ConTejas Code – Détails, épisodes et analyse

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

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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

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- Codecrafters: https://tej.as/codecrafters

- Tejas on X: https://x.com/tejaskumar_

- JSHeroes conference: https://jsheroes.io

- Attention is All You Need Paper: https://scispace.com/pdf/attention-is-all-you-need-1hodz0wcqb.pdf

- Google Agents paper: https://ppc.land/content/files/2025/01/Newwhitepaper_Agents2.pdf

- Jack Herrington episode about implementing MCP server:

- YouTube: https://www.youtube.com/watch?v=0zXyCQV4A84

- Apple: https://podcasts.apple.com/nz/podcast/jack-herrington-model-context-protocol-mcp-growing/id1731855333?i=1000698551942

- Spotify: https://open.spotify.com/episode/5u7ReU2AMnS3TOYuiSwVY1?si=HrBzavRGThOITtYdXDloTA

- John McBride episode about fine-tuning Mistral 7B at OpenSauced

- YouTube: https://www.youtube.com/watch?v=ipbhB3k0ik0

- Apple: https://podcasts.apple.com/us/podcast/1731855333?i=1000663298584

- Spotify: https://open.spotify.com/episode/77UWTis0TxCd1uPOZhGAnJ?si=CUGmHtJ2RxWhmW5MI3XYbg

This episode is a long-form lecture on AI innovation in 2025. We cover a wide range of topics. For more details, see chapters below.

00:00:00 Intro

00:02:31 What is AI?

00:07:30 Limitations of AI

00:14:29 Solving AI Problems with RAG

00:22:51 Embeddings and Vector Databases Explained

00:31:23 Hybrid Search: Vectors and Keywords (BM25)

00:38:17 Rerankers for Maximum Accuracy

00:43:51 RAG vs. Fine-Tuning

00:54:29 AI Agents

01:13:12 Model Context Protocol (MCP)

01:26:12 How to Get Started

01:34:04 Conclusion

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Links

- Codecrafters: https://tej.as/codecrafters

- Tiny Fish: https://tinyfish.io

- AgentQL: https://www.agentql.com/

Summary

In this conversation, we discuss AgentQL, a framework designed to enable AI agents to access the web using natural language. Together, we explore the technical aspects of AgentQL, its advantages over traditional web access methods, and the challenges faced in its development. The discussion also covers the role of TinyFish, the parent company of AgentQL, and the future direction of their products.

Key use cases for developers are highlighted, showcasing how AgentQL can simplify web scraping and automation tasks. We deep dive into the integration of Playwright with AgentQL, the engineering decisions behind its development, and the importance of maintaining consistency across different SDKs. The conversation also touches on the challenges of remote browsing, security concerns, and the complexities of navigating data structures. Additionally, the various operating modes of AgentQL are explored, highlighting the trade-offs between speed and accuracy.

Chapters

03:25 Introduction to AgentQL

06:33 The Technical Framework of AgentQL

09:34 Challenges with Traditional Web Access

12:35 The Role of TinyFish and Future Products

15:25 Technical Hurdles in Building AgentQL

18:26 Interacting with the DOM

21:29 Use Cases for Developers

24:21 Building with AgentQL

27:35 Disambiguation and Query Context

30:32 Balancing Precision and Flexibility

33:30 Future Directions and Enhancements

36:36 Integrating Playwright with AgentQL

38:56 Building Infrastructure for Remote Browsing

39:30 Engineering Decisions in AgentQL Development

45:05 Web Test Automation and AgentQL

45:55 SDK Development: Python vs JavaScript

47:39 Maintaining Consistency Across Languages

51:40 Cross-Browser Support with Playwright

54:17 Security Concerns in Remote Browsing

59:14 Navigating Complex Data Structures

01:03:36 Operating Modes of AgentQL

01:04:20 Understanding Browser Fingerprinting and Anti-Bot Measures

01:06:31 Exploring AgentQL's Browser Toolkit for Langchain

01:09:15 AgentQL's Potential in Automating Workflows

01:10:17 The Future of Email Automation with AgentQL

01:11:34 Navigating the Challenges of Building a Startup

01:16:20 Achieving Success on Product Hunt

01:19:30 Implementation Pitfalls for New AgentQL Developers

01:21:37 Founder's Playbook: Lessons Learned

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Links

- Codecrafters (partner): https://tej.as/codecrafters

- Snyk: https://snyk.io/

- Liran on X: https://x.com/liran_tal

- Tejas on X: https://x.com/tejaskumar_

Summary

In this conversation, we explore the complexities of software security, particularly focusing on the challenges posed by Node.js and the broader software supply chain. We discuss the evolution of security practices, the importance of awareness among developers, and the role of automation in enhancing security measures. The conversation highlights the need for a balance between automated tools and manual audits, emphasizing that human oversight remains crucial in high-risk environments.

We also explore the vulnerabilities associated with open-source software and the trust developers place in third-party tools and extensions, specifically the importance of SBOMs in understanding software dependencies. We discuss the SolarWinds attack as a pivotal case in supply chain security and the role of tools like lockfile lint in enforcing security policies.

