Different work calls for different ways to use AI.

When AI can produce analysis directly, the durable advantage moves from output volume to problem framing, evidence, and decision quality.

Data analysts and analytics leaders · Data Analytics team session

AI should expand the questions a data scientist can answer—not merely shorten the time to the next query.

Data scientists · Data Science team session

AI first makes reports, plans, and other work evidence abundant. As those signals lose scarcity, value moves back toward problems, judgment, responsibility, and real-world results.

Knowledge workers and leaders rethinking what remains valuable when AI makes work evidence abundant · Long-form video argument · public cue-card edition

A strong strategic analysis challenges the starting view, clarifies what is tangled, and turns judgment into action. AI can build the 60-point factual base; people must push the judgment to 90.

Strategy, business analysis, and AI leaders · Delivered · Judgment Engineering strategy briefing

Strategy teams do not lack information. The scarce work is turning information into organizational judgment—and preserving the context so the next cycle starts further ahead.

Strategy researchers and leaders · May 2026 session edition

A useful transformation coordinate system separates tool usage, workflow redesign, and new organizational capability.

Engineering teams and leaders · Delivered enterprise session for engineering leaders

AI adoption is not transformation. The real work is changing how a team builds, evaluates, and learns.

Engineering and technical leaders · Engineering leadership briefing

Move from one-off chats to agentic loops with context, evaluation, and standards that survive the first request.

Technical and non-technical builders · AI agent workshop

A side project is not only an income bet; it allocates time, reputation, and career capital. Use three ledgers—cash, commercial evidence, and durable assets—to decide when to stop, pivot, or double down.

Programmers and AI builders exploring side projects · Public talk deck · Career capital edition

AI makes building cheaper, but durable income still depends on demand, distribution, trust, retention, margin, and the willingness to keep taking responsibility.

Programmers and AI builders exploring side projects · Public talk deck · Commercial gates edition

The useful leap is not from one chatbot to another. It is from isolated conversations to a personal AI work system that compounds.

Professionals and investors without a technical background · Joint public online session

When non-engineers can build, the ceiling moves from using a tool well to redesigning an entire workflow.

Company-wide, cross-functional teams · Company-wide AI session

When production gets cheaper, judgment, context, trust, and coordination become more valuable.

Content, product, operations, and business teams · Company-wide productivity session

A 10x outcome rarely comes from a better prompt. It comes from changing the operating system around the work.

One-person-company founders · Founder workshop and live demo

When AI writes much of the code, beginners should learn to specify, inspect, debug, and own the result.

Founders and first-time builders · Hands-on workshop

The important move is not from one tool to another, but from asking for answers to building work that can be inspected and reused.

Knowledge workers and new builders · Public online session

The gap between using AI and creating value with it is a better problem, a complete workflow, and a reusable asset.

Creators and small-business operators · AI internal workshop

Introduce the joint operating team, show how AIE creates a two-way bridge between Shanghai and the global AI engineering network, and define a focused first cooperation package with the association.

Industry associations, technology companies, and ecosystem partners · Partnership briefing for the Shanghai AI industry association

FDE is not merely onsite delivery. Done well, it turns the customer frontier into a high-speed product learning loop.

Founders and product leaders · Public product and organization talk

Enterprise AI training should start with real role-level constraints, then connect capability progression, project practice, and reusable organizational assets.

Game development teams and learning leaders · Three-track custom training proposal · public-safe edition