Spec-Driven Development: Beyond Vibe Coding with Commands & Hooks

The current generation of AI coding assistants has a ceiling. The conversational, prompt-and-response model—what some call ‘vibe coding’—is great for generating boilerplate or solving isolated problems. But it falls apart when tasked with building complex, production-grade software. The unstructured nature of conversation lacks the rigor, reproducibility, and verifiability that professional development demands.

The industry is now moving towards a more powerful paradigm: Spec-Driven Development (SDD). It inverts the traditional power structure where code is king. In SDD, the specification is the program, and code becomes a generated expression of that intent. This shift is powered by a programmable environment built on two pillars: custom commands to encapsulate complex actions and event-driven hooks to create self-correcting, automated workflows.

This is how we stop talking to our code and start programming our development process.

The Limits of ‘Vibe Coding’

Conversational AI is a dead end for serious development because it lacks a stable, programmable interface. Through our work running an AI agency, we’ve seen these failures firsthand:

• It Creates Misalignment: Vague prompts lead to flawed assumptions. Architectural diagrams are open to interpretation. Without a single source of truth, teams, clients, and AI agents are never truly on the same page.
• It Lacks Rigor: Vibe coding encourages a ‘plan as you go’ approach, which often misses critical edge cases that a more formal process would uncover.
• It Forces the AI to Guess: When an agent is given a vague prompt, it is forced to assume user requirements. When it’s wrong, the result is wasted time and flawed output.

The Solution: A Programmable, Spec-Driven Workflow

A professional workflow requires turning the AI assistant from a conversational partner into a programmable platform. This is achieved by centering the entire process around a formal specification, manipulated and executed by a command-and-hook architecture.

1. From Prompts to Specs

The foundational change is to replace freeform prompts with structured, version-controlled specifications. A spec is not just a better prompt; it is a formal artifact that becomes the project’s unambiguous source of truth about the what and the why.

2. Commands as Executable Actions

Custom commands are user-defined actions that bundle a complex series of steps into a single, reusable instruction. For example, instead of a long prompt to set up a new feature, a /scaffold command can read a spec and deterministically create the required file structure.

This concept is now being fully realized by toolkits like GitHub’s Spec Kit, which provides a suite of commands to orchestrate the entire development lifecycle:

• /speckit.constitution: Define the project’s governing principles—coding standards, architectural rules, and quality requirements.
• /speckit.specify: Describe a feature. The tool automatically creates a git branch and a structured spec.md file.
• /speckit.plan: Provide technical direction. The agent generates a detailed implementation plan, data models, and API contracts.
• /speckit.tasks: The agent breaks the plan into a granular, ordered list of tasks.
• /speckit.implement: The agent executes the task list, writing the code and tests to bring the feature to life.

3. Hooks as Self-Correcting Loops

Hooks are the key to creating a truly agentic system. They are automated scripts that trigger in response to specific events, like an AI writing a file. The most powerful example is a post-write hook that validates code immediately.

File: scripts/validate.sh

#!/bin/sh
# $1 is the path to the file written by the AI

prettier --write $1
eslint --fix $1
npm test -- --findRelatedTests $1

# If any command fails, the AI sees the stderr output and can be prompted to fix its own mistake.

This creates a powerful feedback loop: The AI writes code, the hook triggers validation, and any failure is fed back to the AI for an automated fix.

The Deeper Philosophy: The Spec is the Program

This focus on executable specs might sound familiar. Many developers hear echoes of Test-Driven Development (TDD)—a methodology often criticized as dogmatic or impractical. The fear is that you’ll get bogged down in specs and lose the ability to make small, quick changes.

This comparison is fair, but it misses a fundamental shift in philosophy. The crucial difference lies in what we consider the durable asset. In traditional development, the code is the source of truth. SDD challenges this.

Plans and code are throwaway. The spec is durable.

An implementation is ephemeral. A codebase written in Node.js today might be rewritten in Go next year to meet new performance requirements. If the Node code is your source of truth, that rewrite is a monumental effort.

But if the spec is your source of truth, you simply create a new implementation plan targeting Go and regenerate the application. The core logic, user stories, and business value—the durable assets—are preserved. This allows for true architectural agility and parallel experimentation, which is impossible when a single codebase is considered sacred.

Conclusion: From Programming Code to Programming Intent

The future of AI-native development isn’t about finding the perfect conversational prompt. It’s about building a programmable environment where the AI is an extensible part of a deterministic, automated workflow.

By embracing Spec-Driven Development, we elevate our work from writing code to engineering intent. The spec becomes the central artifact—a precise, executable, and durable expression of what we want to build. This creates systems that are robust, predictable, and professional. With practical toolkits like Spec Kit leading the way, we are finally turning the promise of agentic development into a practical engineering reality.