Windsurf Archives - Scrum Master Toolbox Podcast

AI Assisted Coding: Building Reliable Software with Unreliable AI Tools

In this special episode, Lada Kesseler shares her journey from AI skeptic to pioneer in AI-assisted development. She explores the spectrum from careful, test-driven development to quick AI-driven experimentation, revealing practical patterns, anti-patterns, and the critical role of judgment in modern software engineering.

From Skeptic to Pioneer: Lada’s AI Coding Journey

“I got a new skill for free!”

Lada’s transformation began when she discovered Anthropic’s Claude Projects. Despite being skeptical about AI tools throughout 2023, she found herself learning Angular frontend development with AI—a technology she had no prior experience with. This breakthrough moment revealed something profound: AI could serve as an extension of her existing development skills, enabling her to acquire new capabilities without the traditional learning curve. The journey evolved through WindSurf and Claude Code, each tool expanding her understanding of what’s possible when developers collaborate with AI.

Understanding Vibecoding vs. AI-Assisted Development

“AI assisted coding requires judgment, and it’s never been as important to exercise judgment as now.”

Lada introduces the concept of “vibecoding” as one extreme on a new dimension in software development—the spectrum from careful, test-driven development to quick, AI-driven experimentation. The key insight isn’t that one approach is superior, but that developers must exercise judgment about which approach fits their context. She warns against careless AI coding for production systems: “You just talk to a computer, you say, do this, do that. You don’t really care about code… For some systems, that’s fine. When the problem arises is when you put the stuff to production and you really care about your customers. Please, please don’t do that.” This wisdom highlights that with great power comes great responsibility—AI accelerates both good and bad practices.

The Answer Injection Anti-Pattern When Working With AI

“You’re limiting yourself without knowing, you’re limiting yourself just by how you formulate your questions. And it’s so hard to detect.” Continue reading AI Assisted Coding: Building Reliable Software with Unreliable AI Tools

AI Assisted Coding: Pachinko Coding—What They Don’t Tell You About Building Apps with Large Language Models, With Alan Cyment

In this BONUS episode, we dive deep into the real-world experience of coding with AI. Our guest, Alan Cyment, brings honest perspectives from the trenches—sharing both the frustrations and breakthroughs of using AI tools for software development. From “Pachinko coding” addiction loops to “Mecha coding” breakthroughs, Alan explores what actually works when building software with large language models.

From Thermomix Dreams to Pachinko Reality

“I bought into the Thermomix coding promise—describe the whole website and it would spit out the finished product. It was a complete disaster.”

Alan started his AI coding journey with high expectations, believing he could simply describe a complete application and receive production-ready code. The reality was far different. What he discovered instead was an addictive cycle he calls “Pachinko coding” (Pachinko, aka Slot Machines in Japan)—repeatedly feeding error messages back to the AI, hoping each iteration would finally work, while burning through tokens and time. The AI’s constant reassurances that “this time I fixed it” created a gambling-like feedback loop that left him frustrated and out of pocket, sometimes spending over $20 in API credits in a single day.

The Drunken PhD with Amnesia

“It felt like working with a drunken PhD with amnesia—so wise and so stupid at the same time.”

Alan describes the maddening experience of anthropomorphizing AI tools that seem brilliant one moment and completely lost the next. The key breakthrough came when he stopped treating the AI as a person and started seeing it as a function that performs extrapolations—sometimes accurate, sometimes wildly wrong. This mental shift helped him manage expectations and avoid the “rage coding” that came from believing the AI should understand context and maintain consistency like a human collaborator.

Making AI Coding Actually Work

“I learned to ask for options explicitly before any coding happens. Give me at least three options and tell me the pros and cons.” Continue reading AI Assisted Coding: Pachinko Coding—What They Don’t Tell You About Building Apps with Large Language Models, With Alan Cyment

AI Assisted Coding: Agile Meets AI—How to Code Fast Without Breaking Things, With Llewellyn Falco

In this BONUS episode we explore the practice of coding with AI—not just the buzzwords, but the real-world experience. Our guest, Llewellyn Falco, has been learning by doing, exploring the space of AI-assisted coding from the experimental and intuitive—what some call vibecoding—to the more structured world of professional, world-class software engineering. This is a conversation for practitioners who want to understand what’s actually happening on the ground when we code with AI.

Understanding Vibecoding

“You can now program without looking at code. When you’re in that space, vibecoding is the word we’re using to say, we are programming in a way that does not relate to programming last year.”

The software development landscape shifted dramatically in early 2025. Vibecoding represents a fundamental change in how we create software—programming without constantly looking at the code itself. This approach removes many traditional limitations around technology, language, and device constraints, allowing developers to move seamlessly between different contexts. However, this power comes with responsibility, as developers can now move so fast that traditional safety practices become even more critical.

From Concept to Working App in 15 Minutes

“We wrote just a markdown page of ‘here’s what we want this to look like’. And then we fed that to Claude Code. And 15 minutes later we had a working app on the phone.”

At the Agile 2025 conference in Denver, Llewellyn participated in a hackathon focused on helping psychologists prevent child abuse. Working with customer Amanda, a psychologist, and data scientist Rachel, the team identified a critical problem: clinicians weren’t using the most effective parenting intervention technique because recording 60 micro-interactions in 5 minutes was too difficult and time-consuming.

The team’s approach embodied lean startup principles turned up to eleven. After understanding the customer’s needs through exposition and conversation, they created a simple markdown specification and used Claude Code to generate a working mobile app in just 15 minutes. When Amanda tested it, she was moved to tears—after 20 years of trying to make progress on this problem, she finally had hope. Over three days, the team released 61 iterations, constantly getting feedback and refining the solution.

Iterative Development Still Matters When Coding With AI

“We need to see things working to know what to deliver next. That’s never going to change. Unless you’re building something that’s already there.” Continue reading AI Assisted Coding: Agile Meets AI—How to Code Fast Without Breaking Things, With Llewellyn Falco