Finally, we discuss AI and the role of LLMs in security, particularly regarding attack vectors and the reliability of AI-generated code.

Chapters

00:00 Liran Tal

01:44 Introduction to Security in Software Development

04:53 The Evolution of Node.js and Security Challenges

07:29 Understanding Software Supply Chain Vulnerabilities

10:49 The Role of Open Source in Security

13:51 Exploring Security in Development Tools and Extensions

16:40 The Importance of Security Awareness and Training

19:40 Automating Security: Tools and Best Practices

22:30 The Balance Between Automation and Manual Audits

25:43 Conclusion and Future of Security in Software Development

35:00 Balancing Automation and Human Intervention in Security

38:08 Understanding S-BOMs and Their Importance

41:14 The SolarWinds Attack: A Case Study in Supply Chain Security

43:29 Lockfile Lint: Enforcing Security Policies in Code

46:49 Generating SBOMs: A Practical Approach

49:03 Demystifying CVSS: Understanding Vulnerability Scoring

52:50 AI in Security: Attack Vectors and Defense Strategies

59:52 Navigating Security in AI-Generated Code

01:05:39 The Role of LLMs in Security Vulnerability Detection

01:08:24 Integrating Agents for Secure Code Generation

01:11:16 Challenges of LLMs in Security Validation

01:14:42 The Complexity of Security in AI Systems

01:20:56 Understanding Fuzzing and AI's Role

01:24:08 Container Breakout Threats and Mitigation Strategies

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Links

- Codecrafters (sponsor): https://tej.as/codecrafters

- Jack on YouTube: https://www.youtube.com/@jherr

- Jack on X: https://x.com/jherr

- Jack on Bluesky: https://bsky.app/profile/jherr.dev

- Tejas on X: https://x.com/tejaskumar_

- create-tsrouter-app: https://github.com/TanStack/create-tsrouter-app

Summary

In this discussion, Jack Harrington and I explore the transition from being a content creator to an open source contributor, discussing the challenges and rewards of both paths. Jack shares his journey from being a principal engineer to a YouTuber, and now to a key player in the open source community with TanStack. We explore the intricacies of YouTube's algorithm, the importance of marketing oneself, and the unique features of Tanstack that allow for a progressive development experience. We also touch on the future of Tanstack, its cross-platform capabilities, and the potential integration with React Native.

We also discuss AI! Specifically, we discuss the Model Context Protocol (MCP) and how it provides tools and resources to AI, enabling seamless integration with applications. We explore the potential of local development with MCP, emphasizing its advantages over traditional cloud-based solutions.

Chapters

00:00 Jack Herrington

06:11 Transitioning from Influencer to Open Source Contributor

09:10 The YouTube Journey: Challenges and Growth

12:13 Navigating the YouTube Algorithm and Marketing Yourself

15:09 The Shift to Open Source and Community Engagement

18:18 Creating Tanstack: A New Era in Development

20:55 The Unique Features of Tanstack and Its Ecosystem

24:09 Progressive Disclosure in Frameworks

26:54 Cross-Platform Capabilities of Tanstack

30:16 The Future of Tanstack and React Native Integration

40:05 Navigating the Tanstack Ecosystem

42:21 Understanding Model Context Protocol (MCP)

54:04 Integrating MCP with AI Applications

01:05:09 The Future of Local Development with MCP

01:11:03 Creating a Winamp Clone with AI

01:17:07 The Future of Front-End Development and AI

01:24:49 Connecting Dots: The Power of MCP and AI Tools

01:33:27 The Entrepreneurial Spirit: Beyond Money

01:39:27 Closing Thoughts and Future Collaborations

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Links

- Codecrafters (sponsor): https://tej.as/codecrafters

- Feedback Intelligence: https://www.feedbackintelligence.ai/

- Chinar on X: https://x.com/movsisyanchinar

Summary

In this podcast episode, we talk to Chinar Movsisyan, the CEO and founder of Feedback Intelligence. They discuss Chinar's extensive background in AI, including her experience in machine learning and computer vision. We discuss the challenges faced in bridging the gap between technical and non-technical stakeholders, the practical applications of feedback intelligence in enhancing user experience, and the importance of identifying failure modes. The discussion also covers the role of LLMs in the architecture of Feedback Intelligence, the company's current stage, and how it aims to make feedback actionable for businesses.

