The Industry section is the landing chapter of the AI Harness knowledge base. It consists of eight industry groups: AI Infrastructure, Embodied Intelligence, Software Engineering, Hardware R&D, Knowledge Collaboration, Data Science, Creative Industry, and Risk & Compliance. Each group opens with a group overview, then splits into several direction documents, bringing the Harness six-layer capability model into concrete scenarios of the industry.
The eight groups cover 45 directions in total: AI Infrastructure (chip / supernode / cluster & datacenter / training framework / inference framework / infra ops), Embodied Intelligence (brain VLA / cerebellum motion control / servo actuators / materials & sensors), Software Engineering (Agents / Coding / DevOps / SRE / Eval / Benchmark), Hardware R&D (chip design / chip verification / packaging / test / AI Infrastructure), Knowledge Collaboration (project collaboration / work products / document collaboration / RAG / knowledge management / workflow / BPM), Data Science (data / analytics / research / science / HPC / AI for Science), Creative Industry (manufacture / industry / media / creative / AI drama / AI animation), and Risk & Compliance (finance / compliance / legal / audit / security).
1. Reading Guide
A suggested order: first read the Whitepaper "Practice" chapter to build the six-industry landing picture, then enter the group overview of your industry of interest for its core conclusions and key judgements, and finally read the individual direction documents in depth.
AI Infrastructure: chips, supernodes, clusters & datacenters, training/inference frameworks, and infra ops — engineering landing on the AI infrastructure side.
Embodied Intelligence: brain (VLA), cerebellum (motion control), servo actuators, materials & sensors — the perception-decision-execution loop of embodied systems.
Software Engineering: agent engineering, coding, DevOps, SRE, Eval, Benchmark — the full R&D and delivery pipeline.
Hardware R&D: chip design, chip verification, packaging, test, AI infrastructure — digital collaboration for hardware R&D.
Knowledge Collaboration: project collaboration, work products, document collaboration, RAG, knowledge management, workflow, BPM — human-machine knowledge collaboration and organizational process.
Data Science: data, analytics, research, science, HPC, AI for Science — data-driven research and engineering.
Creative Industry: manufacture, industry, media, creative, AI drama, AI animation — intelligent content production.
Suggestion: decision-makers read each industry group overview; architects and engineers go deep into the direction documents of their industry; compliance and risk teams focus on the Risk & Compliance group.