCrafters (partner): https://tej.as/codecrafters - Dev on X: https://x.com/devagrawal09 - Xolvio: https://xolv.io/ - Tejas on X: https://x.com/tejaskumar_ Previous Episodes - Taylor Desseyn - YouTube: https://www.youtube.com/watch?v=6l6GpkHNlZw - Spotify: https://open.spotify.com/episode/1xN7YeNpkCf4qJ3kUkVVuh - Apple: https://podcasts.apple.com/nz/podcast/taylor-desseyn-how-to-build-a-genuine-high-quality-network/id1731855333?i=1000684664112 - Event Sourcing - YouTube: https://www.youtube.com/watch?v=VtmPTigdpos - Spotify: https://open.spotify.com/episode/32dmiUBZclkXNWT1YcUJHr - Apple: https://podcasts.apple.com/us/podcast/event-sourced-architecture-a-deep-dive/id1731855333?i=1000696976876 Summary We discuss the journey of becoming a notable developer, the importance of intentional networking, and the role of content creation in building a professional presence. Dev shares insights from his experiences in DevRel, the challenges of the industry, and the significance of event sourcing in modern applications. We then discuss the intricacies of event sourcing, exploring its implications for software architecture, performance, and testing. The discussion highlights the importance of projections, caching, and the separation of command and query responsibilities (CQRS) in building efficient applications. Real-world applications, such as Git and Redux, are examined as examples of event sourcing in practice. Finally, we explore Solid.js and its comparison with React, focusing on fine-grained reactivity, the challenges of adopting new frameworks, and the evolution of web development practices. They explore the unique features of Solid.js, including its compiler and async signals, while discussing the broader implications for developers transitioning between frameworks. The conversation also touches on the importance of full stack development and the mindset required to excel in the field. Chapters 00:00:00 Dev Agrawal 00:04:16 Becoming Notable in Tech 00:14:24 Intentional Networking and Building a Presence 00:24:27 The Role of Content Creation 00:34:29 DevRel Insights and Career Transitions 00:44:05 Understanding Event Sourcing 00:43:37 Caching and Performance in Event Sourcing 00:48:42 Real-World Applications of Event Sourcing 00:51:31 Command Query Responsibility Segregation (CQRS) Explained 00:54:24 Event Sourcing in UI State Management 00:57:25 Overcoming Resistance to Event Sourcing 01:00:22 The Challenges of Transitioning to Event Sourcing 01:04:34 Storing Events and Schema Management 01:07:16 Testing with Event Sourcing 01:08:51 Introduction to Solid.js and Its Advantages 01:13:12 Understanding Fine-Grained Reactivity 01:15:06 Challenges in Replacing React 01:16:30 The Unique Model of Solid.js 01:18:22 The Catch-22 of Learning React 01:19:52 Comparing Fine-Grained Reactivity in Solid and React 01:23:50 The Role of Solid's Compiler 01:25:57 Exploring Solid.js 2.0 and Async Signals 01:28:55 Server-Side Rendering and Async Signals 01:35:08 Partial Pre-Rendering and Edge Workers 01:37:41 Becoming a Full Stack Developer ---------------------------------------- Hosted on Acast. See acast.com/privacy [https://acast.com/privacy] for more information.

Links - CodeCrafters (partner): https://tej.as/codecrafters - Lu on X: https://x.com/todepond - Lu on Bluesky: https://bsky.app/profile/todepond.com - Lu on YouTube: https://www.youtube.com/@todepond - tldraw: https://tldraw.com/ - Make Real: https://makereal.tldraw.com/ - tldraw computer: https://computer.tldraw.com/ - Tejas on X: https://x.com/tejaskumar_ Summary We talk with Lu Wilson, an engineer at tldraw: a startup focused on innovative whiteboard technology. Together, we discuss the evolution of tldraw, the impact of AI on creative workflows, and the importance of experimentation in tech development. Lu shares insights on their very interesting experiments like Make Real and the new tldraw Computer, emphasizing the need for user-friendly AI tools that empower everyone, not just programmers. The discussion also touches on building a culture of experimentation within teams and the future of AI in design and development. Chapters 00:00 Lu Wilson 04:12 Introduction to TL Draw and Lou Wilson's Work 07:12 Exploring Make Real: AI and Canvas Integration 10:07 The Evolution of TL Draw Computer 12:56 User Experiences and Creative Applications 15:57 Future Directions and Innovations in TL Draw 19:06 AI Workflows: Democratizing Technology for Everyone 35:16 The Evolution of Teal Draw's Features 38:05 Challenges in Implementing Autocomplete 41:23 Building a Future-Proof AI Module 43:01 Understanding LLMs and Canvas Interaction 45:52 Evaluating AI Performance on Canvas 48:25 AI as a Collaborative Partner 53:01 Fostering a Culture of Experimentation 54:11 Balancing Innovation and Business Goals ---------------------------------------- Hosted on Acast. See acast.com/privacy [https://acast.com/privacy] for more information.

Links - Codecrafters (sponsor): https://tej.as/codecrafters - Agent Experience: https://agentexperience.ax - Arrazo: https://spec.openapis.org/arazzo/latest.html - Netlify: https://netlify.com - Sean on X: https://x.com/JavaSquip - Tejas on X: https://x.com/tejaskumar_ Summary This episode dives deep into the emerging field of Agent Experience (AX), exploring how software agents, including LLMs, will interact with the web and online services. The conversation highlights the distinction between the "human web" and the "agent web," emphasizing the need for new approaches to ensure agents can effectively understand context and execute tasks. Key topics include contextual alignment protocols like MCP (Machine Context Protocol), and standards such as `llms.txt` and `agents.json`, alongside efforts like Arrazo, which aim to provide structured information and enable complex workflows for agents. A significant portion of the discussion focuses on the challenges of authentication for agents, moving beyond human-in-the-loop processes and complex systems like OAuth2 towards more agent-friendly, secure, and auditable solutions, possibly involving dedicated agent user identities. The dialogue also covers practical considerations like providing data to LLMs efficiently, the importance of API accessibility for agents, and the need for businesses to adapt to this new paradigm of interaction. Finally, the conversation underscores that AX is a rapidly evolving area, transitioning from theoretical concepts to practical applications, with a strong call for community collaboration to develop best practices and robust solutions for the future of agent-driven web interactions. Chapters 00:00 Intro 03:35 Exploring Agent Experience (AX) and Its Importance 06:23 Understanding the Role of Model Context Protocol (MCP) 09:22 The Principles of Great Agent Experience 12:24 Agent Accessibility and Its Challenges 15:34 Contextual Alignment: Enhancing Agent Interaction 18:31 Human-Centric Design in Agent Experience 21:23 The Future of AI and Agent Experiences 24:25 Improving Human Accessibility Through Agentic Experiences 27:29 Primitives of Agent Accessibility 30:22 Avoiding Human in the Loop Patterns 33:19 Authentication in an Agentic World 38:34 Navigating API Token Strategies 43:30 Contextual Alignment: The Next Frontier 55:50 Understanding Agents vs. Bots 01:00:19 Optimizing Contextual Alignment for Agents 01:14:11 Understanding Website Infrastructure and Cost Implications 01:14:37 The Role of LLMs in Web Navigation 01:17:54 Quantifying ROI in Web Technologies 01:19:43 Introduction to Arazo and Workflow Management 01:24:26 Measuring Human vs. Agent Interaction 01:30:28 The Emergence of Agent Experience (AX) 01:38:09 Five Principles of Agent Experience (AX) ---------------------------------------- Hosted on Acast. See acast.com/privacy [https://acast.com/privacy] for more information.