Chapters

00:00 Chinar Movsisyan

02:08 Introduction to Feedback Intelligence

03:23 Chinar Movsisyan's Background and Expertise

06:33 Understanding AI Engineer vs. GenAI Engineer

09:08 The Lifecycle of Building an AI Application

13:27 Data Collection and Cleaning Challenges

16:20 Training the AI Model: Process and Techniques

24:48 Deploying and Monitoring AI Models in Production

27:55 The Birth of Feedback Intelligence

31:58 Understanding Feedback Intelligence

33:26 Practical Applications of Feedback Intelligence

42:13 Identifying Failure Modes

45:58 The Role of LLMs in Feedback Intelligence

51:25 Company Stage and Future Directions

57:24 Making Feedback Actionable

01:01:30 Streamlining Processes with Automation

01:03:18 The Journey of a First-Time Founder

01:05:48 Wearing Many Hats: The Founder Experience

01:08:22 Prioritizing Features in Early Startups

01:13:09 Learning from Customer Interactions

01:16:38 The Importance of Problem-Solving

01:21:51 Handling Rejection and Staying Motivated

01:27:43 Marketing Challenges for Founders

01:29:23 Future Plans and Scaling Strategies

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Links

- Codecrafters (partner): https://tej.as/codecrafters

- Ghost: https://ghost.org/

- Daniel on X: https://x.com/daniellockyer

- Tejas on X: https://x.com/tejaskumar_

Summary

In this conversation, Daniel Lockyer (Ghost) and I explore the intricacies of DevOps, server management, and the balance between simplicity and complexity in software engineering. We discuss the ideal server setup for static sites, scaling considerations, the use of PHP and NGINX, and the challenges of manual server management. The conversation also touches on the debate around Kubernetes, cognitive load in software engineering, and the importance of monitoring and alerting. Ultimately, we emphasize the accessibility of server management and the common fears that prevent individuals from taking the plunge into this domain.

Chapters

00:00 Daniel Lockyer

03:41 Introduction to DevOps and Server Management

09:36 Simplicity in Server Setup

15:38 The Kubernetes Debate

21:37 Challenges of Manual Server Management

27:33 Productizing Server Management

33:29 The Fear of Failure in Server Management

39:21 Navigating Server Management Challenges

46:42 The Cost of Custom Solutions vs. Managed Services

55:39 Building a Custom Platform as a Service

01:03:31 AI Integration in DevOps Practices

01:08:50 Cost-Effective Solutions in Kubernetes

01:15:18 The Importance of Passion in Programming

01:21:41 The Impact of Programming on Life Choices

01:33:01 Simplicity as the Key to Problem Solving

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Links

- Codecrafters (partner): https://tej.as/codecrafters

- Blog Recorder: https://blogrecorder.com/

- Eddy on X: https://x.com/eddyvinckk

- Tejas on X: https://x.com/tejaskumar_

Summary

In this conversation, we discuss Blog Recorder which allows users to create blog posts by speaking their thoughts. Eddy explains the technology behind the product, including the speech-to-text pipeline and the AI components involved. He shares insights into his journey as a software engineer, the balance between AI and UI development, and the importance of building a future-proof product.

Chapters

00:00:00 Eddy Vinck

00:03:08 Introduction to Blog Recorder

00:06:11 Understanding the Technology Behind Blog Recorder

00:09:12 The Speech-to-Text Pipeline Explained

00:12:05 Eddy's Journey as a Software Engineer

00:15:07 Balancing AI and UI Development

00:18:07 Building a Future-Proof Product

00:20:54 Choosing the Right Hosting Solutions

00:24:15 Lessons Learned from Building Blog Recorder

00:31:02 Kubernetes and Cloud Infrastructure Insights

00:40:32 Navigating Product Development and MVPs

00:52:09 The Importance of Early Feedback in Product Launches

01:00:21 Timing and Market Readiness

01:01:37 Innovations in Blog Recording

01:03:29 AI and Long-Form Content Creation

01:10:35 Current State of Blog Recorder

01:18:53 Future Aspirations and Marketing Strategies

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Links

- Codecrafters (sponsor): https://tej.as/codecrafters

- FASHN AI: https://fashn.ai

- Dan on X: https://x.com/danbochman

- Aya on X: https://x.com/ayaboch

- Tejas on X: https://x.com/tejaskumar_

Summary

In this conversation, we dive deep into the intricacies of AI, focusing on concepts like latent space, diffusion, and the evolution of image generation techniques. We explore how latent space serves as a condensed representation of features, the challenges faced by GANs, and how diffusion models have emerged as a more effective method for generating images from noise. The discussion also touches on the importance of quantization in AI models and the iterative approaches used in image generation.

Chapters

00:00 Dan Bochman

02:25 Introduction to AI and Latent Space

07:24 Understanding Latent Space and Its Importance

12:29 The Concept of Diffusion in AI

17:21 From Noise to Image Generation

22:32 Challenges with GANs and the Emergence of Diffusion

27:28 The Role of Quantization in AI Models

32:26 Iterative Approaches in Image Generation

35:51 The Noise of Life and Image Clarity

37:09 Exploring Diffusion Models in Creative Generation

39:00 Understanding Latent Space and Its Importance

40:27 Diving Deeper into Loss Functions and Image Quality

43:32 Signal to Noise Ratio in Image Generation

45:54 The Transition to Latent Space for Better Learning

48:44 The Power of Variational Autoencoders

53:01 Navigating the Uncanny Valley in AI Generated Images

57:43 Guidance in Image Generation and Fashion Applications

01:10:24 Understanding Architecture in AI Models

01:14:40 Training Diffusion Models: Getting Hands-On

01:21:18 Fine-Tuning Techniques and Challenges

01:26:53 The Accessibility of AI Model Development

01:34:10 Navigating Funding and Research in AI

01:46:45 Lessons Learned: The Builder's Journey

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