Modern Web

In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson talk with Philipp Krenn, Head of Developer Advocacy at Elastic, about how Elasticsearch has evolved from a search engine into a foundation for observability, security, and AI-powered systems. Philipp explains how Elastic approaches information retrieval beyond just vector search, using tools like LLMs for smarter querying, log parsing, and context-aware data access.They also discuss how Elastic balances innovation with stability through regular releases and a focus on long-term reliability. For teams building with AI, Elastic offers a way to handle search, monitoring, and logging in one platform, making it easier to ship faster without adding complexity.Key points from this episode: Elasticsearch has expanded beyond search to support observability and security by treating all of them as information retrieval problems.Elastic integrates with AI tools like LLMs to improve search relevance, automate log parsing, and enable features like query rewriting and retrieval-augmented generation.Vector search is just one feature in a larger toolkit for finding relevant data, and Elastic supports hybrid and traditional search approaches.Elastic maintains a steady release cadence with a focus on stability, making it a reliable choice for both fast-moving AI projects and long-term production systems.Philipp Krenn on Linkedin: https://www.linkedin.com/in/philippkrenn/Rob Ocel on Linkedin: https://www.linkedin.com/in/robocel/Danny Thompson on Linkedin: https://www.linkedin.com/in/dthompsondev/This Dot Labs Twitter: https://x.com/ThisDotLabsThis Dot Media Twitter: https://x.com/ThisDotMediaThis Dot LabsInstagram: https://www.instagram.com/thisdotlabs/This Dot Labs Facebook: https://www.facebook.com/thisdot/This Dot Labs Bluesky: https://bsky.app/profile/thisdotlabs.bsky.socialSponsored by This Dot Labs: ai.thisdot.co

In this episode of Modern Web, Danny Thompson chats with MelkeyDev, a Machine Learning Infrastructure Engineer at Twitch, about AI’s real-world applications, developer productivity, and the future of careers in Go. They cover everything from the rise of tiny AI-driven teams competing with large enterprises to how system prompts may matter more than model choice. Melkey shares his thoughts on cost-effective LLMs, production pitfalls, and the cognitive downsides of over-relying on AI. The conversation also explores backend development with Go, what makes it great for fast-moving teams, and how new developers can get started.Keypoints from this episode:- AI’s real value lies in business use cases. Melkey emphasizes that AI isn’t just a productivity tool; it enables small teams to build faster, cheaper, and more effectively than ever before.- System prompts are underrated. When it comes to LLM performance, prompt engineering often matters more than the model itself, especially for UI generation and agent design.- Cognitive cost of AI reliance. Referencing recent research, Melkey warns that overusing AI tools can reduce your ability to retain knowledge and perform certain tasks independently.- Go remains a strong backend choice. Despite being “boring,” Go continues to power developer velocity and scalable infrastructure, making it a smart language for backend-focused engineers.Follow MelkeyDev on Twitter: https://x.com/MelkeyDevSponsored by This Dot Labs: thisdot.co

On this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson talk with Brian Morrison, Senior Developer Educator at Clerk. They cover the state of authentication today, what makes Clerk stand out for small teams and indie builders, and how thoughtful developer experience design can make or break adoption.Brian shares why bundling tools like auth, billing, and user management is becoming more common, how Clerk handles real-world concerns like bot protection and social login, and why starting with a great developer experience matters more than ever.The conversation also explores the role of AI in software development and content creation, where it helps, where it hurts, and how to use it responsibly without losing quality or trust.Keypoints for this Episode:Modern auth is about experience, not just security. Clerk simplifies user management, social login, bot protection, and subscription billing with developer-friendly APIs and polished default UIs.Bundled platforms are making a comeback. Developers are shifting from handpicking tools to using tightly integrated services that reduce setup time and complexity.Developer education needs more care and creativity. Brian emphasizes the importance of visual storytelling, thoughtful structure, and anticipating confusion to help devs learn faster and retain more.AI is a productivity multiplier, not a replacement. The group discusses how AI can accelerate development and content creation when used with oversight, but warn against using it to blindly build entire apps.Follow Brian Morrison on Social MediaTwitter: https://x.com/brianmmdevLinkedin: https://www.linkedin.com/in/brianmmdev/Sponsored by This Dot: thisdotlabs.com

In this episode of the Modern Web Podcast, Rob Ocel, Danny Thompson, and Adam Rackis sit down with Ahmad Awais, CEO and founder of LangBase, to talk about agents, context, and the future of AI-assisted software development. Ahmad shares the origin story of Chai.new, an agent that builds agents, and why he believes context, not code, is the true value layer in the AI era. The group unpacks how "vibe coding" is reshaping who can build software, why Chai isn’t just another AI assistant, and how agents might evolve into personalized, production-grade tools for everyone, technical or not. Plus: Tailwind analogies, Stanford lectures, sports nutrition agents, and a CLI that went viral in a hospital.Key points from this episode:- Ahmad Awais explains that AI agents aren't magic; they're just a new paradigm for writing software. What makes them powerful is their ability to act autonomously with relevant context, not just generate text.- Chai.new helps developers (and non-developers) create purpose-built agents without needing deep ML expertise. It abstracts complex concepts like memory, retrieval, and orchestration into an approachable interface.- Ahmad emphasizes that the real opportunity lies in agents tailored to individual users and use cases. Personal agents with custom context outperform generic ones, much like small teams beat massive frameworks for specific problems.- Chai and LangBase aim to bring AI development to the millions of engineers who aren't AI researchers. With tools like Chai, you don’t need a PhD to build powerful, production-ready AI agents.Follow Ahmad Awais on Social MediaTwitter: https://x.com/MrAhmadAwaisLinkedin: https://www.linkedin.com/in/mrahmadawais/Sponsored by This Dot: thisdot.co

