Cucumber

BDD, ADR, PRD, WTF: Capturing Decisions for Humans and AI Alike — Michal Cichra, Safe Intelligence

Jun 3, 2026 · 12:49

Michal Cichra from Safe Intelligence argues that teams using AI agents must capture architectural and product decisions in structured documents—ADRs, PRDs, and BDD scenarios—to compensate for LLMs' limited context and prevent the 'why did we do this' confusion. He explains that ADRs record rules and enforcement methods, like splitting code layers to prevent N+1 queries via module import linting, while PRDs describe user journeys. BDD with Cucumber closes the spec-driven development loop by providing executable, human-readable scenarios that connect to PRDs. Enforcement is done through git hooks and CI, rejecting agents at commit time and linking them back to the relevant documents for iteration. Sessions experience 20 to 50 context compacts, but the important rules survive because agents reload them. Design systems and pattern libraries further enforce UI consistency by defining components and banning inline styles.

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.