Oct 21, 2026

Does Code Quality Still Matter? It Depends on This — Max Kanat-Alexander, Capital One

Max Kanat-Alexander reframes the familiar "it depends" answer around two factors that govern all software work: understanding a system and safely changing it. He explains why code quality matters for durable software but not for a new, rapidly growing category of disposable software created by AI, and shows how to make systems more disposable and make rigor cheap through standardization, inward-flow tooling, easier testing, and maximum strictness.

Sep 11, 2026

Building ambitious software — Jonathan Kelley, Dioxus Labs & Cognition

Jonathan Kelley, founder of Dioxus Labs, shares insights from building a cross-platform Rust app framework for five years. He details Dioxus's evolution, its core technologies like Blitz and Subsecond, and the transformative impact of AI coding agents. Kelley explains how AI excels at handling Rust's complexity, automating mundane tasks, and serving as patient specialists for knowledge-intensive problems, yet falls short in writing effective tests. He concludes that while AI makes code cheap, quality remains paramount, shifting the engineer's focus to architecture and strategic system design.

Sep 07, 2026

Code Quality in the Age of AI: Why Great Code Isn't Enough

Meenakshi Kodati discusses how AI is transforming software engineering, shifting the focus from coding to critical decision-making. As AI rapidly generates code, the true challenge and value lie in architectural choices, system-level understanding, governance, testing, and continuous quality assurance to deliver meaningful business outcomes, emphasizing human judgment over mere implementation.

Aug 28, 2026

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.

Jul 20, 2026

In the Land of AI Agents, the Verifiers Are King — Tariq Shaukat, Sonar

This talk addresses the critical challenge of verification in AI agent development, moving beyond generation to ensure correctness. It highlights the problem of "AI slop" and the "productivity paradox" of AI coding agents, where initial velocity gains are offset by increased technical debt and quality issues. The speaker introduces the AC/DC (Agent-Centric Development Cycle) framework comprising three stages: Guide (providing context and constraints), Verify (zero-trust, multi-layered verification using both algorithmic and agentic methods), and Solve (active code maintenance to control technical debt). This systems-level approach, integrating verification across agentic, CI, and code maintenance loops, significantly reduces issues and transforms AI into a reliable enterprise asset.

Jul 17, 2026

The Great Loops Debate — Dex Horthy, Geoff Huntley, Ian Livingstone, Greg Pstrucha, @insecure-agents

An Oxford-style debate exploring the gap between the hype and practical reality of "loops" in AI/ML development. Experts discuss their history, optimal anatomy, future role in software factories, and challenges like security, economic viability, and the imperative for strong engineering discipline.