AI-Native Work Glossary
The vocabulary of AI-native engineering work in plain language, with how many open roles on the board match each term.
Agentic workflows
Software where an AI model plans steps, calls tools and acts on the results in a loop, instead of answering one prompt at a time.
AI engineer
A job title for engineers who build products on top of AI models: calling model APIs, building retrieval, agents and evaluations. Not the same as AI-native work, which is a way of working open to any role.
AI-assisted
Our label for listings where AI tools are used alongside conventional engineering. The role is still a normal engineering job; the tools are part of how it gets done.
AI-first
Our label for listings where AI tools are central to the work and the person is expected to operate them every day.
AI-mentioned
Our label for listings where AI appears only in vague terms or as the company's product area, with no named tool the person must use. These roles are hidden on the board by default; turn them on in the filters.
AI-native
A way of working where AI tools are part of the daily job rather than a side experiment. On this board it describes roles, not companies: a listing counts when it names AI tools the person is expected to use.
Claude Code
Anthropic's coding agent. It works in the terminal and your codebase, reading files, running commands and making edits.
Cursor
An AI-first code editor built on VS Code, with chat and agent features built in.
Evals
Repeatable tests that measure how well an AI system does on your own tasks. Teams use them to catch regressions when a prompt or model changes.
Forward deployed engineer
An engineer embedded with customers to deploy and adapt a product to their environment, mixing software engineering with customer-facing work. Common at AI companies selling to enterprises.
GitHub Copilot
GitHub's AI coding assistant, with completions, chat and an agent mode inside editors.
LangChain
An open-source framework for building applications around language models, with building blocks for prompts, tools and retrieval.
LangGraph
A library from the LangChain team for building stateful, multi-step agents as graphs.
MCP (Model Context Protocol)
An open standard from Anthropic for connecting AI models to tools and data sources through one common interface.
Prompt engineering
Writing and refining instructions for language models to get reliable output. It is rarely a job title any more; it shows up as a skill inside other roles.
RAG (retrieval-augmented generation)
Fetching relevant documents and giving them to a model when a question is asked, so its answers rest on your own data.
Vector database
A database that stores embeddings, numeric representations of text or images, so you can search by meaning. Common in retrieval systems.
Vibe coding
Building software by describing what you want to an AI model and steering the result, rather than writing most of the code by hand. The term was coined by Andrej Karpathy in early 2025.