SpecKit

Using Spec-Driven Development for Production Workflows - Erik Hanchett, AWS

Jun 28, 2026 · 17:47

Erik Hanchett (AWS) argues that spec-driven development—writing markdown specification files before any code—produces higher quality code by guiding AI coding assistants, which he compares to 'AI interns' that need explicit direction. He introduces Kiro, AWS’s new AI IDE and CLI, which offers a spec mode that generates requirements documents, design documents with mermaid diagrams, property-based tests using Fastcheck, and a task list. In a demo building a movie website, Kiro created an MVP-focused implementation verified by property tests. Hanchett also highlights integrating external data via the Model Context Protocol (MCP) and stresses the importance of human review. He advises balancing context in steering docs and using on-demand skills to control the workflow.

Full Walkthrough: Workflow for AI Coding — Matt Pocock

Apr 24, 2026 · 1:36:30

Matt Pocock presents a hands-on workshop on building a full AI-assisted coding workflow, arguing that software engineering fundamentals—not hype—make agents effective. He introduces the 'smart zone' and 'dumb zone' of LLMs (performance drops after ~100k tokens) and the 'Memento problem' (agents forget between sessions). His process starts with a 'Grill Me' skill that relentlessly questions the user until shared understanding is reached, then produces a PRD without reading it, slices work into vertical 'tracer bullet' issues, and runs agents AFK using TDD. He advocates designing codebases with deep, testable modules and shows Sandcastle, a TypeScript library for parallel agent execution with separate implementer (Sonnet) and reviewer (Opus). The workshop transforms ambiguous briefs into shippable features while keeping humans in the loop for QA and taste.