How to read a job market without being lied to

Part I of Computing Careers 2026, free and complete. Not an extract — the whole method, the part that works on any career and does not age.

If you take this and never come back, you have got the most useful part.

1. Why 'career' is not a salary number

   Priya and Marcus both earn $95,000 a year. They are the same age and have the same years of experience. Their lives are not alike at all.

2. The anatomy of a bad statistic

   A number can come from a serious institution, be reported accurately, and still be close to useless. That is what the four cases below have in common, and why writing about computing careers reads as either too negative or too positive. You have probably repeated at least two of them.

3. The source hierarchy

   Every source of career data falls into one of five grades, and the grade tells you what a number from it is worth. Lower is better. Chapter 4 judged four bad numbers one at a time; this is the system that saves you doing that.

4. Reading AI-impact claims specifically

   One distinction clears most of the noise around AI and jobs. It is whether a number counts something that happened, or estimates something that might. No topic in this book attracts more noise, which is why it gets a chapter of its own.

5. How to check a school, a bootcamp or a certificate

   Training is the largest payment most readers of this book will make before they earn anything at all. It is also bought with the worst information in the book. A degree, a bootcamp, a certificate, a course: Chapter 5’s five grades of evidence all get spent here.

6. Your personal instrument panel

   This book will age, as every book of numbers does. What follows is how to check any career, in any country, yourself. After this you do not need this book to be your only source, which is the point.

Take it with you