Define the terms.Then build the roadmap.

Each seminar in the series taught part of the roadmap. Here are all seven rules, in order.

1. 01

   Define terms

   Seminar 1

   So every one of us means the same thing by the same words. Our terms and definitions are below.

2. 02

   Stay current

   Seminar 1

   The time between AI milestones has gone from decades to years to months. You can't keep up with it alone, and you shouldn't have to. Our AI Update covers what changed every two weeks.

3. 03

   Create barriers and rules

   Seminar 1

   Decide what you will adopt and what you will not hand over, and set the rules for who is allowed to touch what.

4. 04

   Keep the best

   Seminar 2

   Keep what already works and the people who make it work. Point AI where the money is leaking, not at what is already working.

5. 05

   Build a plan

   Seminar 2

   Scope the whole picture first, then build toward it. Built piece by piece, a tool does one thing well and can't grow.

6. 06

   Proven partners

   Seminar 2

   Choose partners with a track record in the exact thing you need. Otherwise you pay for their learning curve.

7. 07

   Security

   Seminar 3

   Protect your data and your machines. Know what leaves your walls, who can reach it and how every connection is secured.

Rule one is to define the terms. These are the definitions we teach, in plain language.

Artifacts

Our name for the elements of your truth: the documents, drawings and procedures an AI system answers from. Answers come from your facts and are never invented.

Chatbot

Just an interface. Text in, text out. The chat window is how you talk to an AI system, not the intelligence itself.

Closed source

Software whose code you can't read or change. You trust the vendor's black box.

Collapsing gap

The time between major AI milestones has shrunk from decades to years to months. Waiting is not a strategy, because the cost of waiting compounds.

Consuming AI

Chatting with AI for ideas and drafts. It's useful, but it's consuming AI, not using it. Using AI means putting it to work on your own operations and your own facts.

Doorman fallacy

The doorman was never only opening doors. The automatic door took over the opening, and lost the security, the welcome and the signal of luxury. AI should amplify the experts who hold your knowledge, not replace them.

Intelligent question

A real question, asked in plain language of your machines and your records, and answered from your own facts. It's the promise behind the name IQ+.

Large language model (LLM)

AI that learns from language and predicts the next word. Prediction, not rules.

Machine learning

AI that learns patterns from your sensor and machine data. On the plant floor you need machine learning and LLMs together: sensors predict, language explains.

Open source

Software anyone can read and anyone can improve. Critical software runs on it.

Pull request

How open source software improves: propose a change, review it, merge it.

Source of truth

Your own manuals, drawings, procedures and records. A trustworthy AI system answers from your source of truth, not from generic internet knowledge.

1. 01

   AI runs on your facts, not generic internet knowledge.

2. 02

   The gap is collapsing. The cost of waiting compounds.

3. 03

   AI augments your experts. It does not replace them.