AI, But Be Serious

If you’ve ever read a “10x with AI” thread and thought “okay… but how?”, you’re home.

Positioning

A public standard for AI clarity

No hype. No demos. Just ways of thinking you can actually use when real work is on the line.

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Doctrine
Truth over fluency

Fluent output isn’t proof. If it matters, we verify-before it becomes a confident mistake.

Doctrine
Scope is a feature

Great systems tell you what they can’t do-early-so you don’t get burned later.

Doctrine
Keep thinking

AI should raise your standards, not lower your responsibility.

Core essays

Read these and you’ll be dangerous (in a good way)

A short, curated set that upgrades how you think about AI.

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Field manual

How serious teams use AI without getting cooked

A simple way to use AI at work without breaking things or embarrassing yourself.

Step 1
Define the job

What is the output? Who will use it? What does “good” look like?

If you can’t write the acceptance criteria, AI can’t guess it safely.
Step 2
Constrain the system

Put instructions first. Separate context. Specify format. Provide one example.

Step 3
Force verification

Treat outputs as drafts. Require checks, citations, tests, or references-depending on the task.

Step 4
Ship responsibly

If it impacts people, money, health, safety, or reputation-add guardrails and review.

Principles

The rules we don’t break

These principles are what separates ‘AI content’ from professional work.

Say what it can’t do

Clear limits beat fancy claims. Scope prevents embarrassment.

Prefer evidence to eloquence

High-stakes work must be grounded: tests, references, or citations.

Keep the human in the loop

AI accelerates execution. Humans own responsibility.

Call to action

Build with AI like you build with electricity: powerful, controlled, and not romanticized.

Read a few posts. You’ll start spotting AI hype immediately-and know what to ignore.