Links

- Kendo React: https://www.telerik.com/kendo-react-ui/components/free

- Kathryn's Book: https://www.telerik.com/campaigns/design-story/ebook--foundations-of-design-for-developers

- Progress: https://progress.com

- Sam on X: https://x.com/samidip

- Kathryn on X: https://x.com/kathryngrayson

- Kiril on X: https://x.com/kirchoni

Summary

In this episode, we talk with Sam Basu, Kathryn Grayson Nanz, and Kiril to explore Kendo UI and Kendo React. We discuss the evolution of UI libraries, the engineering behind Kendo's components, and the importance of accessibility in modern applications. The conversation delves into the unique offerings of Kendo React, particularly its data grid and virtualization techniques, as well as the design considerations that enhance user experience.

The introduction of the Theme Builder is highlighted as a tool that bridges the gap between design and development, allowing for seamless collaboration and customization. We also cover the importance of collaboration between designers and developers, the significance of design tokens, and the incremental adoption of Kendo React in existing applications.

Chapters

00:00:00 Intro

00:04:24 Kendo UI and Progress

00:07:19 Kendo React's Unique Offerings

00:10:35 The Engineering Behind Kendo UI Components

00:13:10 Kendo React: A Case Study in UI Libraries

00:16:19 Accessibility and Compliance in Kendo React

00:19:35 Deep Dive into Kendo React's Data Grid

00:22:26 Virtualization Techniques in Kendo React

00:25:31 Design Considerations for Kendo UI Components

00:28:37 Theme Builder: Bridging Design and Development

00:38:15 Version Control in Design Workflows

00:39:22 The Evolution of Theme Builder

00:40:41 User-Centric Design and Feedback

00:42:35 The Role of Design Systems

00:44:37 Bridging the Gap: Designer-Developer Collaboration

00:46:12 Understanding Design Tokens

00:47:57 Incremental Adoption of Kendo React

00:55:53 State Management in Kendo React

00:62:37 Bundle Size Considerations

01:10:35 Measuring the Success of a Design System

01:15:14 Design Systems and Component Libraries

01:19:45 The Role of Progress and Kendo UI

01:24:21 Learning Resources for Developers

01:27:56 Evaluating UI Component Libraries

01:33:56 Collaboration in UI Design and Development

01:36:14 Emerging Technologies and AI in UI Development

01:44:23 Future Trends in React and UI Components

Hosted on Acast. See acast.com/privacy for more information.

Follow me on 𝕏: https://x.com/tejaskumar_

This podcast episode dives deep into the world of Event Sourcing, a powerful architectural pattern used in modern software development. Beginning with a clear definition of Event Sourcing, the episode explores its roots in Domain Driven Design and its critical role in recording and storing every change made to the state of an application in an event store. I break down complex topics, such as the nature of events, the intricacies of implementing Event Sourcing in real-world applications, and the various benefits and challenges associated with this approach.

Listeners will gain insights into the practical aspects of Event Sourcing, including detailed discussions on storage costs, computational expenses, and the practice of snapshotting to optimize performance. The episode also covers the concept of event ownership, Command Query Responsibility Segregation (CQRS), and ensuring data consistency using Apache Kafka, a distributed event streaming platform known for its high throughput, reliability, and scalability.

Further, the episode delves into Kafka's performance mechanisms, its use as an event store, and the transition from Zookeeper to KRaft for cluster coordination. Alternatives to Kafka, such as using Postgres' Write-Ahead Logging (WAL) as an event store, are examined, providing listeners with a comprehensive view of the options available for implementing Event Sourcing.

The discussion extends to real-life use cases of Event Sourcing, highlighting its application across various industries and projects. The experts also tackle some of the common problems encountered when adopting Event Sourcing, offering practical advice and solutions. Finally, the episode concludes with a thoughtful analysis on whether Event Sourcing is the right choice for your project, helping listeners to make informed decisions based on their specific needs and project requirements.

This episode is a must-listen for software developers, architects, and technology leaders looking to understand Event Sourcing, its benefits, challenges, and implementation strategies. Whether you're new to Event Sourcing or looking to refine your existing knowledge, this episode provides valuable insights into making the most of this powerful architectural pattern.

Chapters

00:00 - Intro

03:33 - Sponsor (CrabNebula.dev)

04:21 - Defining Event Sourcing

07:47 - What are Events? (Domain Driven Design)

14:45 - Real-World Examples of Event Sourcing

19:52 - Complexities of Event Sourcing

21:33 - Storage Costs

23:36 - Computational Costs

24:10 - Snapshotting

35:15 - Event Ownership

36:19 - CQRS

44:08 - Consistency with Kafka

54:10 - Kafka Performance Mechanisms

01:03:05 - Kafka as an Event Store

01:04:13 - Zookeeper & KRaft

01:09:47 - Postgres WAL as an Event Store?

01:13:24 - Event Sourcing Use Cases

01:18:50 - Event Sourcing Problems

01:26:22 - Should You Event Source?

01:27:44 - Conclusion

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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

Hosted on Acast. See acast.com/privacy for more information.

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

Hosted on Acast. See acast.com/privacy for more information.

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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