Dimension.Know how it works.
In-depth handbooks on building AI systems and software that hold up in production, with news from the Academy.
Upskilling
A Notes System for Technical Learning
Good notes are written for future problems, not for the lecture. A small system with three kinds of note covers most needs.
Cybersecurity
Logging an AI System So an Incident Can Be Reconstructed
When an assistant does something wrong, you need to know what it saw, what it was asked and what it called. Logs are the only way to answer.
Careers
Independent Work in AI: Scoping Projects and Saying No
Freelance and contract work in AI fails most often at the scope, not the code. A few habits keep it honest.
AI Models
Tool Use and Agents: A Model That Can Act Needs Boundaries
Once a model can call tools, its mistakes have consequences. Design the permissions and checks before the clever part.
Upskilling
Debugging as a Way to Learn
A bug is a question the system answers for you. Learning to ask it well teaches more than many lessons do.
Cybersecurity
Incident Response When the Attacker Also Uses AI
Attackers can now draft phishing messages, scripts and reports quickly. Response plans need faster triage and clearer decision points.
Careers
Why Job Titles Tell You Less Than Your Work Samples
Titles are inflated, renamed and reused across companies. What you can show, and what others can check, carries more weight.
AI Models
Reading Benchmarks Without Being Misled by Them
A benchmark score summarizes a narrow test. The number is useful only when you know what the test measures and whether its questions leaked into training.
Upskilling
Closing Skill Gaps Across a Team
A team with mixed experience needs a shared baseline and room to practice inside real work. Both can be planned.
Cybersecurity
A Skills Roadmap for Security Professionals Moving Into AI
Security experience transfers well. The new skills are model behavior, data handling and building evaluations for AI features.
Careers
The Product Role When a Prototype Takes an Afternoon
Building is faster now, so the scarce skill is deciding what to build and why it matters to a user.
AI Models
What a Model Learns From Its Data, and What It Cannot Learn
Training data shapes what a model knows, how it writes and what it overlooks. The gaps are as informative as the strengths.