In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson sit down with Julián Duque, Principal Developer Advocate at Heroku, to talk about Heroku’s evolution into an AI Platform-as-a-Service. Julián breaks down Heroku’s new Managed Inference and Agents (MIA) platform, how they’re supporting Claude, Cohere, and Stable Diffusion, and what makes their developer experience stand out.They also get into Model Context Protocols (MCPs)—what they are, why they matter, and how they’re quickly becoming the USB-C for AI. From internal tooling to agentic infrastructure and secure AI deployments, this episode explores how MCPs, trusted environments, and better AI dev tools are reshaping how we build modern software.Key Points from this episode:- Heroku is evolving into an AI Platform-as-a-Service with its new MIA (Managed Inference and Agents) platform, supporting models like Claude, Cohere, and Stable Diffusion while maintaining a strong developer experience.- MCPs (Model Context Protocols) are becoming a key standard for extending AI capabilities—offering a structured, secure way for LLMs to access tools, run code, and interact with resources.- Heroku's AI agents can perform advanced operations like scaling dynos, analyzing logs, and self-healing failed deployments using grounded MCP integrations tied to the Heroku CLI.- Despite rapid adoption, MCPs still have rough edges—developer experience, tooling, and security protocols are actively improving, and a centralized registry for MCPs is seen as a missing piece.Chapters0:00 – What is MCP and why it matters3:00 – Heroku’s pivot to AI Platform-as-a-Service6:45 – Agentic apps, model hosting, and tool execution10:50 – Why REST isn’t ideal for LLMs14:10 – Developer experience challenges with MCP18:00 – Hosting secure MCPs on Heroku23:00 – Real-world use cases: scaling, healing, recommendations30:00 – Common scaling challenges and hallucination risks34:30 – Testing, security, and architecture tips36:00 – Where to start and final advice on using AI tools effectivelyFollow Julián Duque on Social MediaTwitter/X: https://x.com/julian_duqueLinkedin: https://www.linkedin.com/in/juliandavidduque/Sponsored by This Dot: thisdotlabs.com

In this episode of the Modern Web Podcast, Rob Ocel is joined by Danny Thompson, Adam Rackis, and special guest Coston Perkins for a lively discussion on the evolving role of AI in software development. The group swaps thoughts on everything from the rise of AI agents like RooCode and Claude, to what makes tools like Vercel’s v0 surprisingly powerful for frontend work. They debate Tailwind’s dominance as the styling output of choice for AI tools, unpack the implications of Shopify’s AI-mandate memo, and tackle the big question: will AI reshape team structures or just amplify developer productivity?Keypoints from this episode:- AI agents in everyday development – The hosts discuss how tools like RooCode, Claude, and Cursor are reshaping daily coding workflows, enabling everything from automated documentation to feature planning and refactoring.- Vercel's v0 is changing perceptions – Originally seen as a landing page generator, v0 is now appreciated for its live, code-focused interface, showing promise for serious frontend development with real-time editing and deployment.- Tailwind’s dominance in AI output – The conversation dives into why Tailwind has become the styling default for AI-generated components, and whether that’s a productivity boost or a future limitation.- AI’s impact on hiring and team structure – The group debates whether AI will reduce developer headcount or empower mid-level devs to produce senior-level output—suggesting AI may reshape team dynamics more than replace them.Follow Coston Perkins on Linkedin: https://www.linkedin.com/in/costonperkins/Sponsored by This Dot: thisdot.co

In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson talk with Corbin Crutchley — founder of Playful Programming, Microsoft MVP, GitHub Star, and maintainer of multiple TanStack libraries including TanStack Form, Store, and Config.They dive into Corbin’s work maintaining open source at scale, what makes TanStack Form different (and a bit esoteric), and why the design decisions behind it matter, especially for enterprise teams. They also unpack the tradeoffs of abstraction, type safety in large-scale apps, and best practices for migrating form logic.Later in the episode, the conversation shifts to Corbin’s nonprofit and developer education philosophy: why Playful Programming focuses on deep conceptual understanding over task-based tutorials, how AI is changing how people learn, and what’s next for guiding developers from beginner to intermediate and beyond.Key points from this episode:– Corbin explains how TanStack Form’s architecture, though verbose and esoteric, enables strong type safety, SSR support, and integration with modern frameworks like Next.js and Remix.– The group discusses common pain points in migrating from other form libraries, especially around type inference and validation layers, and how TanStack Form encourages a clean separation of concerns.– Maintaining open source at scale requires balancing community feedback with a strong guiding philosophy; Corbin highlights the importance of civility and staying true to the project’s design principles.– Playful Programming focuses on deep, conceptual education over task-based tutorials, aiming to help learners move from beginner to intermediate with free, accessible content and personalized learning in the future.Chapters0:00 – Why TanStack Form Is Built This Way1:06 – Meet Corbin Crutchley and the TanStack Ecosystem3:34 – How Corbin Joined and Shaped TanStack Form6:17 – Why Use TanStack Form (Despite the Verbosity)10:28 – Type Safety, Generics, and Enterprise-Ready Patterns14:50 – Validation Best Practices and SSR Integration18:45 – Handling Feedback in Open Source21:22 – Playful Programming: Teaching Concepts Over Tasks27:33 – Bridging the Developer Education Gap35:54 – Is It Still Worth Learning Programming?38:25 – The Evolving Role of Developers and Soft Skills41:57 – Wrap-Up and Where to Connect OnlineFollow Corbin Crutchley on Social MediaLinkedin: https://www.linkedin.com/in/corbincrutchleyX/Twitter: https://x.com/crutchcornSponsored by This Dot: thisdot.co