Recent Posts
LLMs as Tools, Not Oracles: A Practical Framework for Effective AI Use
How to Leverage Large Language Models for Real Impact Without Falling for the Expert Illusion
LLMs mimic expertise but lack true reasoning. Learn how to use them effectively with a 2x2 framework for matching tasks to strengths.
The Brute-Force Illusion: Why Bigger AI Models Aren't Smarter
Scaling Delivers Capability, Not Comprehension
Brute-force AI scales capability, not intelligence. Explore the limits of scaling, from logic failures to inefficiency — and the path to smarter design.
AI: A Field, Not a Buzzword
From Symbolic Logic to Neural Networks — Why AI's Diversity Matters for Engineers
AI isn’t one thing. Explore its diverse techniques — symbolic AI, neural networks, and more — and learn why engineers must understand the differences.
The Invisible Engineer: Why Your Best Work Disappears (And How to Fix It)
How to prove your impact when prevention is your superpower — and silence is the reward
Proactive engineering prevents disasters — but who gets credit? Learn how to make invisible work visible.
Test-Driven Development: The Pragmatic Path to Software Correctness
How executable examples mitigate bugs from ambiguous requirements — the root of 60–80% of defects
TDD bridges the gap between ad-hoc testing and formal verification. Learn how test-driven development catches 80% of bugs early — with minimal overhead.
Containerized Embedded Development: The Right Tools for Reproducible Workflows
Podman vs. Docker, DevContainers vs. Codespaces — how to choose tools that actually work for hardware debugging, team collaboration, and CI
A practical guide to Podman vs Docker and DevContainers vs Codespaces for embedded workflows, hardware debugging, collaboration, and CI.