AI-Native Engineer
Someone who designs the environment agents work in: loops, specification, context, and responsibility. Not "a dev who uses Copilot".
Learn to design the environment in which AI agents work: specification, context, validation, and responsibility.
Code stops being the central artifact. The central artifact becomes the environment: specifications, agents, context, validation, and responsibility.
Vocabulary, tools, and method for moving beyond the demo and owning the system that produces the software.
The terms you need to keep reading this site, plus vibe coding: where it helps, where it breaks, and how to turn a demo into real software.
Understand the difference between tools, products, and models so you can choose IDEs, CLIs, cloud agents, and LLMs with intent.
Spec-Driven Development (SDD) turns intent into a verifiable plan. Harness Design organizes tools and validation so agents can deliver with quality and safety.
Someone who designs the environment agents work in: loops, specification, context, and responsibility. Not "a dev who uses Copilot".
A program that pursues a goal in loops: it observes the environment, plans, acts with tools, checks the result, and repeats. Unlike a chat that only answers, an agent executes: it edits files, runs tests, navigates.
Large Language Model — the "brain" that gives the AI agent its intelligence. Wired into the harness, the LLM processes the SDD definitions, analyzes the repository context, and makes mathematical decisions on every cycle.
The primary artifact that defines the specification and the working method. The agent implements and validates the work from the definitions in the Spec.
The environment around the model: instructions, tools, memory, checks, and limits. It is the chassis the agent runs on, and it determines the quality of what comes out.
When the theory clicks, put it to work: build an AI-Native project from scratch with your coding agent and publish it to GitHub Pages.