AI writes most of the code now. These pages cover what actually works, what doesn't, and why.
Understand the Problem
Spec-Driven Development
The spec is the product. One spec, many implementations.
What the Model Knows
The model knows how to code. Your job is telling it what to build.
Vibe vs Spec
When to chat with AI vs. write structured specs. Different tools for different problems.
The Solution Space
Every prompt maps to possible outputs. Specs narrow the space. Vague prompts don't.
The Telephone Game
Information degrades at every layer. LLM chains make it worse.
The Abstraction Paradox
Hiding complexity from AI doesn't remove it. It moves the debugging later.
Approaches
Matrix Methodology
Compose context from requirements, templates, and architecture. Our approach.
Ralph Loop
Read plan, do task, verify, update. Autonomous execution with fresh context each cycle.
GSD
Get Stuff Done. Structured prompting for real projects.
BMAD
Break down, map, assign, deliver. Multi-agent orchestration.
Thought Experiments
Specs as DNA
Specs encode intent like DNA encodes organisms. Same spec, different environments, different output.
Code Diffusion Model
LLMs resolve code from noise like diffusion models resolve images.
Fuzzy Compiler
A compiler that accepts natural language. No syntax errors. It just guesses.
Concepts
Continuous Evolution
Spec-driven development for live systems. Work from diffs, not regeneration.