AI Coding Summit 2026

This talk will explore the ongoing fundamental transformation of the role of software developers. It will provide guidance on succeeding in this new rapidly evolving environment, where to focus your personal development, and explore the workflows and techniques that actually work, and aren’t hype or sales driven. 

AI coding tools work best when they can plan, act, and iterate - not just respond. This talk covers patterns for building autonomous workflows across the developer workflow and how you can get the most out of Claude Code.

LLMs need access to the relevant context to succeed. One key element of Context Engineering that we can use to help agents remember is Memory.Let's dive into the world of memory management for agents. We'll discuss the difference between short and long term memory, how to manage memory, and the importance of preventing context poisoning and clash using techniques such as trimming and summarization.

AI speeds up development — but it also introduces silent vulnerabilities. This talk exposes the hidden security risks of unreviewed AI-generated code and shows practical ways to protect your applications without slowing down your workflow.Table of Content: - How LLMs Generate Code & Why It Can Be Dangerous- Real-World Examples of AI-Introduced Vulnerabilities- A Practical, Secure Workflow for AI-Generated Code- Q&A

AI code reviews often feel like tossing a coin. Heads - you get endless nitpicks about style. Tails - it finds real issues. And even when the signal is good, are we really getting quality and productivity benefits?The secret isn't the AI, it's how we're deploying it. This talk explores what actually drives value in AI-assisted code reviews: rich contextual integration, scalable specialization, and measurable impact on developer productivity. Learn to transform AI reviews from a compliance checkbox into a strategic advantage for your engineering organization.

Developers now create entire applications by simply chatting with AI tools. More and more startups rely on predominantly AI-generated code. But what initially thrilled developers quickly leads to frustration: generic code, poor architecture, and security vulnerabilities.In this talk, I demonstrate how Spec Driven Development (SDD) solves these problems. Instead of coding first and documenting later, SDD begins with precise specifications as the "single source of truth." Various tools and CLIs make this methodology practically applicable today with a structured 4-phase approach: Specify, Plan, Tasks, Implement.Using a real project, I show how SDD works with modern AI coding tools. I share honest insights from hands-on experience: where SDD excels, where it fails, and whether the specification overhead actually leads to better results.