Brian Casel's Spec-Driven Development

Table of content

Brian Casel is a product designer and developer who has bootstrapped and sold five software businesses over 15 years. In 2025, he shifted focus to teaching developers how to build with AI through Builder Methods, creating open-source frameworks that bring structure to what he calls the chaos of AI-assisted development.

Background

Serial bootstrapper with five exits including Audience Ops and ZipMessage
Full-stack product designer and Ruby on Rails developer
Creator of Agent OS, Design OS, and Builder Methods training platform
Co-host of Bootstrapped Web and The Panel podcasts

GitHub | Twitter | Blog

The Problem with AI Coding

Casel noticed a pattern: developers using AI coding tools kept hitting the same walls. The AI would generate code, but without context about why it existed or how it fit the broader system. Three months later, nobody dared touch it.

From his AI-First Development Framework Guide:

“AI projects that promised innovation stall out, burning budget on hidden maintenance and refactoring costs.”

The supposed productivity gains vanished into debugging sessions and refactoring cycles.

Agent OS

Agent OS is a free, open-source system for spec-driven development with AI coding agents. The core idea: instead of prompting AI to write code directly, you write specs first, then let the AI implement against those specs.

# Agent OS workflow
1. Shape spec (requirements, constraints, acceptance criteria)
2. AI generates implementation plan
3. Execute tasks against the spec
4. Verify output matches spec

The system works with any AI tool: Claude Code, Cursor, Codex, or Gemini. No vendor lock-in.

Feature	Description
Modular architecture	Adapts to your existing workflow
Multi-agent orchestration	Coordinate multiple AI agents on complex builds
Tool-agnostic	Works with any AI coding assistant
Standards alignment	Trains agents to follow your coding conventions

Agent OS now at version 3.0 includes profiles, standards injection, and product planning templates.

Design OS

Design OS fills a gap Casel identified: AI coding tools build fast, but the results look like a hodgepodge. Disconnected screens. Generic UIs. No cohesion.

Design OS is a methodical design process that happens before your coding agent touches the backend. You design actual frontend components, not mockups, then export production-ready code that any AI agent can implement.

The workflow:

Product planning (define what you’re building)
Design sections (build real components)
Export (hand off to AI agents)

Finding Flow with AI

Casel describes a new rhythm emerging in AI-assisted development. From his Finding Flow video:

“There’s no rhythm to it. Just a lot of starts and stops.”

His solution is a repeating 3-step cycle that keeps momentum going while keeping the developer engaged as the architect driving the project.

Key Takeaways

Principle	Implementation
Spec before code	Write requirements before prompting AI
Standards injection	Teach agents your conventions once
Design before backend	Build UI components, then hand off
Tool independence	Don’t lock into a single AI vendor

Links

Next: Geoffrey Litt’s Malleable Software